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Item 1. Business

2026-02-25 compared with 2025-02-28 · 807 added, 1542 removed, 723 unchanged (76% of the section changed)

Recursion At-a-Glance

Discovering and developing effective new medicines is among the most challenging human pursuits due to the incredible complexity of biology, the vastness of chemical space, and both the ineffectiveness and inefficiencies in clinical development.

Today more than 90% of clinical trials fail.

Our Mission and Philosophy

Recursion was founded in 2013 to decode biology to radically improve lives by building the next generation biopharma company from the ground-up, leveraging the latest technology tools to help map and navigate the incredible complexity of biology, vastness of chemical space, and the broken drug development process.

We believe that rapid commoditization of artificial intelligence creates a once-in-a-generation market opportunity for companies with the ability to build the right datasets in biology and chemistry to win.

Our Competitive Advantage

That’s why we have invested heavily in creating one of the most sophisticated automated wet-laboratories in the world where robots and sensors help us conduct and digitize millions of real-life experiments each week, spanning cellular systems, chemical systems, tissue systems, and animal models.

We also partner with select companies to aggregate and relate data from patients and health systems at scale.

In addition, we command industry-leading computational capabilities including BioHive-2 (the fastest supercomputer wholly owned and operated by any biopharma company), and employ hundreds of data scientists, software engineers, and AI researchers who build software to automate our work and foundational AI models that help us see patterns in our data at scale.

Together our laboratories, data, software, compute, and team comprise what we believe is one of the most sophisticated operating systems for drug discovery on earth, The Recursion OS.

How we Create Value

We leverage the Recursion OS to deliver value in three ways:

1) our own pipeline of clinical and preclinical potential medicines focused in precision oncology, rare disease, and other niche areas of unmet need;

2) by discovering new medicines with large biopharmaceutical companies in some of the biggest areas of unmet need like neuroscience and inflammation;

and 3) by leveraging our tools, technology, and data for the benefit of other partners in targeted and limited ways.

Portfolio poised for value creation from a unified operating system.

1 Includes preclinical programs (programs expected to enter the clinic within the next 18 months).

2 Program milestones include data readouts, preliminary data updates, regulatory submissions, trial initiation, etc.

2024 Highlights & Progress

In 2024, we accelerated the next wave of AI-driven drug discovery and development, delivering key milestones across multiple clinical programs, advancing our transformative partnerships, unveiling major breakthroughs in foundation models, and by consolidating some of the best tools, technologies, and talent into what we believe is the leading company in the burgeoning field of TechBio.

Advancements in the Pipeline:

A potential best-in-class CDK7 inhibitor optimized using our AI platform, delivered early Phase 1/2 results demonstrating promising safety and preliminary efficacy, including a durable partial response in a late-stage metastatic ovarian cancer patient and stable disease across four other patients with solid tumors (e.g.

A potential first-in-disease oral superoxide scavenger for symptomatic CCM, confirmed safety and tolerability of chronic dosing in a Phase 2 study, with exploratory analyses suggesting lesion volume reduction on MRI and symptom stabilization as evaluated by change in mRS scores

• Clinical Advancements and Regulatory Milestones:

Initiated three clinical studies:

DAHLIA (Phase 1/2, REC-1245 for solid tumors and lymphoma), TUPELO (Phase 1b/2, REC-4881 for FAP), and ALDER (Phase 2, REC-3964 for recurrent C.

difficile infection), received IND clearance for REC-4539 (small cell lung cancer), CTA approval for REC-3565 (b-cell malignancies), and progressed REC-4209 (idiopathic pulmonary fibrosis) to IND-enabling studies

Advancements in Partnerships:

• Roche and Genentech:

Generated whole-genome and chemical perturbation maps in a gastrointestinal oncology indication and a whole genome neuroscience phenomap.

The neuro phenomap resulted in the exercise of a $30M milestone

Achieved $15M in milestones, advancing multiple targets in immunology and oncology into lead optimization

Completed 25 multimodal oncology data packages and delivery of LOWE, our LLM-orchestrated workflow software, to enhance research capabilities

• Merck KGaA (Darmstadt, Germany):

Advanced alliance to identify first-in-class or best-in-class targets across oncology and immunology

Advancements in Platform:

• Full Stack AI Powered Platform:

Our constantly evolving Recursion OS spans target discovery through clinical development, enabling efficient molecule design and testing for both first-in-class and best-in-class opportunities

• Breakthroughs in Foundation Models:

We’ve developed both unimodal and multimodal AI models like Phenom, MolPhenix, and MolGPS that accelerate our ability to make high-confidence predictions in our therapeutics programs

• Advancement in Causal AI Models:

Through collaborations with Tempus and Helix, we integrate real-world, scaled patient datasets with our proprietary internal data to deepen biological insights and better match our therapeutic candidates with target populations

• Emerging Focus on ClinTech:

We are using AI and machine learning to optimize clinical trial design, accelerate patient enrollment, and enhance evidence generation through data-driven methodologies

In 2025, we plan to accelerate our pipeline with additional clinical readouts, deepen existing partnerships, and further expand our proprietary data suite.

We anticipate up to 10 additional clinical program milestones over the next 18 months, exciting milestone achievements in our R&D collaborations, and continued breakthroughs in AI-driven discovery, advancing our mission to decode biology to radically improve lives.

Significant milestones from our portfolio of pharma R&D partnerships and a focus on monetizing select assets in our pipeline will help to subsidize continued investment to expand our leading position in the TechBio space, which we view as a generational opportunity for value creation.

Business Overview

Recursion is a leading clinical stage TechBio company with a mission to decode biology to radically improve lives.

We aim to achieve our mission by industrializing drug discovery using the Recursion Operating System (OS), a vertical platform of diverse technologies that enables us to map and navigate trillions of biological, chemical, and patient-centric relationships utilizing approximately 65 petabytes of proprietary data.

The Recursion OS integrates ‘Real World’ data generated in our own wet-laboratories or by select partners and a ‘World Model’ which is a collection of AI computational models we also build in-house.

Today, our scaled ‘wet-lab’ biology, chemistry, and patient-centric experimental data feed our ‘dry-lab’ computational tools to identify, validate, and translate therapeutic insights, which we can then validate in our wet-lab to both advance drug discovery programs and to generate data to further refine our world model.

Recursion is a clinical-stage TechBio company with a mission to decode biology to radically improve lives.

We have advanced a portfolio of differentiated internal programs and strategic partnerships powered by our integrated drug discovery and development platform, the Recursion Operating System (OS).

This platform provides end-to-end, AI-native capabilities that span from novel biological ideas through the clinic, integrating multimodal biological data generation, AI-powered small molecule synthesis, and AI-enabled clinical development.

All of our technologies are designed to translate complex science into medicines that matter — faster, better, and at scale — for patients who are waiting.

Historically, it has taken over ten years and an average capitalized R&D cost of approximately $2-3.5 billion to move a drug discovery project from early discovery to an approved therapeutic, with less than 4% of drug discovery programs initiated resulting in an approved medicine.

1,2,3,4,5,6 Today, we are working to transform the traditional high-attrition, “V-shaped” discovery funnel by pivoting to a ‘T-shaped’ model.

By leveraging advanced computational tools across biology, chemistry and clinical development, we aim to rapidly narrow a broad set of potential medicines to the candidates with the highest probabilities of success, with the goal to move programs through development more efficiently and with less attrition.

Illustrative.

Reshaping the drug discovery funnel.

Recursion’s goal is to leverage technology to reshape the typical drug discovery funnel towards its ideal state by moving failure as early as possible to rapidly narrowing the funnel into programs with the highest probability of success.

In recent years, advances in artificial intelligence and machine learning (“AI/ML”) have increasingly influenced both the technology and biopharmaceutical industries.

Industry reports estimate that a majority of large biopharmaceutical companies now employ AI/ML in some aspect of drug discovery or development, and global investment in AI-enabled drug discovery has grown to several billions of dollars annually.

Regulators and policymakers have also engaged more actively in this area, with AI/ML-enabled approaches being applied across multiple stages of drug discovery and development, including target identification, molecular design, chemical synthesis, clinical development, and manufacturing.

We believe the increasing adoption of these technologies reflects a growing industry consensus that AI/ML has the potential to improve efficiency, decision-making, and productivity in drug discovery and development — the extent and timing of these benefits remain subject to ongoing validation and focus on proof-of-concept by leading players, including Recursion.

and Johnson, R.

Pharmaceutical Probability of Success.

Alacrita Consulting, 1-42.

2 Steedman, M, and Taylor, K.

Measuring the return from pharmaceutical innovation.

3 DiMasi et al.

Innovation in the pharmaceutical industry:

New estimates of R&D costs.

Journal of Health Economics.

4 Paul, et al.

How to improve R&D productivity:

the pharmaceutical industry’s grand challenge.

Nature Reviews Drug Discovery.

5 Martin et al.

Clinical trial cycle times continue to increase despite industry efforts.

Nature Reviews Drug Discovery.

6 European Federation of Pharmaceutical Industries and Associations (EFPIA).

The pharmaceutical industry in figures:

Key data 2024.

Our Strategic Focus Across Three Pillars

The Recursion OS provides a common foundation for mapping biology, navigating disease space, designing molecules, and optimizing clinical trials across therapeutic areas and modalities.

We deploy these capabilities to meet the specific differentiation and risk-reward needs of each program, tailoring our approach based on medical, market, regulatory, and capital considerations through a combination of internal pipeline development and strategic partnerships.

This approach allows us to balance near-term learning and proof generation with longer-term platform innovation, while allocating capital where Recursion has the highest confidence and greatest potential for differentiation.

The three strategic pillars described below reflect how we operationalize this model to drive disciplined value creation and impact.

Recursion’s strategy is organized around three core pillars, described below.

Pillar 1 – Translate insights to proof points – on the path to new medicines

A core pillar of our strategy is demonstrating that our AI platform can consistently translate scientific insights into medicines that deliver meaningful patient impact.

In 2025, we made tangible progress against this objective, including a positive clinical readout from our familial adenomatous polyposis (FAP) program, where our novel platform-derived insight, identifying the potential therapeutic benefit of MEK1/2 inhibition in FAP, translated into clinically meaningful reductions in polyp burden in a disease with no approved therapies.

We have several clinical-stage and multiple preclinical programs that are differentiated by novel biology, chemistry, and/or patient understanding from our platform.

We have achieved key progress-based milestones across multiple strategic partnerships that further validate the applicability of our platform across diverse aspects of discovery and therapeutic areas.

To date, we have received over $500 million in partner payments for novel data generation (e.g.

maps optioned by Roche and Genentech) and advancing AI-designed small molecule programs with Sanofi and others.

We expect to receive additional milestone payments as programs continue to progress.

Together, these advancements across our internal and partnered pipeline provide growing evidence that our approach can convert insights into early proof points.

Progress, by the numbers .

Includes preclinical programs that are expected to enter the clinic within the next 18 months.

Potential Roche and Genentech and Sanofi milestones per small molecule program.

Recursion is eligible for tiered royalties up to high single digits (Roche and Genentech) and up to double digits (Sanofi).

Pillar 2 – Focused innovation, grounded in clear impact

We have built an end-to-end, AI-native platform that spans biological discovery, small molecule design, and clinical development, and our strategy is to continue investing selectively in capabilities that improve the probability of success, speed, and confidence of scientific and clinical decision-making.

For example, a key area of focus in 2025 was the build out of our ClinTech capabilities, where we are applying data, automation, and AI to enable more efficient trial design, patient stratification, and evidence generation.

Leveraging our Recursion OS platform, we have also been able to advance small molecule drug candidates that potentially solve complex design problems, while synthesizing approximately 90% fewer compounds than the industry average.

Looking ahead, we will continue to direct resources toward platform capabilities that address critical bottlenecks in research and development and that we believe can drive durable differentiation and long-term value creation.

The Recursion OS.

Recursion generates massive quantities of rich, high-dimensional real world –omics data (e.g., phenomics, transcriptomics and proteomics) and chemical data.

We build and train ML and AI models that take the data and learning from the real world to understand and identify patterns and insights, using the fastest supercomputer wholly owned and operated by any pharmaceutical company globally (based on available data).

This creates a virtuous cycle of learning and iteration based on real-world data and models that learn to simulate that real world.

This virtuous cycle, i.e., the Recursion OS, generates value through our pipeline, in addition to building pipelines for our partners.

We have demonstrated that the Recursion OS already accelerates the timelines and scale of drug discovery, and we hope to prove in the coming years that we not only meet the industry average probability of success in clinical development but exceed it.

If successful in achieving our mission, we may be able to build one of the most valuable businesses in our industry while also improving the lives of patients and pushing down the cost of healthcare.

Over time, we believe our transformational way of designing and developing drugs can change the industry's underlying pharmacoeconomic model, what we call 'shifting the curve'.

We aim to demonstrate that it is simultaneously possible to improve probability of success through designing better quality drugs while also reducing investment requirements through improved technologies and process.

Recursion was created to take advantage of the discontinuity between these fields and harness the power of accelerating technological innovations to improve the efficiency of drug discovery and development.

The Recursion OS – A Platform that Powers a Portfolio

The Recursion OS is a full-stack solution delivering technology-enabled first-in-class and best-in-class molecules with speed, efficiency, and scale from target discovery through early clinical development.

We generate and aggregate enormous quantities of high-quality, high-dimensional data spanning hundreds of millions of cellular perturbations across biology and chemistry, translational experiments, ADMET experiments, in vivo experiments, patient data, and from scaled automated chemical synthesis.

In parallel, we have built foundation models that leverage those data to learn and understand the underlying biological and chemical interactions with broad predictive capabilities.

Recursion’s World Model approach (1) Profile biological and chemical systems using automation to scale a small number of data-rich assays, including phenomics, transcriptomics, InVivomics, and ADME to generate massive, high quality empirical data;

(2) aggregate and analyze the resultant data using a variety of machine learning models, in a process coordinated with in-house software systems and tools;

and (3) map and navigate leveraging proprietary software tools to infer properties and relationships in biology and chemistry.

These inferred properties and relationships serve as the basis of our ability to predict how to navigate between biological states using chemical or biological perturbations, which we can then validate in our automated laboratories, completing a virtuous cycle of learning and iteration.

Our competitive advantage compared to the hundreds of companies both large and small that seek to follow our path is the intense focus and early success in verticalizing this approach.

The company began by pioneering a point solution to scaled target discovery and hit ID based on phenomics, the use of cell morphology and computer vision.

Today, we are generating, aggregating, or simulating data from patients to cells, cells to pathways, pathways to proteins, proteins to atomistic interactions, cells to organoids, organoids to animals, and animals to people in the clinic.

We're systematically capturing complex, high-dimensional datasets, training specialized machine learning and AI models, and building foundation models that synthesize insights across diverse data layers.

As we combine and coalesce these foundation models, spanning target discovery through clinical development, we are increasingly building a ‘world model’ that contains within it a virtual representation of how biology and chemistry are working.

Today, our world model is enabling us to make many high-confidence predictions about the result of previously untried or untested questions.

In the coming years we believe that our world model will attain a level of understanding of biology and chemistry of sufficient quality that our wet lab will move from data generation for model improvement as its primary use to ‘scaled validation of simulated solutions.’ In essence, our world model will become a ‘virtual cell’ where we can simulate an inexhaustible quantity of ‘experiments,’ identify those targets and chemistries that have the highest probability of success in modulating disease and achieving a desired (and automatically generated) Target Product Profile, and then our wet lab can validate those predictions at scale.

Over time, models can become broadly applicable and performant enough to be the first rather than last step in the process, that is “move to the left” in the diagram, with Real World Models serving to validate individual insights “on the right.”

Building a Pipeline

Building on a first-in-class and best-in-class OS platform after the business combination with Exscientia, Recursion’s pipeline now encompasses 10 clinical and preclinical programs and over 10 advanced discovery programs across oncology, rare diseases, and other areas of high unmet need.

This broad and rapidly evolving portfolio reflects our commitment to advancing discovery and clinical development through unbiased, scaled scientific insights and AI-driven discovery.

Programs in our internal pipeline are built on unique biological and chemical insights surfaced through the Recursion OS where:

• The etiology of the disease is well defined, but the subsequent impacts of the disease are generally obscure and/or the primary targets are typically considered undruggable,

• There is a high unmet medical need, no approved therapies, or significant limitations to existing treatments.

The power of our Recursion OS exemplified by our expansive therapeutic pipeline.

1 Includes non-small cell lung cancer (NSCLC), colorectal cancer, breast cancer, pancreatic cancer, ovarian cancer, head and neck cancer.

2 Joint venture with Rallybio.

Advancing our Pipeline

The Recursion OS is designed to use AI to advance and accelerate decision-making and insight across the entire R&D value chain with the end goal to make novel medicines that matter.

The Recursion OS generates value by advancing a pipeline of differentiated investigational medicines, in addition to building pipelines for our partners.

Pillar 3 – Pair bold ambition with disciplined execution

Our strategy emphasizes pairing long-term ambition with disciplined execution, clear prioritization, and prudent capital allocation.

We apply rigorous go/no-go decision-making across our portfolio and focus resources on programs and initiatives where we believe we have a true strategic advantage.

Actions taken in 2025, including prioritizing our clinical portfolio and streamlining operations, reflect this disciplined approach and are intended to support sustainable execution over the long term.

Going forward, we will continue to balance investment in innovation with operational and financial discipline, aligning resources with our highest-impact opportunities while maintaining flexibility as we advance our mission.

Foundation – Empowering exceptional, bilingual teams to deliver impact with humanity

As Recursion works to transform how better medicines are brought to patients, we believe a new, integrated culture is essential to success.

A core foundation of our strategy is our people, which we view as a critical operating advantage in translating platform capability into real-world impact.

Recursion has intentionally built integrated, bilingual teams that operate fluently across science, computation, and engineering, enabling tight collaboration between wet-lab experimentation, model development, and clinical strategy.

We continue to invest in our people and teams to reduce friction across workflows, accelerate iteration, and ensure that experimental design, AI models, and development decisions are informed by a common context.

Paired with a culture that emphasizes rigor, accountability, and disciplined execution, this talent model is expected to enable us to pursue bold scientific ambition while consistently delivering progress toward medicines that matter — with speed, confidence, and humanity.

Building a Pipeline – Wholly Owned and Partnered Discovery

Our combined wholly-owned and partnered pipeline represents the primary vehicle for translating novel insights and capabilities from the Recursion OS into tangible medicines.

We utilize a wide range of AI and automation to achieve differentiation in biology, chemical design, and clinical development, targeting areas of high unmet need with a speed and precision unique to our AI-native approach.

The progression of the portfolio through clinical development represents a critical step in validating our OS-driven methodology.

Our goal remains for these proprietary insights to be translated into successful clinical outcomes across our internal focus areas of oncology and rare disease, as well as for our partners across oncology, neuroscience, immunology, and other therapeutic areas with high unmet need.

All of our programs target differentiated medicines in select patient populations.

Advancing our Wholly Owned Pipeline

We are accelerating critical clinical milestones while delivering measurable progress against diseases with high unmet medical needs.

At the same time, we continue to validate various components of the Recursion OS, which has played a role in advancing every program in our portfolio, reinforcing its potential to accelerate drug discovery and development.

We have already demonstrated promising safety and preliminary efficacy data for two of our programs.

REC-994, a superoxide scavenger in development as a potential first-in-disease therapy for symptomatic CCM, was featured in a late-breaking oral presentation at the 2025 International Stroke Conference.

Phase 2 data highlighted MRI-based lesion volume reduction and symptom stabilization trends.

Next steps in this program will be informed by regulatory discussions and long-term extension data expected in 2025.

REC-617, a potential best-in-class CDK7 inhibitor has demonstrated early clinical activity in advanced solid tumors, including a durable partial response in metastatic ovarian cancer and stable disease across patients with multiple tumor types.

These findings support further clinical development as we continue to explore its potential in combination regimens.

In parallel, Recursion has recently initiated three other clinical studies:

DAHLIA (Phase 1/2, REC-1245 for solid tumors and lymphoma), TUPELO (Phase 1b/2, REC-4881 for FAP), and ALDER (Phase 2, REC-3964 for prevention of recurrent C.

difficile infection).

Additionally, REC-3565 (B-cell malignancies) and REC-4539 (SCLC) are expected to enter dose escalation studies.

REC-4209 (idiopathic pulmonary fibrosis) has progressed to IND-enabling studies and REV102 (HPP) IND-enabling studies have been initiated, further expanding our pipeline across oncology, rare diseases, and other areas of high unmet need.

To focus resources on programs with the strongest scientific rationale and the highest potential for near- and long-term impact, such as REC-4881 in FAP and REC-617 in advanced solid tumors, we streamlined our portfolio in May 2025.

As part of this prioritization, the clinical programs REC-2282 for NF2, REC-994 for CCM, and REC-3964 for C.

difficile were discontinued and/or partnering opportunities are being pursued.

Recursion’s wholly-owned clinical pipeline includes differentiated medicines across oncology and rare disease.

The current pipeline consists of 5 clinical programs and 2 preclinical programs with the potential to enter Phase 1 pending go/no go decision.

Pipeline Highlights from 2025

In 2025, we reported the first clinical validation of the Recursion OS, with positive Phase 1b/2 results from our REC-4881 MEK1/2 inhibitor program in FAP.

The rapid and durable reduction in polyp burden observed in the Phase 2 portion of the TUPELO study shows how unbiased phenotypic and mechanistic insights from the Recursion OS, such as MEK1/2 rescue of APC loss-of-function, can translate to novel, differentiated therapeutics for diseases like FAP.

We expect to engage with the FDA to define a potential registration path for REC-4881 while further optimizing dosing schedule in the ongoing TUPELO trial, to continue to progress in this disease with no approved pharmacotherapies.

In parallel, Recursion has three other clinical studies ongoing:

ELUCIDATE (Phase 1/2, REC-617, CDK7i), DAHLIA (Phase 1/2, REC-1245, RBM39 degrader) and EXCELERIZE (Phase 1, REC-3565, MALT1i).

A fourth study, ENLYGHT (REC-4539, LSD1i) is expected to enter Phase 1 for solid tumors in 2026.

IND-enabling studies are ongoing for REC-7735 (PI3Kα H1047Ri) and REC-102 (ENPP1i), with the potential to enter Phase 1 studies pending go/no go decision.

Anticipated Near-term Catalysts

Recursion is poised for a catalyst-rich period, with multiple programs reaching critical milestones over the next 18 months.

REC-3565 (MALT-1i) will enter Phase 1 for B-cell malignancies, with the first patient expected to be dosed in the first half of 2025.

REC-617 (CDK7i) will initiate combination studies in advanced solid tumors in the first half of 2025.

REC-4881 (MEK1/2i) will report Phase 1b/2 safety and early efficacy data for FAP during the same period.

REC-2282 (HDACi) for NF2-related meningioma will undergo PFS6 futility analysis and REC-4539 (LSD-1i) will begin Phase 1 dose escalation in SCLC during the same period.

Additional Phase 1 data from the ELUCIDATE trial for REC-617 (CDK7i) in advanced solid tumors is expected in the second half of 2025.

Furthermore, we continue to rapidly advance development programs such as a PI3Kα H1047Ri and an ENPP1i towards the clinic.

Impact Through Partnerships

Through our business combination with Exscientia, we have doubled our partnership footprint with leading pharmaceutical companies including Roche and Genentech, Sanofi, Bayer and Merck KGaA (Darmstadt, Germany), securing $450M million in upfront milestone payments to date with the potential for over $20 billion in additional milestones before royalties.

Recursion is poised for a catalyst-rich period, with multiple programs reaching meaningful milestones over the next 24 months.

In the first half of 2026, we will engage with the FDA to define a registration path for REC-4881, and we will report early monotherapy safety and PK data for REC-1245 (RBM39 degrader) during the same period.

Go/no-go decisions on the initiation of Phase 1 studies for REC-7735 (PI3Kα H1047Ri) and REC-102 (ENPP1i) are expected in the second half of 2026.

Additional clinical data for REC-4881 (MEK1/2i), early combination safety and PK data for REC-617 (CDK7i), and early monotherapy safety and PK data for REC-3565 (MALT1i) will be reported in the first half of 2027, with early monotherapy safety and PK data for REC-4539 (LSD1i) reported in the second half of that year.

Impact Through Partnered Pipeline

Through our partnerships with leading pharmaceutical companies including Roche and Genentech, Sanofi, Bayer, and Merck KGaA (Darmstadt, Germany), we have secured more than $500 million in upfront and progress-based milestone payments to date, with the potential for over $20 billion in additional milestones before royalties.

These global collaborations not only provide near-term cash flows but also combine our scaled biology, precision chemistry, and automated synthesis capabilities to pave the way for transformative therapies in oncology, neuroscience, immunology, and other therapeutic areas with high unmet need.

By partnering with some of the best biopharmaceutical companies on earth in their respective areas, our platform and team have an opportunity to learn from some of the most experienced teams in the industry.

By partnering with some of the best biopharmaceutical companies in their respective areas, our platform and team have an opportunity to learn from some of the most experienced in the industry.

By uniting our AI-driven platforms, vast proprietary data, and deep scientific expertise, we continue to unlock powerful innovations and expand patient impact.

Below are some of the latest developments illustrating this momentum:

Designing molecules against difficult and diverse protein targets in challenging data-poor and data-rich environments

• Small Molecule Joint Portfolio:

Recursion is using its platform to discover and advance a joint portfolio of 5+ AI-driven and differentiated novel small molecule programs in immunology and oncology therapeutic areas.

The joint collaboration has the potential for up to 15 AI-driven small molecule programs.

• Milestones and Collaboration:

In February 2026, we achieved our fifth milestone across the collaboration, generating a $4 million payment from Sanofi.

In total, we have achieved $134 million in upfront and progress-based milestones to date.

There is potential for additional near-term milestones as the first programs advance towards development candidate milestones and earlier-stage programs progress.

Roche and Genentech:

Turning novel insights from proprietary digital maps of complex biology into potential novel therapeutics

• Neuron Map:

In partnership with Roche and Genentech, Recursion built the first whole-genome CRISPR knockout map generated from a subset of 1 trillion internally manufactured iPSC-derived neuronal cells ($30 million milestone payment, accepted in 2024).

This proprietary dataset is being used in partnership with Roche and Genentech to identify potential new targets in neuroscience, a field which has historically suffered from limited new discoveries.

• Microglia Map:

Recursion built and Roche and Genentech accepted a second neuroscience Phenomap, a first-of-its-kind whole-genome CRISPR knockout map generated from over 100 billion internally manufactured iPSC-derived microglial cells ($30 million milestone payment, accepted in 2025).

With approximately 46 million images, the scale and quality of this proprietary map enables us, in partnership with Roche and Genentech, to leverage the power of AI to explore novel targets and pathways.

• Gastrointestinal-Oncology Advancements:

In partnership with Roche and Genentech, we generated multiple whole-genome phenomaps with chemical perturbations across various disease-relevant cell types, enabling deeper insights into how different cellular contexts respond to gene knockouts and chemicals.

• Neuro-specific CRISPR KO Phenomap:

In partnership with Roche and Genentech, we have developed the first whole-genome CRISPR knockout map in neural iPSC cells, providing valuable data to identify potential new targets in neuroscience, an area with limited new discoveries.

We have built four proprietary Phenomaps which are being leveraged under the collaboration to identify novel insights that can be used to initiate programs for a gastrointestinal-oncology indication including continuing to advance one program optioned by Roche and Genentech.

• Milestones and Collaboration:

The neuroscience phenomap work led to a $30M option from Roche and Genentech in August 2024, and we’re moving forward with target validation projects.

• Immunology & Oncology Achievements:

We reached milestones in three programs, generating $15M in aggregate payments from Sanofi for two of these programs in 2024.

• Oncology Achievements:

Completed 25 multimodal oncology data packages utilizing the Recursion OS platform.

Multiple programs rapidly progressing to Lead Series nomination.

Additionally, Bayer was the first beta-user of our LOWE LLM-orchestrated workflow software to enhance their research capabilities.

In total, Recursion has received $213 million in upfront and milestone payments from the collaboration.

Roche and Genentech have accepted six Phenomaps and initiated one small molecule program based on Phenomap insights to date.

The companies have also identified a number of biological insights from Phenomaps that are now being validated or advanced as potential novel targets.

Developing programs in challenging oncology indications with high unmet need

With our partners at Bayer, we are advancing multiple programs towards lead series milestones in precision oncology.

Merck KGaA (Darmstadt, Germany):

• Our ongoing alliance with Merck KGaA, Darmstadt, Germany is focused on leveraging Recursion’s discovery engine to identify first-in-class and best-in-class targets across oncology and immunology, driving innovation in these key therapeutic areas.

Leading indications of success in our business combination with Exscientia

We believe that to truly redefine the way drugs are discovered and developed, we need to build technology tools and data across the full-stack of drug discovery and development.

Doing this well also requires the best talent from across many different fields.

While Recursion has, in our view, achieved more than any other TechBio company, we constantly survey the market to find potential opportunities to augment and accelerate our business.

The business combination with Exscientia was one such opportunity, bringing together the best biology-first TechBio platform in Recursion and one of the most comprehensive chemistry-first TechBio platforms in Exscientia, a compelling set of both first and best-in-class clinical programs, sector-leading partnerships and some of the best talent in the industry.

Given the compressed timeline between signing and close of the transaction (just over 3 months), prior to the close we prioritized in-depth assessments of each company's programs, partnerships, technology, capabilities, and ways of working.

With this information in hand, we then conducted an organizational design process that allowed us to provide go-forward status and role clarity for each employee within 48 hours of close.

We also outlined a set of goals to be accomplished in the first 90 days post close that will help us rapidly demonstrate the exponential value of the business combination and help employees to rapidly integrate across teams, portfolio, partnerships, and technologies.

We are already seeing the benefits of this approach in terms of amplifying delivery, though much more work remains to be completed through 2025.

In the weeks post-close we focused on ensuring all employees understood where they were situated within the go-forward organization (role, manager, etc.) and connected them with new members of their teams.

We wrapped 2024 with a 2-day Welcome Event in London, giving former Exscientians the opportunity to learn about Recursion, meet new colleagues across a variety of teams, celebrate their contributions to the deal close, and begin to shift their professional identity to that of a Recursionaut.

Before the transaction closed, we established a set of key goals to be achieved within approximately 90 days.

These goals were designed to quickly demonstrate early indicators of the value of combining the companies.

The goals largely focus on deploying relatively mature and unique elements of each company's technology to accelerate the other party's programs and processes.

These goals also require key members of each legacy team to sprint together, accelerating the team forming and norming process.

Key updates are as follows:

Using Recursion’s causal AI to optimize Exscientia clinical programs - LSD1 Patient Stratification:

• Recursion is utilizing AI models and Tempus data to build a patient stratification framework in small cell lung cancer (SCLC).

This work is informing clinical strategies for the planned REC-4539 Phase 1 study that originated at Exscientia and is commencing in the first half of 2025.

• We have expanded this work to explore indications for REC-4539 beyond SCLC and laboratory validation work is beginning imminently.

• This work will be used as a template to expand causal modeling for many programs beyond LSD1.

Use Exscientia’s Centaur Platform to Accelerate Recursion’s Internal Programs:

• Programs from legacy Recursion in early chemistry design cycles have already entered Exscientia’s Centaur precision chemistry platform, where significant improvements in potency have been demonstrated.

• Advanced protein structure predictions are guiding compound optimization, aiming to enhance binding conformation and optimize key properties.

• In-progress synthesis and cryo-EM work are enhancing our understanding of binding interactions, informing the next design cycles and optimizing compound characteristics.

Use Recursion’s Maps of Biology to Identify New Targets for Legacy Exscientia Partners:

• The Recursion OS has been used to identify hit compounds in 7 immune-relevant targets or dual target pairs and early validation work has commenced to prepare reports for our partners.

Accelerate Recursion’s Partnered Programs Leveraging Exscientia’s Centaur Chemistry Platform:

• We integrated Centaur into more than 10 design cycles for programs Recursion has previously partnered, with early validation work achieved and progress accelerating across multiple additional partnered programs.

• We have successfully delivered compounds for wet-lab testing on Recursion’s platform using the legacy Exscientia automated synthesis platform for partnered programs.

• Applied a newly built pipeline using structural bioinformatics and molecular dynamics for more precise compound design, focused on addressing specific design challenges on partnered programs.

Incorporate Exscientia Tech into Recursion’s Workflows:

• Reduced manual effort by 60% for evidence collection for hit nomination packages supporting entry into hit-to-lead, through knowledge graphs and LLM-based data aggregation with further reduction expected with additional data layers.

• Mapped 1.4 million active ligands to binding pockets for structure-based drug discovery and target deconvolution.

• Working to leverage Exscientia’s tools to achieve a 75% reduction in time-to-program nomination by increasing alignment with portfolio strategy and bridge phenotypic- to target-based drug discovery and facilitating target-centric and structure-based drug discovery within Centaur Chemist.

Integrate Recursion models into Centaur:

• To augment Exscientia’s chemical design platform with additional filters, experimental data for >950,000 compounds profiled in living cells were used to build two new models for (1) measurable cellular activity and (2) cytotoxicity.

These large datasets provide highly generalizable models demonstrating a >2.5x increased efficiency in detecting new bioactive scaffolds with a >40% reduction in the flagging of likely cytotoxic compounds.

• 18 new combined ADMET data products and respective models representing the combined organization’s datasets, and five program-specific phenomics response models have been added to Centaur, enabling use of legacy Exscientia’s active learning based precision design technology with Recursion internal programs.

Corporate Updates

• In order to continue to streamline its operations and focus on its core geographic footprint, the Company's fully owned subsidiary, Exscientia AI Limited ("EXAI"), will carve out its Austrian operations.

On February 27, 2025, the Company entered into an agreement to invest in and acquire 49% of the share capital of Alpha Biotechnology GmbH (“Alpha”), an Austrian startup that will leverage a patient-tissue platform for the development of precision therapeutics for the treatment of hematological and solid cancers, while focusing its efforts and moderating spend.

Alpha will in turn acquire 100% of the share capital of Exscientia GmbH, a wholly-owned Austrian subsidiary of EXAI which holds certain intellectual property assets crucial to Alpha’s operations and business activities.

The closing of the transaction is expected in the first half of 2025, subject to customary closing conditions.

A clear vision, durable mission and a focus on people and culture drive success

Recursion was founded in 2013 with a vision to capitalize on the convergence of advancements in computation and machine learning to address the decreasing efficiency of drug discovery and development.

We believe that this opportunity represents one of the most positively impactful applications of ML and AI.

Our vision is to leverage technology to map and navigate biology, chemistry, and patient-centric outcomes to increasingly transition the process of developing medicines from discovery to design.

We believe that advanced computational approaches, massive datasets or human intelligence alone cannot fundamentally shift the efficiency curve of drug discovery and development;

instead, we believe that those companies that augment their teams with sophisticated computational tools and focus deeply on generating and aggregating the right datasets will have a significant advantage.

Our success and the success of the burgeoning TechBio sector has the promise to drive more, new, and better medicines to patients at higher scale and lower prices in the coming decades.

We are working to not only lead this space – but define it.

Leveraging Recursion’s discovery engine to identify differentiated targets across oncology and immunology

• Oncology and immunology:

With our partners at Merck KGaA, we are focused on identifying differentiated targets across oncology and immunology and assessing target tractability using our precision design chemistry platform.

The Recursion OS – A Platform that Powers a Portfolio

The Recursion OS is a unified, AI-native operating system for drug discovery and development that integrates biology, chemistry, and clinical execution end-to-end.

Built on proprietary, multimodal data generated at unprecedented scale through automated wet and dry labs and partnerships, the OS combines large-scale phenomics, emerging omics layers, AI-driven chemistry design, and clinical development intelligence into a single, closed-loop system.

Powered by purpose-built models, scalable compute, and bilingual teams fluent in both science and AI, the Recursion OS enables faster translation of insights into proof points, reduces R&D bottlenecks, and supports the delivery of better medicines at scale for patients who are waiting.

Recursion combines proprietary multimodal data, purpose-built models and compute, and our bilingual teams and culture to create the first AI-native, end-to-end platform spanning idea through the clinic.

Rather than optimizing isolated steps, the Recursion OS improves decision-making across the entire R&D value chain—from decoding unknown biology and generating first-in-class targets, to designing synthetically feasible molecules, to selecting the right patients and executing trials more efficiently.

By systematically generating, integrating, and analyzing high-dimensional experimental and real-world data, we train purpose-built machine learning and foundation models that translate complex biology into actionable insights across discovery and development.

Throughout these processes, we are deploying AI agents and automated systems to help orchestrate our wet-lab experimentation and dry-lab modeling, standardizing workflows, coordinating data generation and analysis, and enabling faster, more consistent, and higher-confidence decisions at scale.

The Recursion OS.

The Recursion OS is designed to use AI to advance and accelerate decision-making and insight across the entire R&D value chain with the end goal to make novel medicines that matter.

The Recursion OS generates value by advancing a pipeline of differentiated investigational medicines, in addition to building pipelines for our partners.

As models are increasingly integrated across biology, chemistry, and clinical data, Recursion is building a systems-level representation of how biology and chemistry function.

This enables high-confidence predictions about previously untested hypotheses and shifts the role of the wet lab from primarily generating data to scaled validation of model-derived insights.

In practice, the platform is used to simulate and prioritize targets, mechanisms, and chemistries with the highest probability of clinical success and a well-defined target product profile, followed by rapid experimental validation.

Bilingual Teams and Culture – Fluent in Tech and Science

Our mission at Recursion, Decoding Biology to Radically Improve Lives , flows naturally from our vision.

2 unchanged sentences

We’ve intentionally designed our culture to fuel the pursuit of our mission.

Our Founding Principles are guideposts for scientific and technical decisions and our Values underpin how our employees engage day-to-day with colleagues inside and outside the company.

Our Guiding Principles are guideposts for scientific and technical decisions, and our Values underpin how our employees engage day-to-day with colleagues inside and outside the company.

The Recursion Mindset, a deep commitment to achieving impact at unprecedented scale through new industrialized approaches, is an essential component of building our TechBio ecosystem.

Our employees bring all these to life, contributing their unique expertise and experiences from their incredible breadth of fields and industries.

For all of our employees, Recursion is a unique company with a different way of working.

Recursion’s team requires operating at the interface of many diverse fields.

Building a TechBio company requires fluency in operating at the interface of many disciplines and fields not previously attuned to working as closely in traditional biopharma.

Recursion’s Founding Principles and Values support our ambitious mission.

Recursion’s teams operate at the interface of many diverse fields.

We have bilingual teams and cultures, scientists that understand AI, and AI researchers that understand science.

Recursion’s Guiding Principles and Values support our ambitious mission.

Together, these elements shape Recursion’s culture by guiding our people to high-impact decision-making and behaviors.

Recursion In-Depth

The Industrialization of Drug Discovery and Development Problem

The traditional drug discovery and development process is characterized by substantial financial risks, with increasing and long-term capital outlays for development programs that often fail to reach patients as marketed products.

Historically, it has taken over ten years and an average capitalized R&D cost of approximately $2 billion per approved medicine to move a drug discovery project from early discovery to an approved therapeutic.

Such productivity outcomes have culminated in a rapidly declining internal rate of return for the biopharma industry.

Historical biopharma industry R&D metrics.

The primary driver of the cost to discover and develop a new medicine is clinical failure.

Less than 4% of drug discovery programs that are initiated result in an approved therapeutic, resulting in a risk-adjusted cost of approximately $2.3 billion per new drug launched.

Despite significant investment and brilliant scientists, these metrics point to the need to evolve a more efficient drug discovery process and explore new tools.

Traditional drug discovery relies on basic research discoveries from the scientific community to elucidate disease-relevant pathways and targets to interrogate.

Coupled with biology’s incredible complexity, this approach has forced the industry to rely on reductionist hypotheses of the critical drivers of complex diseases, which can create a ‘herd mentality’ as multiple parties chase a limited number of therapeutic targets.

The situation has been exacerbated by human bias (e.g., confirmation bias and sunk-cost fallacy).

Accentuating this problem, the sequential nature of current drug discovery activities and the challenges with aggregation and interoperability of data across projects, teams and departments lead to frequent replication of work and long timelines to discharge the scientific risk of such hypotheses.

Despite decades of accumulated knowledge, the result is that drug discovery has unintentionally created hurdles for innovation.

Simultaneously, exponential improvements in computational speed and reductions in data storage costs driven by the technology industry, coupled with the rapid rise of LLMs, generative AI and other ML tools, have transformed complex industries from media to transportation to e-commerce.

Historically, the biopharma sector has been slow to embrace such innovations.

Over the past 2-3 years, there have been remarkable shifts in perception among technology and biopharma companies as well as among regulators and policymakers, who highlight the utility of AI/ML for broad drug discovery and development from novel target discovery to automated chemistry synthesis and next-generation manufacturing.

We believe this rapid acceleration and adoption of these technologies demonstrates the growing consensus that AI/ML is a catalyst for substantial leaps in drug discovery.

and Johnson, R.

Pharmaceutical Probability of Success.

Alacrita Consulting, 1-42

2 Steedman M, and Taylor K.

Measuring the return from pharmaceutical innovation.

3 DiMasi et al.

Innovation in the pharmaceutical industry:

New estimates of R&D costs.

Journal of Health Economics.

4 Paul, et al.

How to improve R&D productivity:

the pharmaceutical industry’s grand challenge.

Nature Reviews Drug Discovery.

5 Martin et al.

Clinical trial cycle times continue to increase despite industry efforts.

Nature Reviews Drug Discovery.

Late-stage clinical failures are the primary driver of reduced impact and IRR in today’s pharmaceutical R&D model.

Reducing the rate of costly, late-stage failures would be the most compelling way to achieve a more productive drug discovery and development process, though expanding the areas of biology that can be explored, accelerating the timeline from hit to a clinical candidate, decreasing the costs of discovery and creating more scalable systems would also create a more sustainable R&D model, all else held equal.

To achieve this more sustainable model, we believe that in its ideal state, a drug discovery funnel would morph from the being shaped like the letter ‘V’ to being shaped like the letter ‘T,’ where a broad set of possible therapeutics could be narrowed rapidly to the best candidate in a scaled and efficient way.

Subsequently, programs that advance through the remaining steps of the discovery and development process would proceed quickly and with no attrition.

While such a path is impossible to fully achieve, rapidly improving technology tools across biology, chemistry and computation are creating the conditions where, in the right hands, progress towards this ‘T’-shaped funnel is possible.

Reshaping the drug discovery funnel.

The Recursion OS provides an opportunity for mapping and navigating massive biological and chemical datasets that contain trillions of inferred relationships between disease-causative perturbations and potentially therapeutic compounds.

Collectively, the components of the Recursion OS can be joined together in a modular way to identify, validate and advance a broad portfolio of novel therapeutic programs quickly, cost-effectively and with minimal human intervention and bias - industrializing drug discovery and development.

We use standardized, automated workflows to identify programs and advance them through key stages of the drug discovery and development process which includes:

• Patient Connectivity and Novelty (i.e., program initiation)

• Hit and Target Validation

• Compound Optimization

• Translation

• IND-Enabling Studies

• Clinical Development

6 Steedman M, and Taylor K.

Ten years on:

Measuring the return from pharmaceutical innovation.

7 DiMasi et al.

Innovation in the pharmaceutical industry:

New estimates of R&D costs.

Journal of Health Economics.

8 Paul, et al.

How to improve R&D productivity:

the pharmaceutical industry’s grand challenge.

Nature Reviews Drug Discovery.

9 Martin et al.

Clinical trial cycle times continue to increase despite industry efforts.

Nature Reviews Drug Discovery.

Multiple -omics modalities within Recursion OS form a full-stack platform that spans the drug development pathway, incorporating patient-centric scaled biology, target exploration, hit discovery, lead optimization, precision chemistry design, automated chemical synthesis, predictive ADMET (absorption, distribution, metabolism, excretion, and toxicity), biomarker selection, translational capabilities, and clinical development.

Areas from legacy Exscientia platform indicated in orange.

We believe we have made progress in reshaping the traditional drug discovery funnel in the following ways:

• Broaden the funnel of therapeutic starting points.

Our flexible and scalable mapping tools and infrastructure enable us to infer trillions of relationships between human cellular disease models and therapeutic candidates based on real empirical data from our own wet labs.

• Identify failures earlier when they are relatively inexpensive.

Our proprietary navigation tools enable us to explore our massive biological, chemical, and patient-centric datasets to validate more and varied hypotheses rapidly.

While this strategy results in an increase in early-stage attrition, the system is designed to rapidly prioritize programs with a higher likelihood of downstream success because they have been explored in the context of high-dimensional, systems-biology data.

Over time, and as our OS improves, we expect that moving failure earlier in the pipeline will result in an overall lower cost of drug development.

• Optimize molecular design and synthesis through Centaur Chemist.

Our Centaur Chemist platform integrates AI-driven generative design with automated synthesis, enabling rapid iteration and optimization of new chemical entities.

By leveraging predictive modeling for potency, selectivity, and ADMET properties, we can efficiently generate high-quality, differentiated drug candidates while reducing synthesis timelines and experimental bottlenecks.

• Accelerate delivery of high-potential drug candidates to the clinic.

The Recursion OS contains chemistry tools that enable highly efficient exploration of chemical space as well as translational tools that improve the robustness and utility of in vivo studies.

• Enhance clinical development efficiency through ClinTech.

We are applying machine learning and AI to optimize clinical trial design, accelerate patient enrollment, and enhance evidence generation.

By integrating scaled patient data with predictive analytics, we aim to improve patient stratification, match therapies with the right populations, and reduce trial failure rates—advancing high-potential medicines to patients faster and more efficiently.

By leveraging our Recursion OS to explore and advance our programs, we have shown leading indicators of improvement when compared to the traditional drug discovery process, particularly with respect to cost and time.

We believe that combining Exscientia’s state of the art chemical platform with Recursion’s cutting edge OS will further enable us to (i) identify candidate compounds earlier in the research cycle, (ii) spend less per program, and (iii) expedite our drug discovery progress compared to industry.

Across >280 Recursion programs from late 2017 through 2024 the average amount of time to reach the validated lead stage is less than 13 months.

We also use AI/ML tools to better understand which molecules to make and test and ultimately design better quality molecules that can solve complex problems – on average, the industry synthesizes about 2,500 molecules to candidate, both legacy Recursion and legacy Exscientia synthesized 250, respectively.

Ultimately, we believe that future iterations of the Recursion OS will enable even greater improvements minimizing the total dollar-weighted failure and maximizing the likelihood of success allowing us to deliver better quality medicines to more patients in need.

Time from hypothesis screening to validated hit package for legacy Recursion programs.

(Center Left):

Legacy Exscientia compounds synthesized from hit to candidate ID.

(Center Right):

Total spend from hypothesis screening to the completion of IND-enabling studies for legacy Recursion novel chemical entity (NCE) programs that advanced to clinical trials.

The cost to IND has been inflation-adjusted using the US Consumer Price Index (CPI) (Far Right).

Time to validated lead is the average of >280 legacy Recursion programs since late 2017 through 2024.

The Recursion OS has not only improved speed and cost but also led us to explore novel targets which could give us a competitive advantage where multiple parties often simultaneously pursue a limited number of similar target hypotheses.

Below one can see quantitative measures for how we prioritize programs characterized by (i) strong genetically driven biological evidence and (ii) differentiated novel biology.

10 Paul, et al.

How to improve R&D productivity:

the pharmaceutical industry’s grand challenge.

Nature Reviews Drug Discovery.

We use LLMs and software tools to organize and initiate internal programs using both proprietary and public data.

We prioritize programs at scale by focusing on targets where our proprietary data provides a distinct arbitrage that suggests we can drive towards novel target identification and selection in oncology.

Each circle represents a gene that can be searched by the Recursion OS across several biological and pharmacological factors.

LLMs harness public datasets such as Cancer Dependency Map, Open Targets, TCGA, CCLE, and COSMIC and Recursion proprietary datasets such as phenomap inferences, Matchmaker assessments, InVivomics experiments, and ADME predictions.

At Recursion, we are pioneering the integration of innovations across biology, chemistry, automation, data science and engineering to industrialize drug discovery in a full-stack solution across dozens of key workflows and processes critical in discovering and developing a drug.

For example, by combining advances in high content microscopy with arrayed CRISPR genome editing techniques, we can rigorously profile massive, high-dimensional biological and chemical perturbation libraries in multiple human cellular contexts to create digital ‘maps’ of human biology.

Leveraging advances in scaled computation, we can conduct massive virtual screens to predict the protein targets for billions of chemical compounds.

Similarly, data generated from our automated DMPK module and InVivomics platform enables us to predict ADMET properties and identify toxicity signals, respectively, significantly faster than traditional methods.

And now, with the business combination with Exscientia complete, we can drive many of our programs from hit to development candidate using an automated internal chemical synthesis platform.

11 Ochoa, et al.

The next-generation Open Targets Platform:

reimagined, redesigned, rebuilt.

Nucleic acids research.

Recursion’s approach to drug discovery.

We utilize our Founding Principles on the right to build datasets which are scalable, reliable and relatable in order to elucidate novel biological and chemical insights and industrialize the drug discovery process.

We have used our approach to generate, aggregate, and integrate one of the largest proprietary biological, chemical, and patient-centric datasets in the world at approximately 65 petabytes at the end of 2024.

This dataset includes proprietary phenomics, transcriptomics, predicted protein-ligand binding interactions, InVivomics, ADMET data, and more across many biological and chemical contexts as well as preferred access to over 20 petabytes of multimodal oncology patient data from Tempus.

Additionally, we have built a proprietary suite of software applications within the Recursion OS which has identified over 7 trillion predicted biological and chemical relationships.

With our approach, we endeavor to turn drug discovery into a search problem where we map and navigate biology in an unbiased manner to discover new insights and translate them into potential new medicines at scale.

Competitive Landscape and Differentiation

There are a few key factors that differentiate Recursion from other technology-enabled drug discovery companies.

Recursion has built a full-stack platform utilizing many biology, chemistry, and patient-centric proprietary datasets and modular tools to industrialize drug discovery, while most other competitor companies rely on a point solution to solve one important step in drug discovery.

We recognize that drug discovery is made up of many steps, and a point solution is insufficient to generate efficiencies across the entire process.

To decode biology, we must construct a full-stack technology platform capable of integrating and industrializing many complex workflows.

Recursion integrates wet-lab and dry-lab capabilities in-house to create a virtuous cycle of iteration.

Fit-for-purpose wet-lab experimental data are translated by dry-lab digital tools into in silico hypotheses and testable predictions, which in turn generates more wet-lab data from which improved predictions can be made.

Recursion is well positioned compared to companies of a similar stage either focused more specifically on the wet-lab only (traditional biotech or pharma companies) or dry-lab only (companies facing rapidly commoditized algorithms and a challenge differentiating on non-proprietary data).

Recursion has achieved a significant scale with respect to its scientific, technological, and business endeavors.

With eight clinical-stage programs, an exciting preclinical pipeline, four of the largest discovery partnerships in the biopharma industry with Roche/Genentech, Sanofi, Bayer and Merck KGaA (Darmstadt, Germany), and four technology-focused partnerships, Recursion has achieved a scale, level of integration, and stage that few other TechBio companies have.

Value Drivers

While most small to medium-sized biopharma companies are focused on a narrow slice of biology or a single therapeutic area, the Recursion OS allows us to discover and translate at scale across biology.

However, we are cognizant that building disease-area expertise, especially in clinical development, is essential.

We have developed a multi-pronged, capital-efficient business model focused on key value-drivers that enable us to demonstrate our progress over time while continuing to invest in the development of the Recursion OS, which we believe is the engine of value creation in the long-term.

While our mapping, navigating and designing tools have the plasticity to be applied across therapeutic areas and modalities, our business model is tailored to maximize value and advance programs cost-effectively based on the nature of market and regulatory dynamics associated with our three value drivers (internal pipeline, transformational partnerships, and fit-for-purpose proprietary biological, chemical, and patient-centric data).

We harness the value and scale of our Recursion OS using a capital efficient business strategy.

Our business strategy is segmented into our following value-drivers:

(1) internally developed programs in capital-efficient therapeutic areas;

(2) partnered programs in resource-intensive therapeutic areas;

and (3) proprietary, fit-for-purpose data and models.

Value Driver 1 - Internally Developed Programs in Capital Efficient Therapeutic Areas

We believe that the primary currency of any biotechnology company today is clinical-stage assets.

These programs can be valued using a variety of models by stakeholders in the biopharma ecosystem and most importantly, present the potential to meet critical patient needs.

For Recursion, these assets have a variety of additional benefits, including:

(i) validation of key elements of the Recursion OS, (ii) growing our expertise in clinical development and (iii) building in-house processes to facilitate smooth interaction with regulatory agencies and advance medicines towards the market.

If the Recursion OS evolves as designed, then it will continuously improve with more iterations such that future programs could be more novel and potentially more valuable than today’s programs.

Operating as a vertically integrated TechBio company that leverages technology at every step from target discovery through clinical development (and even marketing and distribution) may be the long-term business model with the most upside for our stakeholders, including both investors and patients.

We may be opportunistic about selling or licensing assets after they achieve key value-inflection milestones so that we can re-invest in our long-term strategy.

Value Driver 2 - Partnered Programs in Resource Intensive Therapeutic Areas

We believe that in its current form, our Recursion OS is already capable of delivering many more therapeutic insights than we would be able to shepherd alone today.

As such, we have chosen to partner with experienced, top-tier biopharma companies like Roche and Genentech, Sanofi, Bayer, and Merck KGaA (Darmstadt, Germany) to explore intractable and resource-intensive areas of biology.

The key advantages of these partnerships are that:

(i) we are able to deploy the Recursion OS to turn latent value into tangible value in areas of biology where it would be challenging for us to do so alone;

(ii) the clinical development paths for these large therapeutic areas are often resource-intensive and highly complex;

and (iii) we are able to learn from our colleagues at these top-tier companies such that it could give us a competitive advantage in the industry over the longer term.

This strategy also embeds us in the discovery process of large pharmaceutical companies and gives rise to an alternative long-term business model whereby we become a valued partner of many such companies.

Based on how value is ascribed across our industry today, this model alone is not yet feasible to maximize our business impact.

However, we feel that due to shifts within the biopharmaceutical industry there is some potential for this portion of our business model to accrete notable value over the long-term.

Value Driver 3 - Proprietary, Fit-for-Purpose Training Data and Models

As has been demonstrated in many other industries, a value driver and competitive advantage can be generated from the creation of a proprietary dataset.

At Recursion, we have generated what we believe to be one of the largest fit-for-purpose, relatable biological, chemical, and patient-centric datasets on Earth.

Spanning multiple omics technologies and more than 300 million unique experiments, the approximately 65 petabytes of data that Recursion generates, aggregates, and integrates has the fundamental purpose of being used to train machine learning models.

Through intensive internal work, Recursion uses this data and our own models, algorithms, and software to advance our own internal pipeline of medicines (Value Driver 1) as well as in partnership with our collaborators to advance additional discovery programs (Value Driver 2).

As our field increasingly recognizes the potential for a technology-driven revolution in drug discovery, our data has increasing potential to drive value directly.

We increasingly see the potential to license select models and subsets of our data to a growing universe of collaborators for which internal efforts would be minimal, but value could be significant.

A Platform to Industrialize Drug Discovery

We have generated one of the largest relatable data sets in biopharma using our automated high throughput labs, which run over 2 million experiments per week.

Our data includes cellular phenomics, captured using Brightfield microscopy, as well as chemical synthesis, transcriptomics, proteomics, ADMET, InVivomics, genomics and patient data.

In total, we have approximately 65 petabytes of proprietary data which we use to train our algorithms and build our Maps of Biology.

In our relentless drive to continue building the most advanced full-stack AI-enabled discovery and development platform, we have now integrated Exscientia's Centaur Chemist platform for molecule design and automated synthesis capabilities with the Recursion OS, allowing us to rapidly move from target discovery to in silico design to physical compound testing.

And while we work daily to continue solidifying our data moat through wet-lab experimentation and simulation, our partnerships with Helix and Tempus give us access to hundreds of thousands of patient insights – including whole exome and whole genome sequencing – across a wide range of chronic diseases and in oncology.

By integrating even limited patient data into the Recursion OS, we can derive powerful new insights that directly fuel our pipeline.

We’re also using patient data to match our drugs to the specific patient population most likely to benefit, to improve the probability of success of clinical trials – where 90% of drugs in development fail.

Our unique platform approach has continued to evolve over time and we continue to lead the industry in innovation and delivery of potential treatments through our pipeline and partnerships.

When we first developed our phenomics-based biological map-making methods using HUVEC cells – creating over 100 billion cells per year for high throughput experiments, our work was dismissed by many.

Now, the early success of our pipeline and partnerships, and the broad adoption of our phenomics approaches across nearly every large pharma company in the industry, suggests a much deeper impact.

While others onboard technology we pioneered over a decade ago, we have moved to live-cell brightfield imaging and in partnership with Roche and Genentech, we built specific cell manufacturing technologies that derive neurons from hiPSCs at scale – ultimately producing over 1 trillion hiPSC-derived neuronal cells to build the world’s first whole-genome neuronal phenotype or “Neuromap,” triggering a $30 million payment.

Through our unique dataset and compute power, in the past year, we’ve launched a number of breakthroughs in foundation models – including powerful multimodal models like Phenom, MolPhenix and MolGPS.

These models give Recursion deeper insights into underlying disease biology and how cells might respond to treatment with new drug candidates, and provide the company with a distinct advantage when driving decisions about which therapeutic programs to pursue.

AI-native end-to-end platform from idea to clinic:

making novel medicines that matter

We have built an integrated, AI-native platform to decode complex biology and chemistry from multi-modal data into potentially transformative medicines.

The strength of our platform is not defined by a single asset or model, but by the scale and quality of our core capabilities and underlying infrastructure, including:

• Proprietary Data:

We have generated one of the largest relatable data sets in biopharma using our automated high throughput labs, which can run over 2 million experiments per week.

Our data includes cellular phenomics, captured using brightfield microscopy, as well as chemical synthesis, transcriptomics, proteomics, ADMET, genomics, and patient data.

• Models & Compute:

We use our proprietary data to train purpose-built AI models that accelerate learning and address specific bottlenecks across the R&D value chain.

We largely train models using our own supercomputer, BioHive-2, one of the largest supercomputers in biopharma, built in collaboration with NVIDIA.

• People & Culture:

A core differentiator is our people and culture—a unique, "bilingual" team of experts fluent in both life sciences (biology/chemistry) and technology (data science/engineering).

The Recursion OS.

The Recursion OS is the integrated technical and scientific vertical platform that underpins drug discovery and development at Recursion, from program initiation through our clinical trials.

Collectively, the components of the Recursion OS can be joined together in a modular way to identify, validate, and advance a broad portfolio of novel therapeutic programs quickly, cost-effectively, and with minimal human intervention and bias.

Connecting modules into a system allows us to quantitatively measure impact and make transformative improvements not just within local point solutions, but across the end-to-end drug pipeline, today and into the future.

To achieve this pipeline impact, the modules of the Recursion OS are connected by industrialized workflows that have been standardized, scaled, and automated.

To drive greater efficiency, we approach the building of modules and workflows similar to modular programming, but for biology and chemistry, so that the same fundamental capabilities are transferable across drug discovery and development activities and reflected in a diverse portfolio for both our internal pipeline and large pharma partnerships.

• Increased the sophistication of modules that improve earlier parts of the pipeline by integrating chemistry-centric models from Exscientia, including our industrialized workflows for chemical optimization enabling both functional- and target-based discovery, biology- and chemistry-centric approaches, and first-in-class and best-in-class compound opportunities.

• Integrated causal models and other analytics based on real patient data into both program initiation phases, ensuring patient connectivity and novelty, as well as clinical development activities, including patient stratification.

A unique advantage of this modular approach is that assay and model outputs become a long-lasting data asset.

This consistency, reliability and standardization allows us to build petabytes of data that can be connected across biological, chemical, and patient-centric sources, and across years of experiment execution, model insights, and data types.

Each type of data that Recursion generates in this manner becomes a vertical layer:

a computable dataset that can be used to build increasingly ever more complete and generalizable machine learning models to infer biological and chemical states (properties) and relationships, iteratively mapping and navigating trillions of inferred relationships between disease-causative perturbations and potentially therapeutic compounds.

(2) aggregate and analyze the resultant data using a variety of machine learning models, in a process coordinated with in-house software systems and tools;

and (3) map and navigate leveraging proprietary software tools to infer properties and relationships in biology and chemistry.

The creation of virtuous cycles of physical experiments and in silico models has been a competitive advantage for leaders in many industries outside of biopharma.

In drug discovery, virtuous cycles of experimentation and machine learning predictions is an approach to efficiently map and navigate biology and chemistry at unparalleled scale and efficiency.

Critically, at the scale Recursion operates, whole systems can be systematically and experimentally evaluated, such as the cellular level effect of individual gene knockouts not just for individual genes of interest, but across the whole genome.

Such comprehensive Real World data sets can underpin new generation AI-enabled Model World predicted states, where rather than individual model predictions, we create model representations to reason about and prioritize opportunities across large swaths of biology or chemistry, such as the hundreds of thousands of protein-protein interactions across the human interactome.

Traversing across layers can allow us to extract more insights and higher confidence than any layer on its own.

For example, patient data is the most relevant to human health and disease of all data modalities, but it suffers deeply from being intrinsically noisy, incomplete, expensive and difficult to collect.

In comparison, cellular phenomics data can be collected cheaply, at scale, with extreme data reliability and completeness.

In 2024, we have demonstrated that by combining patient level data with cellular level data, we can extract genetic causal targets from small (24,000) patient data sets that had previously required patient data sets of over one million in some cases to overcome challenges with patient data quality.

Similarly, we are exploring how protein-level data can add pathway interpretability and completeness to our cellular level data.

We believe that by computationally combining data layers across the micro-meso-macro, we can unlock many new, powerful efficiencies and insights along the drug discovery pipeline.

Highlights of Recursion’s achievements to-date in generating real world data and building a world model demonstrate progress on our delivery of Recursion’s mission to decode biology.

Towards a Virtual Cell – How Recursion is combining data and compute across different scales

By closely integrating real world experimentation and AI in an iterative manner, and across multiple ‘levels’ of biology, one can create cycles of virtuous learning, where large fit-for-purpose wet-lab datasets support better in silico model generation and enable more focused future wet-lab experiments.

Over time, this allows something powerful to emerge:

rather than a data-first approach underpinning World Model creation, our drug discovery opportunities emerge from the World Model, and Real World physical experimentation serves to validate the most promising insights.

The order of operations has swapped from experiments underpinning the creation of models, to a more scientifically comprehensive yet still more efficient approach:

World Model predictions being selectively confirmed by Real World experiments.

In essence, we will have created a Virtual Cell which we can test in nearly unlimited ways, selecting the most promising outcomes for validation in a Real World cellular system.

Over time, models can become broadly applicable and performant enough to be the first rather than a step in the process, that is “move to the left” in the diagram, with Real World Models serving to validate individual insights “on the right”

12 Internal data and analysis (2025).

13 TOP500 List (2024).

https://top500.org/lists/top500/list/2024/06/

Because the utility and impact on drug discovery would be so profound if achieved, a handful of compelling organizations, spanning academics to institutions to companies, are competing to build a Virtual Cell.

Success in this endeavor requires scaled hiqh-quality data, spanning multiple levels of biology alongside cutting-edge compute approaches.

We believe Recursion is uniquely positioned to lead at the intersection of these needs.

Scale and Quality.

Scale is achieved through three pillars:

• Automation:

Automation powers our labs, ensuring we create high-quality data outputs at industry leading scale.

• Relatability:

Output data is highly relatable allowing us to infer relationships and identify connections across many experiments.

• In silico models:

Scaled relatable data is used to train in-silico models to infer and predict experimental outcomes at scale far exceeding what is possible in the real world, which can then be validated at scale in our automated labs.

Spanning multiple layers of biology

Our Real World data layer and World model are built to use data across three scales:

macro, meso and micro.

The following section provides examples of these models based on each scale.

At the highest level, macroscale data informs on organism-level phenotypes and is typically deeply associative rather than causal – one can find associations between clinical outcomes and human observables, but the causal chain of how to go from variant to macro-scale phenotype is usually hidden.

Different size scales and data generation formats tend to have differing levels of interpretability, data quality and noise, costs, and data completeness.

In the middle, mesoscale data is measurements on cellular biological systems, such as phenomics and transcriptomics.

Here, we built our first in silico maps of biology and have historically executed our largest laboratory experiments.

At the smallest end, microscale data informs on molecular-level events like protein-small molecule binding and interactions and can enable insights at the level of target- and protein-interactions and properties.

It is the realm of many of our physics- and chemistry-centric models, and our protein sciences and biochemical laboratory assays.

Formation of a highly predictive Virtual Cell from scales of data layers that form Real World data and World model.

The macro data layer aims to find associations between clinical outcomes and human observables and determine causal chains of biology.

The mesocale data uses measurements on cellular biological systems, such as phenomics and transcriptomics, to build in silico maps of biology.

Microscale data uses molecular-level events, such as protein-small molecule binding and interactions using our protein sciences, biochemical assays, and physics- and chemistry-centric models, to enable insights at the level of target- and protein-interactions and properties.

Macro Scale Data Layers

Macroscale data informs on tissue-, organism-, and population-scale biology, enabling us to connect insights at the molecular (micro) and cellular (meso) levels to the behavior of drug candidates in patients, and to perform “reverse translation” of insights from patient populations to direct the initiation of programs at the beginning of discovery.

In 2024, Recursion built investments in macroscale biology in both model organisms for in vivo testing (InVivomics) and human populations, spanning cancer –omic data, population genetics data for non-oncology indications, and real-world clinical data.

InVivomics Data Layer

Recursion’s data layers combine to tell the story that our therapeutics will safely provide benefit to a patient.

Currently, in vivo experimentation is necessary to confidently translate the initial insights from high throughput experimentation in biology and chemistry to applications in the real world.

Our InVivomics platform removes human toil and bias from animal data collection.

Leveraging this platform maximizes data collection while minimizing human effort in key in vivo experimentation areas, in vivo pharmacology and toxicology.

REAL WORLD WORLD MODEL

Physical observations of animals including one million hours of video

Physical measurements (body weight, blood work, etc.)

Microchipping / collecting digital biomarkers for all animals

149,000 environmental datapoints

InVivoPrints Foundation Model to detect organ toxicities as early as possible and prioritize new drug candidates

In 2024, InVivomics produced important data that drove decisions across disease models in fibrosis, neuroscience, and oncology.

We integrated tolerability studies into our automated industrial workflows, streamlining the process from hit compound identification to animal model testing through a standardized set of experiments and decision criteria.

Our in-house execution of a lung fibrosis model helped accelerate the delivery of a molecule now progressing to clinical trials.

We also piloted studies in oncology and neuroscience.

In neuroscience, we introduced new endpoint measurements like rotarod and CMAP.

Developing this skill set and assessing how digital biomarkers can enhance and accelerate data not only supported an internal project decision but will also play a key role in advancing our partnership projects.

In total in 2024, we ran 62 InVivomic-informed studies at our Milpitas, CA facility.

Of those, 27 were mouse tolerability studies, delivering richer data to project teams as they design downstream in vivo pharmacology studies.

Across our internal portfolio, 7 projects leveraged this technology to inform dose selection as well as to evaluate impacts on specific tissues of interest.

We are also exploring the use of our digital system in rat toxicology studies, evaluating the advantage gained both with the richer constant-monitoring data as well as better connection to our other data layers.

We expect a data-driven evaluation in early 2025.

To extract maximum insights from this data, we also built a deep learning model called InVivoPrint V1 (IVP-1) that increases our ability to decode signals coming from these smart cages – detecting liabilities such as inflammation or toxicity earlier than our previous digital biomarker approach.

IVP-1 allows us to detect organ toxicities linked to a compound or dose candidate as early as possible during in vivo tolerability studies – and to prioritize new drug candidates for the efficacy phase.

Our current InVivomics dataset includes 1 million hours of video;

1 million hours of digital biomarkers such as locomotion, body temperature, wheel speed, and cage humidity levels;

149,000 environment data points, including cage slottings, rack used, rack room, sex, and birth time, as well as a number of other categories.

A Recursion scientist uses our in house dashboard to monitor digital readouts and live video of an ongoing animal experiment.

Human genetics data layer.

At the macroscale, patient omics and observational Real World Evidence (RWE) informs organism-level phenotypes, which is critical for discovering the underlying genetic associations of a particular disease.

As an independent data layer, human genetics has proven to be undeniably important for increasing the probability of clinical success.

Yet the full value of these patient datasets is limited by the fact that these data are inherently noisy, incomplete, and difficult to collect at a scale that allows for recall of sufficiently rare variants and disease phenotypes.

At Recursion, we have the capability to bridge our highly controllable, densely sampled perturbative map data (meso) together with observational patient data (macro) in a joint forward-reverse genetics approach.

Using human genetics, we can connect the macroscale down to the mesoscale to inform phenotypic discovery and deliver stronger, more disease-relevant and patient-connected insights.

While conversely, by integrating scaled meso data, we in turn increase the power and derive further value out of macro data above standard approaches.

REAL WORLD WORLD MODEL

Publicly available datasets including TCGA

Helix – non-oncology

Tempus - oncology

Historical and Recursion trial data

Non-patient trial data

Bootstrapping clinical genomics with phenomics to increase effective power of genetic association tests

Causal discovery models integrating reverse and forward genetics for target identification and program initiation

Causal inference models for patient biomarker identification and optimized selection strategies

In 2024, we expanded our real-world macro data layer by partnering with various clinico-genomics companies and acquiring other sources of RWE.

In addition to retaining access to over 20PB of de-identified oncology patient data through our partnership with Tempus, we are now partnering with Helix and have scaled access to hundreds of thousands of de-identified non-oncology patient records consisting of longitudinal clinical records paired with Helix’s Exome+® genomic data.

We are working with real world data (RWD) providers and continue to augment the foundational macro layer with non-patient trial data such as fit-for-purpose natural history, and both historical and Recursion trial data.

With the integration of these real-world macro and meso data, we built critical components of the Recursion world model to increase the effective power of genetic association tests, inform on patient causality, and enable the precise selection of patient populations based on causal insights.

In 2024, we demonstrated that we could extract genetic causal targets from small (24,000) patient data sets that had previously, depending on the target, required patient data sets of hundreds of thousands up to over

one million (3-67x increase in effective power).

Recursion believes this to be a new and plausible capital-efficient approach to rare variant discovery.

We also developed a generalizable causal discovery workflow combining macro-meso data features and applied these models for target identification and program initiation purposes.

This has led to over 60 genes identified through these causal models that are currently in testing on our validation platform.

Beyond discovery, these causal AI models are deployed to identify potential population expansions on current development programs.

We have also started testing causal inference models for predicting responsive patient populations to aid in biomarker identification and design optimized patient selection strategies.

Our diversification and expansion of our access to large-scale real-world data, has strengthened our foundation for building world models.

This included the integration of electronic health records, claims data, non-patient clinical trial data, and historical trial data.

These data sources are being leveraged to advance development through intelligent trial design —optimizing patient selection, trial protocols, and biomarker strategies based on predictive insights;

AI-powered clinical trial execution —accelerating patient enrollment via data-driven site selection, automated outreach, and dynamic recruitment optimization;

and multi-modal RWE application at scale —combining genomic, clinical, and claims data to inform decision-making across discovery, development, and validation.

Finally, we also accelerated patient enrollment with data-driven site selection and automated site outreach.

Looking ahead, we will expand and develop these components, and the industrialized workflows that integrate these into the Recursion OS to drive industrialized clinical development and increase probability of success for our clinical programs.

Meso Scale Data Layers

Mesoscale data at Recursion informs us about cellular biology and serves a unique role:

data on cellular systems integrates over biological pathways, revealing information about the multiple effects that individual molecules and targets may mediate to enhance translatability (polypharmacology), while simultaneously offering orders of magnitudes greater sample scale and interventional capability than macro-scale systems.

Recursion has built and applied two high-throughput mesoscale assays and data layers, phenomics and transcriptomics.

Phenomics Data Layer

Phenomics measures the morphology of cultured cells grown in laboratory plates.

Morphology is a holistic measure of cellular state that integrates changes from underlying layers of cell biology, including gene expression, protein production and modification, and cell signaling, into a single, powerful readout.

Image-based -omics can be two to four orders of magnitude more data-dense per dollar than other -omics datasets that focus on these more proximal readouts, enabling us to generate far more data per dollar spent to inform our drug discovery efforts.

Phenomics data on genetic and small molecule perturbations forms the backbone of Recursion’s Maps of Biology.

REAL WORLD WORLD MODEL

morphology provides a holistic measure of cellular biology integrating changes in gene expression and protein function.

Recursion can run up to 2.2M phenomics experiments per week.

Majority of Recursion phenomics capacity is now dedicated to multi-timepoint brightfield imaging, enabling measurement of cellular dynamics, beyond single endpoints.

BioHive-2 enabled continued scaling of Phenom models, with Phenom-2 demonstrating a 25.7% increase in expressed gene knockouts detected.

Phenom models demonstrate potential path to direct relatability between historical fluorescent phenomics data and new brightfield data.

Our real-world experimental phenomics data has historically been captured using multi-channel fluorescence microscopy;

through 2024, we transitioned the platform to acquire live-cell brightfield images, an imaging modality bringing the capability to measure dynamic cellular state across time, rather than at a single timepoint as is typical for fluorescence-based phenomics or sequencing.

In 2024, Recursion’s real-world phenomics experimental capabilities scaled to be able to generate up to 13.2 million cell paint images (110 terabytes) or up to 16.2 (135 terabytes) million multi-timepoint brightfield images across up to 2.2 million experiments per week.

Our state-of-the-art machine learning work in phenomics contributes deeply to the Recursion world model.

In 2024, Recursion demonstrated the power of scaling laws in machine learning with the training and deployment of Phenom-2, a larger version of the Phenom-1 phenomics model from 2023, making use of the increased computational power of BioHive-2 to improve the detection rate of expressed gene knockouts by 25.7%.

We further demonstrated the power of Phenom models on our data by training a Phenom-2-derived model to reconstruct fluorescent Cell Painting images from brightfield data alone, potentially enabling us to directly relate historical Cell Painting data to the brightfield data being collected today and in the future.

Predicting Cell Paint from Brightfield.

Phenom-derived models are able to accurately impute fluorescent stains from brightfield-only images.

Using paired brightfield and fluorescent phenomics (“Cell Paint”) data, Recursion scientists trained a Phenom-derived model to reconstruct fluorescent images from brightfield data.

Transcriptomics and new –omics data layers

Transcriptomics is a high-dimensional measure of cellular biology distinct from phenomics that assesses gene expression by measuring RNA levels in the cell.

Transcriptomics augments our mesoscale data acquisition in three key ways.

First, it enables independent replication, at scale, of effects detected in phenomics to verify that they are not morphology-specific artifacts.

Second, it offers a route to greater potential interpretability of high-dimensional biological effects by mapping perturbations onto identifiable genetic pathways.

Finally, it potentially enables the acquisition of new kinds of biological information, including both effects specific to the transcriptome and new perturbations inaccessible on our phenomics platform.

REAL WORLD WORLD MODEL

Generated >1.6M individual transcriptomes since its launch in 2023, with just under 1M generated in 2024

Built world’s first genome-scale CRISPR knockout map in primary human cells

Developed algorithms to orthogonally confirm phenomics results using arrayed transcriptomics replacing disease-specific confirmatory assays, with 90% ability to filter out compounds that would have failed such bespoke assays

Initiated work on scaled representation learning in transcriptomics

We acquire transcriptomics data in the real world using both an internally developed high-density bulk arrayed transcriptomics platform as well as a newly developed pooled single-cell transcriptomics capability.

In 2024, we have expanded our arrayed transcriptomics platform capability to enable the sequencing up to 62,000 wells per week and in 2024, generated just under 1 million individual transcriptomes of data.

This year, we augmented our platform with the capability to read out pooled perturbations by single-cell RNA sequencing and demonstrated this capability with what we believe to be the world’s first genome-scale CRISPR knockout map in primary human cells.

We continue to explore investments in –omics technologies beyond transcriptomics, including but not limited to proteomics and metabolomics.

Transcriptomics represents the first extension beyond phenomics in the Recursion world model.

In 2024, we applied Recursion algorithms operating on transcriptomic experiments confirming phenomics to replace time-consuming, disease-specific validation assays with a portfolio-wide multimodal analysis.

This analysis demonstrated a 90% ability to predict compounds that failed later disease-relevant assays in internal tests and 60% ability to predict compounds that passed later disease-relevant assays in internal tests.

The results of our whole-genome transcriptomic knockout map are now available for internal analysis in the Recursion Data Universe, and in 2025 we anticipate further development of scaled machine learning capabilities on transcriptomic data paralleling our historical development in phenomics.

Phenomics and transcriptomics can provide complementary views of biology.

In this figure, relationships between knockouts of genes involved in control of RNA transcription and protein translation are visualized, with relationships from phenomics in the lower triangle and those from our internal genome-scale transcriptomic knockout map in the upper triangle.

As a distal readout, phenomics sees similar effects on cellular biology from the loss of either transcription or translation.

By contrast, transcriptomics identifies opposite directionality of effect between knockouts of these two classes of genes, potentially offering higher resolution in certain areas of biology.

Micro Scale Data Layers

At the smallest end, microscale data informs on the key chemical and biophysical measurements needed to succeed in drug discovery.

This scale covers the molecular-level events, such as the binding events between compounds and their target proteins, as well as the chemical reactions involved in synthesizing and metabolizing these compounds.

Three data layers encompass this micro scale.

(1) Protein Target, (2) Chemical Data & Automated Synthesis, and (3) ADMET, each encompassing scaled data generation and state-of-the-art AI models to accelerate our design initiatives.

Protein Target Data Layer

Our protein target data layer measures the protein-ligand binding interactions that drive drug discovery.

Engaging protein targets with new compounds is a key driver in the development of effective medicines.

This data layer encompasses the development of new target-centric functional assays, the automated platform conducting these real-world experiments, as well as our suite of advanced physics-based simulations that yield accurate synthetic data.

These insights are captured by our state-of-the-art predictive chemistry models, using this data to guide automated design decisions.

REAL WORLD WORLD MODEL

In-house support for over 250 unique assay types

Over 50% fully unattended assay ready plate production

Co-folding & ABFE simulations

MolGPS Foundation Model

In 2024, we scaled and automated our experimental bioassay platform, which drives the testing phase of our precision Design-Make-Test-Analyze (DMTA) active learning loop.

The platform's key features include assay type diversity, speed of execution, and close integration with software tools to enable autonomous operation.

The platform currently supports over 250 diverse biochemical and functional assay types, allowing us to drive diverse, high-quality target-enabled programs.

All assay plates are prepared autonomously, without human intervention, with over 50% of assay plate preparations taking place overnight in unattended facilities.

Recursion enhances its automated bioassay platform with absolute and relative binding free energy simulations (ABFE/RBFE) of protein-ligand interactions and protein folding predictions, each serving a different purpose toward enhancing molecule design.

ABFE and RBFE are accurate molecular dynamics (MD) simulations of protein-ligand binding interactions, which evaluate new chemical design on structurally enabled targets by computationally determining their affinities to the target.

Our RBFE calculations have demonstrated an average accuracy of 1.3 kCal/mol.

These evaluations prioritize which designed compounds are made and tested.

From there, protein folding and co-folding predictions are used to locate the ligand binding and mechanistic targets responsible for observed biology activities detected by our meso data layers (phenomics and transcriptomics).

In 2024, we connected 1.4 million known active ligands mapped to specific pockets across a synthetic data layer of 3D human protein structures.

These relationships are used to identify tentative off-target interactions, binding site (and their key active residues), and to initiate subsequent structure-based modeling, including ABFE and RBFE simulations.

Bioactivity assays measured through the bioassay platform and sourced across the Recursion Data Universe are further modelled through a suite of state-of-the-art machine learning models.

Notably, activity models are built with our MolGPS foundation model pretrained on thousands of chemical properties and biological activities.

Together, each virtual model enhances the “Design” capability of the iterative Design Make Test Learning loop.

Interaction surfaces of a molecule as determined by fragment hotspot analysis.

Fragment hotspot maps are used to identify druggable sites on protein surfaces, and to map target similarity across a synthetic data layer of 3D protein structures.

Chemical Data Layer & Automated Synthesis

Our chemical data layer integrates precision design, state-of-the-art molecular property prediction, and fully automated chemical synthesis, with the goal of designing and producing high-quality, differentiated medicines for patients.

The precision design element transforms the drug discovery and development process.

It replaces the current conventional/conservative approach with an AI-first learning system that is well-suited to the complexities of drug discovery in each step of the process.

Our proprietary AI excels at generative molecular design, molecular property prediction and multi-parameter optimization - powering our platform to multiplex design against addressing more complex, desired profiles than conventional approaches, with synthetic accessibility at its core.

REAL WORLD WORLD MODEL

Automated chemistry platform

Reaction data generation

Automated purification platform

Generative design

ADMET/potency prediction

Retrosynthesis prediction

Reaction outcome prediction

The synthesis-first, generative design approach addresses a significant challenge posed by early generative methods, which frequently yield undesirable molecules that are difficult to synthesize.

Our approach represents a substantial advancement in generative design and can be considered a next-generation solution.

As we design molecules with AI-driven algorithms, our

platform, informed by our performant property prediction models, guides the design process towards compounds that are not only biologically and physiologically optimized, but also amenable to efficient synthesis on a unique, fully automated platform, suggesting the most cost and time-effective way to make the molecule with sophisticated retrosynthesis that is vendor-logistics-aware.

We capture reaction data, alongside bioassay data, and leverage active learning to ensure that our molecular property and synthesis prediction models continue to learn in step with the evolution of our pipeline, continuously refining our ability to identify the most promising molecules and predict the feasibility and success of future synthetic routes.

Recursion’s AI synthesis planning capability shows a 25% improved tractability assessment of AI-generated compounds over competitors and integrates with the Recursion OS.

Incorporation of our platform into our discovery processes has resulted in a 35% improvement in design cycle productivity, enabling our design platform to support a broad pipeline.

Recursion's automated chemistry wet lab, a modular system for chemical synthesis preparation, execution, analysis, work-up, and purification.

ADMET Data Layer

A durable truth in drug discovery is the requirement that we have confidence in our prediction of how our drugs will behave in patients.

We must enter clinical experimentation assured that we have a reasonable expectation that we will safely deliver benefit to patients.

A key part of building that confidence is early testing of a candidate molecule’s pharmacokinetic (PK) properties, which informs the likelihood that the drug will stay in a patient’s body for the right amount of time to be effective.

At Recursion we strive to generate critical decision-making data as early as possible.

Focusing our testing resources on compounds with higher likelihood to advance accelerates our mission to radically improve lives.

REAL WORLD WORLD MODEL

High throughput experimentation on RADME-01

Experimentation at CRO’s to add to our dataset

and inform project decisions

Publicly available datasets

Prediction of compound properties to inform probability of clinical success

Prediction of properties to inform the best compounds to advance

Prediction of properties to inform the best compounds to make

In 2024, we leveraged our high throughput ADME platform, RADME-01, to generate a bolus of data informing a compound’s likelihood to be viable.

The RADME-01 platform semi-autonomously runs a suite of ADME experiments including passive permeability, metabolic stability in liver microsomes, and non-specific protein binding.

Our platform has been operational since late 2023 and can evaluate two 384-well plates in all available assays each week.

In 2024, we tested 12,209 novel compounds through this system, supporting both Recursion’s internal pipeline and partnered projects.

Throughout the year the automation system evolved and refined, allowing for continually less human intervention.

A sophisticated in-house built software system intelligently prioritizes compounds and designs experiments to deliver highest value data while avoiding pitfalls related to compound analysis at scale.

Drug discovery project teams can use this data to prioritize higher quality compounds for subsequent evaluation, and we’ve also installed pre-set criteria for compound evaluation in our earlier (hit to lead) stage.

In this semi-autonomous loop, data is generated and compounds are nominated for in vivo PK testing without human effort or bias.

We are evaluating these criteria on a regular basis to ensure we are giving our projects the best chance at advancing high quality projects and compounds.

Another primary use of data generated on our RADME-01 platform is to train predictive models, capable of evaluating designs before synthesizing new molecules.

In 2024, we developed an automated machine learning framework that retrains and deploys new RADME-01 assay endpoint models weekly upon availability of new data, as well as several curated ADME property

These models included a broad set of properties such as intrinsic clearance, non-specific binding, solubility, efflux, drug-drug interactions, and several human PK parameters.

Our teams used these models for both internal pipeline and partnership projects both for prioritization of experimentation and prioritization of new molecule synthesis targets.

Recently, automated models derived from the RADME model were combined with their counterparts in the Centaur Chemist platform, further enabling rapid design compounds across both internal and partnership projects.

Our combined datasets revealed very little direct overlap and have expanded the chemical space our models are trained on.

The Exscientia and Recursion ADME datasets had few overlapping compound matches but were sufficiently representative to train ADME models with equivalent or improved performances across all endpoints.

Scientific agents and industrialized workflows

Agentic systems are artificial intelligence systems, typically large language model-based, that can pursue complex goals with limited human intervention.

They make decisions in a context-dependent manner and can learn and adapt through interaction with the world around them.

They are perfectly suited to workflow design leveraging the data layer and model inference-based modules of the Recursion OS, automating the design of workflows to meet a human or machine-stated objective.

Our goal at Recursion is to industrialize drug discovery and development through standardization and automation.

The early stages of our drug discovery process, filling the T-shaped funnel, benefits from standardization and exploitation of the program-agnostic data universe that Recursion has generated this past decade.

Industrializing later stages of drug discovery, where the focus is on molecular design, make and test in a program-specific assay cascade, requires context-dependent automation and exploitation of program-specific data.

Agentic systems, with their adaptability and flexibility, provide Recursion with the opportunity to industrialize the drug discovery and development process in its entirety.

The industrialization of drug discovery and development at Recursion is implemented via a series of Industrialized Workflows, each exploiting the Recursion OS to serve both the mission of decoding biology to radically save lives and the pipeline.

The first of these workflows, Initiation Workflow, offers a standardized approach to program initiation, the filling of the T-shaped funnel.

Its role is to generate and assess disease-gene hypotheses.

It succeeds by querying the patient data and maps of biology that reside in the data universe and, with help from a suite of Recursion OS models, hypothesizes which genes are associated with which diseases.

Large language model-based approaches are used to annotate these hypotheses with strategic insights collated from external, unstructured sources.

Such insights inform the biological relevance, novelty, commercial opportunity, competitor landscape, and the opportunity to differentiate.

LLMs are also responsible for assigning a score related to the strength of the hypothesized relationship between each disease-gene pair.

The industrialization of lead optimization requires a different approach.

At this stage, a program’s needs can be unique to that program.

The assay cascade may be different and the chemical series undergoing optimization will be different.

Recursion’s AI precision design platform, Centaur Chemist, enables computational and medicinal chemists to build molecular design workflows that design molecules that are synthesizable on our automated chemical synthesis platform and meet a particular design cycle objective.

Our precision design approach represents a constant interplay of automated data generation from experimentation and intelligent learning systems, embodying virtuous cycles of improvement in chemistry optimization.

Through our integrated platform, we can systematically encode the goals and strategy of each molecular design cycle, executing them through a sophisticated combination of scientific technology modules that form cohesive workflows.

Compounds progress through synthesis and testing, generating valuable data that are automatically captured in our integrated platform, along with valuable annotations from our medicinal chemists, ready to inform and enhance our predictive modules.

This closed-loop system helps translate design objectives into executable workflows, leveraging our 30+ scientific tech modules:

from 2D and 3D synthesis-aware generative methods to property prediction models, reinforced with physics-based thinking, and active learning approaches for compound selection.

As compounds are generated, synthesized, tested, and evaluated, the platform captures every decision point and experimental outcome, feeding this information back into our models to enhance future design choices.

This recursive learning process ensures each iteration becomes more precise and informed than the last, driving the evolution of a more intelligent and efficient drug discovery engine that continuously learns and adapts.

Industrializing lead optimization with an integrated design and synthesis workflow.

Processing and Data Storage Infrastructure

We believe modern drug discovery and development is a data and compute problem – the need to understand pathways, targets, compounds, and mechanisms of actions requires obtaining, synthesizing, or predicting large volumes of data.

To store this data in an efficient and low-risk way, Recursion makes use of a combination of cloud storage, and on-premises storage.

To process this data efficiently, we bring it close to where the compute will run – either in our HPC datacenter (BioHive) or to our cloud (partnering with Google Cloud).

To make this more seamless for our scientists, we have invested in a hybrid storage and compute platform, which enables replication of data and locality of compute to allow us to use these resources as efficiently as possible.

This year we expanded our partnership with Google Cloud to explore generative AI capabilities, including Gemini models, supporting the Recursion OS, driving improved search and access with BigQuery, and helping scale compute resources.

We currently have over tens of petabytes of unique data replicated across our sites for redundancy and resiliency.

We use this data to train state of the art (SOTA) foundation models of biology and chemistry and continue to push the limits of what is possible as we invest to scale up beyond Phenom-2 on the biology side, and bring unique Quantum Mechanics (QM) and Molecular Dynamics (MD) data to bear in our chemistry models like MolGPS.

We largely train these models using our own supercomputer which consists of two generations of DGX SuperPod, with 504 H100s, and 320 A100s, and over 65 TB of VRAM.

BioHive-2 is Recursion’s new NVIDIA DGX SuperPOD AI supercomputer, powered by 63 DGX H100 systems with a total of 504 NVIDIA H100 Tensor Core GPUs interconnected by NVIDIA Quantum-2 InfiniBand networking.

This NVIDIA-powered AI supercomputer results in over four times faster speeds than Recursion’s original supercomputer, BioHive-1, in benchmark performance tests.

Based on available data, BioHive-2 is the fastest supercomputer wholly owned and operated by any pharmaceutical company worldwide.

Bringing it together – Combining data scales to drive value

The vision of the Recursion OS is to integrate data and insights across biological scales to build a comprehensive and predictive World Model that deciphers biology with unprecedented efficiency.

Our ability to generate and leverage real-world data at scale—across macro, meso, and micro levels—has already begun to reshape how we approach drug discovery.

By combining these layers through the Recursion OS, we are moving toward an industrialized, AI-driven system that not only accelerates therapeutic discovery, but we also believe will help us to increase the probability of success in clinical development.

Our first demonstrations of this approach have successfully integrated macroscale patient data with mesoscale phenomics, allowing us to extract genetic causal targets from datasets previously considered too small for statistical power.

This methodology enables a capital-efficient approach to rare variant discovery, increasing our ability to identify novel drug targets that are deeply connected to human disease, and it is just the beginning.

At the mesoscale, we have advanced our phenomics and transcriptomics capabilities to provide high-throughput, high-dimensional insights into cellular biology.

By connecting these layers with microscale molecular interactions, such as protein-ligand binding and ADMET properties, we enhance the interpretability and mechanistic understanding of our drug candidates.

We believe that bridging across all three scales—macro, meso, and micro—will unlock a deeper understanding of human biology and significantly improve the efficiency of drug discovery and development.

One of the most transformative outcomes of our integrated approach will be the ability to construct a Virtual Cell—an AI-powered system that simulates biological responses at scale.

Traditionally, drug discovery has been an experiment-driven process where models are built from data collected in the lab.

At Recursion, we are reversing this paradigm:

our World Model is now driving the generation of new hypotheses, with real-world experimentation serving to validate the most promising insights.

By iteratively refining these AI-driven predictions with physical experiments, we are creating a feedback loop that accelerates learning and reduces reliance on trial-and-error experimentation.

As this approach matures, we envision a future where the Virtual Cell serves as a comprehensive digital twin for human biology, enabling us to model drug interactions, disease progressions, and therapeutic interventions in silico before ever entering the lab.

This shift—from experiment-first to model-first—has the potential to revolutionize how drugs are discovered, reducing both time and cost while significantly improving success rates.

Scaling Beyond What Was Previously Possible in 2024

In 2024, Recursion expanded its ability to industrialize drug discovery by enhancing the OS’s automation, scalability, and machine learning capabilities.

Key milestones included:

• The launch of BioHive-2, the most powerful supercomputer owned by any biopharma company, enabling the training of industry-leading foundation models like Phenom-2, MolPhenix, and MolGPS.

• The integration of Exscientia’s automated chemistry platform, which has already generated over 500 custom molecules in under nine days per cycle.

• The successful completion of the world’s first whole genome neuronal phenotype map (Neuromap) in partnership with Roche and Genentech, representing a significant leap forward in neuroscience drug discovery.

• The augmentation of our real-world data layer with hundreds of thousands of patient records through new partnerships with Helix and Tempus, dramatically improving our ability to connect patient-level insights with early-stage discovery.

• The rapid expansion of our transcriptomics capabilities, surpassing 1 million whole transcriptomes sequenced in a single year, reinforcing our ability to generate multimodal insights.

• The development of InVivoPrint V1 (IVP-1), an advanced deep learning model that enhances our ability to detect organ toxicities and prioritize drug candidates with greater precision.

The Road Ahead

Recursion is at the forefront of a new era in drug discovery, where data, AI, and automation converge to redefine the boundaries of what is possible.

The continued evolution of the Recursion OS will focus on:

• Further expansion of multimodal AI models that integrate patient-level insights with cellular and molecular data to refine drug target selection.

• Greater automation in preclinical validation through advances in high-throughput biology and AI-driven chemistry.

• Industrialized clinical development leveraging AI-powered trial design and patient selection to increase the probability of success.

• Scaling our Virtual Cell approach to predict and validate therapeutic interventions with unparalleled accuracy.

As we move forward, we remain committed to the mission that has guided Recursion from the beginning:

to decode biology to radically improve lives.

With our unique combination of scaled experimentation, AI-driven insights, and industry-leading automation, we are not just advancing drug discovery—we are fundamentally redefining its future.

Programs in our internal pipeline are built on unique biological and chemical insights surfaced through the Recursion OS where:

The etiology of the disease is well defined, but the subsequent impacts of the disease are generally obscure and/or the primary targets are typically considered undruggable.

There is a high unmet medical need, no approved therapies, or significant limitations to existing treatments.

Following the combination with Exscientia, we have expanded our internal and partnered portfolio, adding multiple programs across oncology, immunology, rare diseases, neuroscience, and more.

Beyond our 10 clinical and preclinical programs, we are advancing 10+ next-gen discovery programs for further development.

The power of our Recursion OS exemplified by our expansive therapeutic pipeline.

1 Includes non-small cell lung cancer (NSCLC), colorectal cancer, breast cancer, pancreatic cancer, ovarian cancer, head and neck cancer;

2 Joint venture with Rallybio.

Clinical Programs in Oncology

The Recursion OS is designed to use AI to advance and accelerate decision-making and insight across the entire R&D value chain with the end goal to make novel medicines that matter.

The Recursion OS generates value by advancing a pipeline of differentiated investigational medicines, in addition to building pipelines for our partners.

Our Portfolio

Our portfolio reflects the industrial scale of our discovery engine, comprising a robust pipeline of wholly owned programs alongside strategic partnerships with leading pharmaceutical companies.

This pipeline currently includes approximately five wholly owned programs in clinical development and roughly 15 discovery-stage programs spanning our internal and partnered efforts.

Each milestone across this diverse portfolio serves as a critical proof point for our ability to translate AI-native insights into meaningful clinical candidates, with the breadth of the pipeline providing multiple, concurrent opportunities to validate the Recursion OS as a transformative engine for drug discovery.

All pipeline programs leverage our platform, which has evolved, across biology to insight, insight to molecule, and molecule to patient.

We leverage and track how we use our platform across every single program.

some programs are focused on novel biological insight, design, or both.

Our Internal Pipeline:

Clinical Programs Overview in Oncology and Rare Disease

REC-4881 – Familial Adenomatous Polyposis

We are developing REC-4881, a highly potent and selective, potential best-in-class MEK1/2 inhibitor, for familial adenomatous polyposis (FAP).

FAP is a genetic condition characterized by the development of adenomas throughout the GI tract.

It is an orphan disease caused by inactivating mutations in APC, with most patients undergoing prophylactic colectomy due to nearly 100% likelihood of CRC by age 40.

During a collaboration with Takeda, we leveraged machine learning and automated analysis to quantify hundreds of cellular parameters linked to APC siRNA knockdown.

We screened numerous compounds in this genetic background within 24 hours and identified REC-4881 as a potent molecule that rescued the phenotype in a concentration dependent manner.

In preclinical studies, REC-4881 demonstrated over 1,000-fold selectivity in APC-mutant tumor cell lines and effectively inhibited spheroid growth and organization.

In the APC min mouse model of FAP, REC-4881 showed up to a 70% reduction in total polyps, surpassing celecoxib’s 30% reduction, highlighting its potential as a highly selective and efficacious therapy for FAP.

The IND was reactivated by Recursion and the Phase 1b/2 trial (TUPELO) of REC-4881 was initiated.

As of December 31, 2025, Part 1 of the study is complete and Part 2 remains ongoing.

In Part 1, which assessed safety, tolerability, and PK in FAP patients, REC-4881 was observed to have a safety profile consistent with other MEK inhibitors.

A 4 mg dose of REC-4881 was shown to be pharmacologically active in FAP and progressed to Part 2.

In May 2025, preliminary Phase 1b/2 data was shared at Digestive Disease Week 2025 for 6 patients following 13 weeks of treatment with REC-4881, demonstrating reduced polyp burden and an early safety profile generally consistent with that of prior MEK1/2 inhibitors.

Expanded data was shared in December 2025 for a larger cohort of FAP patients treated for 12 weeks with REC-4881, followed by a 12 week off-treatment phase.

Rapid reductions in polyp burden were demonstrated by week 13 (median polyp burden reduction of 43%), with a durability of effect and reductions maintained through the off-treatment phase at week 25 (median polyp burden reduction of 53%).

The safety profile of REC-4881 was consistent with MEK1/2 inhibition, with adverse events predominantly low grade and N=4 discontinuations.

This data provided the first clinical validation of the Recursion OS, from an unbiased phenotypic signal identifying MEK1/2 inhibition as a rescue mechanism for APC loss-of-function, through mechanistic confirmation and clinical translation, to positive clinical data.

In the first half of 2026, we expect to engage with the FDA to define a registration path while further optimizing dosing schedule in the ongoing TUPELO trial.

We expect to provide additional clinical data in the first half of 2027.

REC-617 – Advanced Solid Tumors

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CDK7 controls cell cycle progression and gene transcription, often overexpressed in advanced stage cancers reliant on transcriptional pathways.

This program utilized our generative AI and active learning platform to optimize molecule design, including non-covalent binding and ADME/PK for rapid absorption.

This program utilized our generative AI and active learning platform to optimize molecule design, including non-covalent binding and improved ADME/PK for rapid absorption.

This rapid design cycle enabled us to synthesize 136 novel compounds and select REC-617 as our lead candidate in under 11 months.

A multicenter, open-label, Phase 1/2 (ELUCIDATE) monotherapy dose escalation (QD and BID) study is currently ongoing in advanced solid tumors.

In December 2024, results from the initial 19 patients (18 response-evaluable at the time of cutoff) were presented at an AACR Special Conference in Cancer Research.

REC-617 monotherapy demonstrated signs of preliminary efficacy.

A multicenter, open-label, Phase 1/2 dose escalation and dose expansion study (ELUCIDATE) is currently ongoing in advanced solid tumors.

Initial results from 19 patients were presented at the 2024 AACR Special Conference in Cancer Research, with data from a larger cohort of 29 heavily pretreated patients reported in November 2025.

From this monotherapy dose escalation (QD and BID) portion of the study, REC-617 demonstrated signs of preliminary efficacy.

One heavily pre-treated ovarian cancer patient achieved a confirmed durable partial response (PR), which correlated with significant reductions in clinical tumor markers (CA125 and TK1).

Four additional patients achieved durable stable disease (SD) as their best response.

REC-617 was generally well-tolerated, with adverse events predominantly low grade, on-target, and reversible upon treatment cessation.

The MTD was not reached and there were no treatment-related discontinuations.

Monotherapy dose escalation (QD and BID) remains ongoing, and we expect to initiate combination studies in the first half of 2025.

We also expect to provide additional data updates from the Phase 1 in 2025.

Five additional patients achieved durable stable disease (SD) as their best response.

REC-617 was generally well-tolerated, with adverse events predominantly low grade and the most common DLTs being nausea and thrombocytopenia.

7% (N=2) discontinued due to a treatment-related adverse event.

The MTD was established at 10 mg once daily.

Monotherapy dose escalation remains ongoing to assess alternative dosing schedules, and in 2025 the ELUCIDATE study was expanded into platinum-resistant ovarian cancer (PROC), with a Phase 2 dose expansion monotherapy cohort ongoing and a Phase 1 dose escalation combination arm also initiated.

Initial combination regimens include bevacizumab plus paclitaxel or pegylated liposomal doxorubicin (PLD).

We expect to provide early safety and PK combination data in 2027.

REC-1245 – Biomarker-enriched Solid Tumors and Lymphoma

REC-1245 is a first-in-class, novel, potent, and selective molecular glue degrader of RBM39, a critical RNA-binding protein involved in alternative splicing and DNA damage repair (DDR) pathways.

Leveraging the Recursion OS, we discovered that genetic knockout of RBM39 can phenotypically mimic CDK12 loss – a validated DDR target –without impacting CDK13.

To our knowledge, we were the first to report this novel biological insight.

REC-1245 is a potential first-in-class, novel, potent, and selective molecular glue degrader of RBM39, a critical RNA-binding protein involved in alternative splicing and DNA damage repair (DDR) pathways.

Leveraging the Recursion OS, we discovered that genetic knockout of RBM39 can phenotypically mimic CDK12 loss – a validated DDR target – without impacting CDK13 which, to our knowledge, is the first report of this novel biological insight.

Utilizing our phenomics based platform for SAR, we synthesized 204 candidates and advanced this program from target ID to IND-enabling studies in 18 months (vs.

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Preclinical data confirmed strong anti-tumor activity, including tumor regressions in a BRCA-proficient ovarian cancer model, minimal off-target effects, and no CDK12 kinase inhibition.

With over 100,000 addressable patients in the US and EU5 each year, REC-1245 has the potential to be a novel therapy in a biomarker-enriched advanced solid tumors and lymphoma patient population – either as a monotherapy and/or in combination regimens.

Following IND clearance in September 2024, we initiated a Phase 1/2 (DAHLIA) study in December 2024 to evaluate the safety, tolerability, PK/PD, and preliminary efficacy of REC-1245 in unresectable, locally advanced, or metastatic cancers.

The trial is currently enrolling at three US sites and includes a biomarker-enriched population that may benefit most from targeted RBM39 degradation.

We expect to share an update on the Phase 1 dose-escalation portion of the study in the first half of 2026.

With over 100,000 addressable patients in the US and EU5 each year, REC-1245 has the potential to be a novel therapy in a biomarker-enriched advanced solid tumor and lymphoma patient population – either as a monotherapy and/or in combination regimens.

Following IND clearance, we initiated a Phase 1/2 study (DAHLIA) to evaluate the safety, tolerability, PK/PD, and preliminary efficacy of REC-1245 in unresectable, locally advanced, or metastatic cancers.

This includes a biomarker-enriched population that may benefit most from targeted RBM39 degradation.

In the third quarter of 2025, we reported updated information on the population being enrolled into the DAHLIA study, to include cancers with high genomic instability (for example endometrial cancer) and to confirm specific biomarker-enriched populations (for example 2L+ MSI-H/dMMR) based on early preclinical data that showed that REC-1245 reduces viability in tumors characterized by replication stress and DNA repair vulnerabilities (DDR defects) across multiple solid tumor types.

The trial is currently enrolling at sites in the US and Canada, and we expect to share early safety and PK data from the Phase 1 monotherapy dose-escalation portion of the study in the first half of 2026.

REC-3565 – Relapsed / Refractory B-cell Malignancies

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As a result, REC-3565’s enhanced selectivity supports the potential for a more favorable therapeutic index not only as a monotherapy, but also in combinations with BTK and BCL2 inhibitors.

A multicenter, open-label, dose escalation Phase 1 study (EXCELERIZE) cleared a CTA by the MHRA in December 2024.

We expect to dose the first patient in the first half of 2025.

REC-4539 – Small Cell Lung Cancer

REC-4539 is reversible CNS penetrant, orally bioavailable, and potential best-in-class inhibitor of LSD1.

A multicenter, open-label, dose escalation Phase 1 study (EXCELERIZE) is ongoing, with the first patient dosed in April 2025.

We expect to share early safety and PK monotherapy data in the first half of 2027.

REC-4539 – Solid Tumors and Hematology Oncology

REC-4539 is a reversible, CNS penetrant, orally bioavailable, and potential best-in-class inhibitor of LSD1.

LSD1 is an epigenetic enzyme that removes methyl groups from histones to control gene expression.

LSD1 is abnormally overexpressed in a broad spectrum of solid tumors including lung, breast, prostate, esophageal, and bladder cancers, as well as acute myeloid leukemia, with evidence suggesting that LSD1 is a promising therapeutic target.

This is exemplified within lung cancer by small cell lung cancer (SCLC).

SCLC is particularly dependent on LSD1 to maintain a neuroendocrine phenotype that drives tumor cell survival in this aggressive lung cancer subtype.

Preclinical studies demonstrate that REC-4539 shows anti-tumor activity in SCLC human xenografts with limited impact on platelets.

Our program used multi-parameter optimization to design a unique candidate combining reversibility with CNS penetration.

In AML, LSD1 has been shown to disrupt normal hematopoiesis by modulating key oncogenic pathways and transcriptional regulators like GFI1 and SNAI1.

Preclinical studies demonstrate that REC-4539 shows anti-tumor activity in SCLC and AML human xenografts with limited impact on platelets.

Our program used multi-parameter optimization to design a unique candidate combining reversibility with CNS penetrance.

We synthesized 414 novel candidates to arrive at our lead candidate in 22 months.

Following IND clearance in January 2025, we

expect to initiate a multicenter, open-label Phase 1/2 trial (ENLYGHT) in the first half of 2025.

We plan to target an SCLC patient population as well as additional biomarker-selected cancers following the dose escalation portion.

Clinical Programs in Rare Diseases

REC-994 – Cerebral Cavernous Malformation

We are developing REC-994, an orally bioavailable small molecule superoxide scavenger, as a first-in-disease opportunity for symptomatic cerebral cavernous malformations (CCM).

CCMs are rare vascular anomalies marked by abnormal capillary-venous structures, recurrent lesions, and stroke-like symptoms.

REC-994 was discovered using the earliest version of Recursion’s comprehensive drug discovery platform.

In an unbiased CCM2 loss of function phenotypic screen, REC-994 demonstrated concentration dependent rescue and was advanced into preclinical studies.

In animal models of CCM, REC-994 reduced the burden of CCM lesions by ~50%.

In addition, REC-994 also reduced the vascular permeability defects in CCM2-deficient mice, which is critical in CCM pathology.

This data supported the clinical development of REC-994, the first industry-sponsored trial for CCM.

In late 2020, initial results from the clinical program were reported and a randomized Phase 2 trial of REC-994 (SYCAMORE) was initiated in March 2022 in patients with symptomatic CCM.

In April 2024, the Phase 1 SAD/MAD study was published.

Initial results in September 2024 showed REC-994 met its primary endpoint of safety with encouraging trends in preliminary efficacy.

The drug was well-tolerated, with no treatment-related discontinuations or Grade 3-4 adverse events reported.

We presented the Phase 2 study data as a late-breaking oral presentation at the International Stroke Conference, or ISC, annual meeting in February 2025.

The data presented showed signs of safety and efficacy as follows:

• REC-994 met the primary endpoint of safety and tolerability in CCM patients with no treatment-related discontinuations, SAEs or Grade ≥ 3 adverse events related to study drug

• No new safety signals observed, with the incidence of adverse events comparable across arms

• No treatment-related adverse events that led to discontinuations

• 50% of patients on REC-994 400 mg (n=20) achieved a reduction in total lesion volume versus 28% of patients in placebo (n=18) and 24% of patients on REC-994 200 mg (n=17)

• Trends towards improvement and/or stabilization of symptoms for patients treated with REC-994 400 mg (n=19) compared to placebo, which observed trends towards functional decline, based on changes in the Modified Rankin Scale (mRS) score from baseline to 12 months

Similar trends of exploratory efficacy (lesion volume reduction and functional outcome improvement) were seen in the cohort of patients with brainstem lesions treated with REC-994 400 mg

Most (80%) patients who completed at least 12 months of treatment in the Phase 2 study elected to continue into the long-term extension (LTE) portion of the trial.

As of December 31, 2024, the LTE portion is ongoing.

As there are no therapeutic options for patients with symptomatic CCM, we plan to seek regulatory guidance from the FDA and additional health authorities on a path forward for this potential first-in-disease program.

We expect to share updates on next steps in 2025.

REC-4881 – Familial Adenomatous Polyposis

We are developing REC-4881, a highly potent and selective, potential best-in-class MEK1/2 inhibitor, for familial adenomatous polyposis (FAP).

FAP is a genetic condition characterized by the development of adenomas throughout the GI tract.

It is an orphan disease caused by inactivating mutations in APC, with most patients undergoing prophylactic colectomy due to nearly 100% likelihood of CRC by age 60.

During a collaboration with Takeda, we leveraged machine vision and automated analysis to quantify hundreds of cellular parameters linked to APC siRNA knockdown.

We screened numerous compounds in this genetic background for 24 hours and identified REC-4881 as a potent molecule that rescued the phenotype in a concentration dependent manner.

In preclinical studies, REC-4881 demonstrated over 1,000-fold selectivity in APC -mutant tumor cell lines and effectively inhibited spheroid growth and organization.

In April 2022, the IND was reactivated and in September 2022, the Phase 1b/2 trial (TUPELO) of REC-4881 was initiated.

As of December 31, 2024, Part 1 of the study is complete, and Part 2 remains ongoing.

We expect to share safety and preliminary efficacy data in the first half of 2025.

REC-2282 – Neurofibromatosis Type 2

We are developing REC-2282, a CNS penetrant, potential best-in-class pan-HDAC inhibitor, for neurofibromatosis type 2 (NF2).

NF2 is a rare genetic disease caused by loss of function mutations in the NF2 gene which leads to deficiencies in the tumor suppressor protein merlin.

REC-2282 was identified as a potential therapeutic capable of rescuing HUVEC cells treated with NF2 siRNA and subsequently in-licensed from Ohio State Innovation Foundation in December 2018.

We initiated the POPLAR study, an adaptive, randomized, multicenter Phase 2/3 trial in June 2022, with the first patient dosed in October 2022.

In November 2024, we announced that the trial was fully enrolled in the Phase 2 portion.

As of December 31, 2024, Phase 2 data is maturing, and we expect to share the results of the futility analysis (PFS6 rate) in the first half of 2025.

REC-3964 – Prevention of Recurrent C.

difficile infection

We are developing REC-3964, a non-microbial, orally bioavailable, potential first-in-class C.

difficile (C.

diff) toxin B selective inhibitor for the prevention of recurrent Clostridioides difficile infection (rCDI).

diff toxin B disrupts the tight junctions in colonic cells and increases vascular permeability, leading to a leaky gut.

REC-3964 is Recursion’s first new chemical entity to reach the clinic and binds and blocks the catalytic activity of the toxin's innate glucosyltransferase, while sparing the host.

In a human disease relevant C.

hamster model, REC-3964 demonstrated a significant difference in the probability of survival versus bezlotoxumab alone.

Our program leveraged an ML-aided conditional phenotypic drug screen in human cells and identified novel mechanisms that mitigated the effect of C.

toxin B treatment.

Through orthogonal validation screens, precursors to REC-3964 emerged as promising substrates for further advancement.

In June 2024, we presented Phase 1 data in healthy volunteers at the 6th Edition of World Congress on Infectious Diseases in Paris.

In October 2024, we initiated a Phase 2 open-label, randomized, 3-arm study (ALDER) to evaluate the rate of recurrence in patients with a high-risk of CDI, who have achieved symptom resolution following treatment with oral vancomycin for 14 days.

We expect to share initial results from the Phase 2 study in the first quarter of 2026.

Details on preclinical programs (e.g., ENPP1 inhibitor, Target Epsilon) will be shared in the next section.

Deep Dive into Clinical and Select Preclinical Programs

Following IND clearance in January 2025, the program was placed on strategic pause in May 2025.

While the broader field has faced safety challenges, REC-4539 remains highly differentiated by its optimized profile, with a potential improved therapeutic index through better management of on-target toxicities e.g.

reduced impact on platelets.

We now expect to initiate the Phase 1 trial (ENLYGHT) in the first half of 2026, with early monotherapy safety and PK data expected in the second half of 2027.

Deep Dive into Clinical Programs

REC-4881 for Familial Adenomatous Polyposis (FAP) - Phase 1b/2

REC-4881 is an orally bioavailable, non-ATP-competitive, allosteric small molecule inhibitor of MEK1 and MEK2 currently under development for familial adenomatous polyposis (FAP).

REC-4881 demonstrated dose-dependent increases in exposure and pharmacological activity, with a safety profile consistent with other MEK inhibitors.

We are currently enrolling patients in TUPELO, a Phase 1b/2, open-label, multicenter study to evaluate the effect of REC-4881 on polyp burden reduction.

Orphan Drug Designation in the US and EU as well as Fast Track Designation in the US were granted to REC-4881 for FAP.

Following positive clinical data from TUPELO shared in 2025, in the first half of 2026 we expect to engage with the FDA to define a registration path while further optimizing dosing schedule within the trial.

We expect to provide additional clinical data from TUPELO in the first half of 2027.

Disease Overview

FAP is a rare, inherited tumor predisposition syndrome affecting more than 50,000 patients in the US and EU5, resulting from autosomal dominant mutations in the APC gene, a key negative regulator of the Wnt signaling pathway.

FAP is a lifelong continuum of disease progression and intervention driven by chronic polyposis, with an almost 100% lifetime risk of colorectal cancer by the age of approximately 40 if untreated.

In adolescence and early adulthood, patients typically develop hundreds to thousands of precancerous adenomas in their colon and rectum.

As disease burden increases, most patients will require a colectomy to remove the colon and manage disease progression and cancer risk.

While this surgery addresses immediate cancer risk in the colon, it does not stop the development of further adenomas in the remaining rectum, pouch, or duodenum.

Post-colectomy, patients with FAP still require decades of repeat endoscopies and excisional procedures.

Approximately 50% of these patients will eventually require removal of the remaining rectum pouch in order to manage uncontrolled polyposis, a life-altering surgery that impacts quality of life.

Disease progression continues in the upper GI tract, where approximately 90% of FAP patients will develop duodenal adenomas, which can often be difficult to manage endoscopically.

Around 6% of these patients will undergo duodenectomy or Whipple surgeries, which are some of the most significant life-altering surgeries associated with high morbidity and mortality.

Despite this substantial disease burden, no approved therapies currently exist for FAP.

Insights from Recursion OS

REC-4881 was identified as a potential first-in-disease therapy for FAP using a high-content phenotypic screening approach targeting APC-deficient human cells.

In this screen, REC-4881 emerged as a potent allosteric MEK1/2 inhibitor that rescued an APC siRNA genetic knockdown-associated morphological phenotype.

Compared to other MEK inhibitors, REC-4881 demonstrated a highly selective and concentration-dependent response, suggesting best-in-class potential.

As a result, REC-4881 was in-licensed from Takeda and subsequently advanced into preclinical studies.

Discovery of REC-4881 in Recursion OS.

Compared to thousands of other molecules tested, REC-4881 rescued phenotypic defects associated with APC siRNA genetic knockdown.

REC-4881 is an orally bioavailable, non-ATP-competitive allosteric inhibitor of MEK1 (IC 50 :

2-3 nM) and MEK2 (IC 50 :

3-5 nM) being developed as a potential first-in-disease therapy for FAP.

Loss of APC disrupts β-catenin regulation, leading to uncontrolled Wnt signaling, RAS stabilization, and ERK pathway activation, which drives MYC-dependent proliferation.

REC-4881 inhibits MEK1/2, and blocks ERK phosphorylation downstream.

This reduces MYC expression levels in the cell and potentially restores Wnt pathway control.

Given ERK signaling activity in both adenoma epithelium and tumor stroma, as well as frequent MAPK-activating mutations in FAP, MEK inhibition offers a targeted strategy to suppress disease progression.

REC-4881 inhibits APC-mutation induced MAPK signaling to block cell proliferation in the context of FAP.

A potential mechanism of action of REC-4881 in cells with loss of function mutations in APC.

7 Jeon, WJ, et al.

Interaction between Wnt/β-catenin and RAS-ERK pathways and an anti-cancer strategy via degradations of β-catenin and RAS by targeting the Wnt/β-catenin pathway.

NPJ Precision Oncology, 2(5).

REC-4881’s activity was validated in tumor cell lines and spheroid models derived from APC-mutant human epithelial tumor cells.

In these systems, REC-4881 inhibited spheroid growth and disrupted cellular organization, demonstrating over 1,000-fold selectivity in APC-mutant cells.

In a disease-relevant FAP model, Apc Min/+ mice were treated with multiple oral doses of REC-4881 or celecoxib over eight weeks.

While celecoxib reduced polyp formation by approximately 30% compared to vehicle, REC-4881 treatment led to a reduction of 50% (1-3 mg/kg), and 70% (10 mg/kg).

Mice that were treated with 10 mg/kg REC-4881, the highest dose tested, exhibited an approximately 70% reduction in total polyps.

Histological analysis of gastrointestinal tissues further revealed that, unlike celecoxib, which primarily affected benign polyps, REC-4881 significantly reduced both benign polyps and high-grade adenomas.

These findings suggest that REC-4881 not only limits early polyp formation but may also inhibit progression to advanced adenomas, highlighting its potential to address both pre- and post-colectomy FAP populations.

REC-4881 reduces GI polyp count and pre-cancerous, high-grade adenomas in the APC Min/+ mouse model of FAP.

GI polyp count (left) and the percentage of high-grade adenomas (right) after oral administration of indicated dose of REC-4881, celecoxib, or vehicle control for 8 weeks.

Polyp count at the start of dosing reflects animals sacrificed at the start of study (15 weeks of age).

P < 0.001 for all REC-4881 treatment groups vs.

vehicle control.

Quantification of high-grade adenomas versus total polyps was based on blinded histological review by a pathologist.

While celecoxib reduces benign polyps, most remaining lesions are high-grade adenomas.

By contrast, REC-4881 reduces both polyps and high-grade adenomas.

REC-4881 has been evaluated in multiple clinical studies, demonstrating a well-tolerated safety profile and pharmacological activity.

Phase 1 Oncology Studies

In a prior dose-escalation study (C20001) conducted by Millennium Pharmaceuticals in 51 participants with advanced solid tumors, REC-4881 (formerly TAK-733) was administered at doses ranging from 0.2 mg to 22 mg once daily on days 1–21 of 28-day treatment cycles.

The maximum tolerated dose (MTD) was determined to be 16 mg.

The most common adverse events (AEs) were rash (67%;

57% Gr1-2, 10% Gr3), diarrhea (29%, All Gr1-2), and increased blood CPK (20%, 10% Gr1-2, 10% Gr3).

Treatment-related serious adverse events (SAEs) were infrequent.

No unexpected safety concerns emerged, and pharmacokinetic analyses showed a less-than-dose proportional increase in exposure.

REC-4881-101 (Healthy Volunteers)

We conducted a Phase 1 study to evaluate the safety and pharmacokinetics of REC-4881 in 25 healthy participants receiving single doses of 4 mg, 8 mg, and 12 mg.

REC-4881 was well tolerated, with no SAEs or dose-related safety concerns.

The most common treatment-emergent adverse events (TEAEs) were mild and self-limiting, including transient blurred vision and vitreous floaters.

No QTcF abnormalities were observed.

8 Data on file.

Phase 1b/2 in FAP (TUPELO)

We are currently enrolling patients in a Phase 1b/2 open-label, multicenter study (TUPELO) evaluating the efficacy, safety, pharmacokinetics, and pharmacodynamics of REC-4881 in FAP.

Part 1 assessed safety, tolerability, and pharmacokinetics in FAP patients receiving 4 mg once daily for 14 days.

REC-4881 was generally well-tolerated, with a safety profile consistent with other MEK inhibitors.

Pharmacodynamic data showed that the 4 mg dose was pharmacologically active in FAP, and this dose progressed to Part 2 of the study.

Part 2 is evaluating efficacy, safety, and pharmacokinetics in post-colectomy FAP patients with confirmed germline APC mutations.

Participants will receive once-daily REC-4881 for three months (the on-treatment phase, with readout at week 13), followed by a 3 month off-treatment phase (with a readout at week 25).

TUPELO study design.

Phase 1b/2 clinical study to assess the efficacy, safety, and pharmacokinetics of REC-4881 in patients with classical familial adenomatous polyposis (FAP)

As of December 2025, treatment with REC-4881 (4 mg QD) demonstrated meaningful and durable reductions in polyp burden in patients with FAP within the Phase 2 portion of TUPELO.

A rapid reduction in polyp burden was reported at week 13.

The majority of evaluable patients responded, with 75% showing reductions in polyp burden, and a median 43% reduction in total polyp burden observed among 12 efficacy-evaluable patients.

40% of patients also achieved a ≥1-point improvement in Spigelman stage from baseline, which is a clinically meaningful measure of upper GI disease severity to assess surveillance and clinical management.

Durability of effect was maintained at week 25, following the 12 week off-therapy phase.

82% (N=9) of 11 evaluable patients responded to treatment with REC-4881, with a 53% median reduction in total polyp burden observed from baseline, which is shown in the figure below.

40% of patients also maintained a ≥1-point improvement in Spigelman stage from baseline.

Durable reductions in polyp burden at week 25 of the TUPELO study.

Percent change in baseline in total polyp burden at week 25 (12 weeks on therapy / 12 weeks off therapy) for patients with FAP treated with 4mg REC-4881.

Percent (%) change from baseline calculates the change between post-resection value from screening visit to the pre-resection value at Week 25/EOT visit.

Polyp burden defined as the sum of all diameters of polyps in the GI.

1 Non-responder with 233% increase – polyp burden increased from 3mm to 10mm due to one polyp growth at Week 25.

Efficacy Evaluable Population:

Defined as all participants who have measurable disease (non-zero polyp burden) at end of baseline endoscopy, received at least 75% of study drug, and have at least one post-baseline on study endoscopic assessment.

One patient who had a week 13 endoscopy did not have a Week 25 endoscopy.

The safety profile of REC-4881 4 mg QD across the combined Phase 1b/2 cohort (19 safety evaluable patients) was consistent with prior MEK1/2 inhibitors.

Treatment-related adverse events were predominantly low grade and N=4 discontinuations occurred due to TRAEs.

The most frequent TRAEs (at greater than or equal to 10%) included dermatitis acneiform (57.9%;

52.6% Grade 1/2, 5.3% Grade 3) / rash (31.6%;

all Grade 1/2) and blood CPK increase (36.8%;

26.3% Grade 1/2, 10.5% Grade 3).

Natural History Analysis

In December 2025, we reported on a natural history analysis in collaboration with Amsterdam University Medical Centre to contextualize the single-arm efficacy TUPELO trial of REC-4881, and to better understand the natural history of FAP.

The study analyzed a subset of 55 patients from a FAP registry which met key inclusion criteria of TUPELO.

Results suggested that the natural history of FAP is to progress:

87% of untreated patients in the registry experienced annualized increase in polyp burden, with 10% being stable and 3% experiencing a modest decrease in polyp burden, shown in the figure below.

A mean increase of 60% and median increase of 28% in annualized polyp burden was observed.

9 Data on file.

Annualized percent change in polyp burden in a natural history cohort.

Each bar represents one patient.

6 patients had separate endoscopic evaluations for upper and lower GI involvement and have repeated bars.

Data includes 55 patients aged ≥55 with a history of colectomy and measurable polyp burden at baseline endoscopy.

In routine care, endoscopies for lower and upper GI are performed annually with variability.

Therefore, polyp burden percent change was annualized.

52 (97%) of the 55 patients had an increase or stable polyp burden.

No drugs have been approved for FAP patients, though some generic drugs are used in selected patients to reduce polyp burden.

The following programs represent the most clinically advanced efforts specifically evaluated in FAP populations:

• Flynpovi (Panbela Therapeutics) — A fixed-dose combination of sulindac and eflornithine.

The combination of the individual drugs was previously evaluated vs.

the individual drugs alone in a randomized Phase 3 trial in FAP.

Post hoc analyses suggested a potential effect on delaying lower gastrointestinal surgery;

Panbela had indicated plans for a new Phase 3 study in FAP patients, including those with an intact colon, although the company has provided no updates on development plans since 2023.

• eRapa (Biodexa Pharmaceuticals) — A formulation of rapamycin currently being evaluated in a Phase 3 study in FAP patients both prior to and following colectomy, with primary completion in 2030.

◦ Phase 2 data among adult patients with and without intact colon in cohort 2 (Phase 3 dose) showed a 29% median reduction in total polyp burden at 12 months.

• Eicosapentaenoic Acid (SLA Pharma) — A derivative of an omega-3 fatty acid which was under evaluation in a Phase 3 study for polyp suppression in FAP, completed over 6 years in 2024 and is pending data updates.

It has previously shared data from a Phase 2/3 study:

◦ A 17% reduction in polyp size (diameters) vs baseline at 6 months, which translates to 29.8% mean reduction vs.

◦ A decrease 34% from baseline in global rectal polyp burden was reported vs.

a 9% increase with placebo.

Depending on jurisdiction, this product may be regulated differently from traditional prescription pharmaceuticals.

The following programs are in early clinical development or include FAP as a subset of a broader development strategy:

• FOG-001 (zolucatetide, Parabilis Medicines) — A peptide-based investigational therapy with early clinical evidence reported in FAP.

Additional clinical data are expected in 2026.

• TPST-1495 (Tempest Therapeutics) — A dual EP2/EP4 antagonist with a Phase 2 study in FAP(NCI run study) anticipated to initiate in 2026.

• ZKN-013 (Eloxx Pharmaceuticals / Almirall) — A small-molecule read through agent currently in a Phase 1 clinical trial that includes a cohort of patients with FAP.

10 Data on file.

REC-617 for Advanced Solid Tumors – Phase 1/2

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ELUCIDATE, a Phase 1/2 open-label, multicenter, safety, PK, PD and preliminary efficacy study is currently underway.

Interim Phase 1 safety, PK, PD, and efficacy data were shared in the fourth quarter of 2024.

We expect to initiate combination studies in the first half of 2025.

Interim monotherapy Phase 1 safety, PK, PD, and efficacy data were shared in the fourth quarter of 2024, with expanded data from a larger cohort of patients shared in the fourth quarter of 2025.

Phase 1 monotherapy dose escalation is ongoing in 2026, to evaluate alternative dosing schedules.

Phase 1 dose escalation combination cohorts were initiated in 2L+ PROC in 2025, with initial combination regimens including bevacizumab plus paclitaxel or pegylated liposomal doxorubicin (PLD).

A Phase 2 dose expansion monotherapy cohort in PROC was also initiated in 2025.

We expect to provide early safety and PK combination data in 2027.

Disease Overview

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Aberrant CDK7 overexpression is common in many cancer indications and associated with poor prognosis.

CDK7 presents an opportunity to improve treatment outcomes over CDK4/6 inhibitors due to CDK7’s dual role in cell cycle and transcription.

Potential specific indications include non-small cell lung cancer (NSCLC), colorectal cancer, breast cancer, pancreatic cancer, ovarian cancer, head and neck cancer for which we estimate an addressable population of approximately 185,000 drug-treatable patients per year in the US and EU5.

CDK7 presents an opportunity to improve treatment outcomes over CDK4/6 inhibitors due to CDK7’s dual role in cell cycle progression and transcription.

Potential specific indications include ovarian cancer, HR+ breast cancer, triple negative breast cancer, pancreatic cancer, ovarian cancer, head and neck cancer, and NSCLC for which we estimate an addressable population of approximately 150,000 drug-treatable patients per year in the US and EU5.

Insight from Recursion OS

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(Right) REC-617 administration results in 8-10 hours of therapeutic coverage at IC 80 .

PK studies conducted in CD1 mice, single-dose administration.

>10 hr IC 80 results in significant body weight loss.

PK studies conducted in CD1 mice, single-dose administration PO.

In the third quarter of 2023, we initiated a Phase 1/2 open-label, multicenter study (ELUCIDATE) in patients with advanced solid tumors, with the design shown in the figure below.

Currently, monotherapy dose escalation (QD and BID) is ongoing, with combination study initiation expected in the first half of 2025.

ELUDICATE study design.

ELUCIDATE study design.

Phase 1/2 trial design to assess the safety, PK, exploratory PD, and efficacy of REC-617 in patients with advanced solid tumors.

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Plenary Session 1

In December 2024, we presented results from the initial 18 response evaluable patients at an AACR Special Conference in Cancer Research.

REC-617 was well-tolerated with predominantly Grade 1-2 adverse events, no treatment-related discontinuations, and fewer GI side-effects than reported for other CDK7 inhibitors.

Dose escalation (QD and BID) is ongoing, and the maximum tolerated dose (MTD) has not been reached.

PK was dose linear and exceeded the CDK7 IC 80 with rapid absorption (Tmax 0.5–2h) and short t½ (5–6h).

Robust target engagement was also observed with rapid increases in POLR2A (3-4x), which normalized within 24 hours.

These data are shown in the figure below.

REC-617 clinical plasma pharmacokinetics and pharmacodynamics.

(Left) REC-617 plasma concentration, in a dose-linear fashion, well above CDK7 IC 80 at peak and well below CDK2 IC 80 , indicating a broad therapeutic window for the study drug.

(Right) POL2RA expression data (PD), which is associated with tumor regression, shows a rapid pharmacodynamic effect and short half-life.

Encouraging antitumor activity included a confirmed partial response (PR), in a heavily pre-treated metastatic ovarian cancer patient, with a durable response that was maintained for more than 6 months of treatment.

LDH levels were also normalized, and reductions were observed in CA125 (-44%) and TK1 (-68%).

Four additional patients achieved the best response of stable disease (SD) lasting up to six months.

We are aware of five active CDK7 inhibitor programs in clinical development:

• Samuraciclib (Carrick Therapeutics):

In Phase 2 as a monotherapy and in a range of combination studies

• SY-5609 (Syros Pharmaceuticals):

Completed Phase 1 monotherapy and in Phase 1/1b in combination with atezolizumab

• Q-901 (Qurient):

In Phase 1/2 in monotherapy and combination with PD-1 inhibitors in solid tumors

• TY-2699a (TYK Medicines):

In Phase 1 trial in China only

• EOC-237 (EOC Pharma):

In Phase 1 trial in China only

In December 2024, we presented results from the initial 18 response evaluable patients from Phase 1 monotherapy dose escalation at an AACR Special Conference in Cancer Research.

In November 2025, updated results from a monotherapy cohort of 29 heavily pre-treated patients who received 6 dose levels of REC-617 (QD and BID) were reported.

REC-617 was well-tolerated with predominantly Grade 1-2 adverse events, and fewer GI side-effects than reported for other CDK7 inhibitors.

The most common DLTs were nausea and thrombocytopenia, and 6.9% (N=2) of patients discontinued due to a TRAE.

The MTD was established at 10 mg once daily.

PK data support dose-proportional exposure (see figure below), rapid absorption, and a short half-life (~5h).

REC-617 clinical plasma pharmacokinetics.

REC-617 demonstrates dose-proportional exposures exceeding CDK7 IC50.

Exposures remain below CDK2 IC80, supporting selective target inhibition.

Encouraging antitumor activity included a confirmed partial response (PR), in a heavily pre-treated metastatic ovarian cancer patient.

The patient had a maintained durable response and was treated with REC-617 for approximately 7 months.

Patient LDH levels were also normalized, and reductions were observed in CA125 (-44%) and TK1 (-68%).

Five additional patients achieved the best response of stable disease (SD) lasting up to six months.

Several investigational CDK7 inhibitor programs have entered clinical development;

however, the competitive landscape remains relatively limited, with only a small number of programs currently advancing in active clinical development.

These programs vary by mechanism, combination strategy, geographic focus, and development priority.

Programs with active clinical development and strategic focus

• Samuraciclib (Carrick Therapeutics) — An oral CDK7 inhibitor currently in Phase 2 clinical development, primarily in combination with selective estrogen receptor degraders (SERDs) for patients with HR-positive, HER2-negative breast cancer following progression on CDK4/6 inhibitors.

◦ Recent data update from Ph2 randomized study evaluating samuraciclib + fulvestrant vs.

fulvestrant alone in, fulvestrant naive, post CDK4/6+AI patient population was directionally positive but with limited quantitative power

▪ Positive direction holds true across ORR, CBR, PFS and in sub-cohorts (TP53wt)

28% with combo (n=32) vs.

14% (n=14) with fulvestrant alone

7.8mo to 8.5mo (n=39) vs.

• In TP53mut not detected:

mPFS of 9.6-14.5mo (n=30) vs 6.8mo (n=11)

▪ The drug continues to show GI toxicities in >80% patients at RP2D (360mg)

• Q-901 (Qurient) — An intravenous CDK7 inhibitor in Phase 1/2 clinical development as monotherapy and in combination with PD-1 inhibitors across solid tumors.

No efficacy data has been shared so far.

Qurient is also developing a HER2-targeted antibody–drug conjugate (QP-101) that incorporates a CDK7 inhibitor payload in combination with a topoisomerase I inhibitor, currently in preclinical development.

13 Data on file.

Other notable programs with limited or geographically-constrained clinical presence

• TY-2699a (TYK Medicines) — A CDK7 inhibitor currently in Phase 1 clinical development in China.

• EOC-237 (EOC Pharma) — A CDK7 inhibitor currently in Phase 1 clinical development in China.

REC-1245 for Solid Tumors and Lymphoma – Phase 1/2

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There are currently no RBM39 degraders approved by the FDA.

Following IND clearance in September 2024, we initiated a Phase 1/2 open-label, multicenter study (DAHLIA) to evaluate the safety, tolerability, PK, PD, RP2D, and preliminary efficacy of REC-1245.

With the first patient dosed in December 2024, we expect to share an update on the program in the first half of 2026.

16 Papadopoulos, et al.

EORTC-NCI-AACR (ENA) Symposium

17 Hallett, et al.

Overcoming traditional design limitations with AI-based discovery.

AACR Special Conference in Cancer Research:

Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry;

Plenary Session 1

We initiated a Phase 1/2 open-label, multicenter study (DAHLIA) to evaluate the safety, tolerability, PK, PD, RP2D, and preliminary efficacy of REC-1245.

We expect to share early safety and PK data from the Phase 1 monotherapy dose-escalation portion of the study in the first half of 2026.

Disease Overview

Alternative splicing and RNA-binding proteins (RBPs) have recently emerged as attractive therapeutic targets for cancer due to their critical roles in the regulation of post-transcriptional modifications, impacts on DNA damage repair pathways, and modulation of cell cycle functions.

Recent studies have revealed that RBM39 is an unexpected target of aryl sulfonamides, which can function as molecular glue degraders by forming a ternary complex with RBM39 and the E3 ubiquitin ligase receptor DDB1 and CUL4 associated factor 15 (DCAF15).

Additionally, clinical trials have shown that aryl sulfonamides were well tolerated with modest anti-tumor activity seen across a variety of cancers.

These findings suggest that RBM39 degraders may show promise as targeted cancer therapies, but the lack of predictive biomarkers and an inadequate understanding of RBM39 biology has limited their therapeutic potential.

With over 100,000 addressable patients, with biomarker-enriched solid tumors and other select histologies in the US and EU5 each year, REC-1245 has the potential to be used as a single agent or in combination with chemotherapy and/or immunotherapy.

Alternative splicing and RNA-binding proteins (RBPs) have emerged as attractive therapeutic targets for cancer due to their critical roles in the regulation of post-transcriptional modifications, impacts on DNA damage repair pathways, and modulation of cell cycle functions.

Of these, RNA-binding motif protein 39 (RBM39) is a critical splicing factor that many high-risk cancers rely on to maintain transcriptional integrity and drive tumor progression.

As a target, RBM39 is vulnerable to a 'molecular glue' approach, where its selective degradation triggers a cascade of lethal splicing errors across key oncogenic pathways, including those involving DNA damage repair.

With over 100,000 addressable patients, with biomarker-enriched solid tumors and other select histologies where RBM39 could be targeted in the US and EU5 each year, REC-1245 has the potential to be used as a single agent or in combination with chemotherapy and/or immunotherapy.

Insight from Recursion OS

Reports suggest that genetic or pharmacologic depletion of CDK12 can reduce the expression of several genes involved in the homologous recombination repair pathway such as BRCA1 and BRCA2, inducing a BRCA-like phenotype and DDR response.

Thus, CDK12 has received considerable interest as a therapeutic target and tumor biomarker for HR-proficient cancers.

Therefore, CDK12 has received considerable interest as a therapeutic target and tumor biomarker for HR-proficient cancers;

however, success has been limited by toxicity associated with CDK12 inhibitors also inhibiting the structurally related CDK13.

Despite reports of functional redundancy, we observed that the genetic knockout of CDK12 could be clearly distinguished phenotypically from that of CDK13.

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REC-1245 single-agent activity and target engagement.

(Left) REC-1245 administered BID PO at doses noted for 15 days.

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N=3 mice per group.

Emerging preclinical data has shown that REC-1245 reduces viability in tumors characterized by replication stress and DNA repair vulnerabilities (DDR defects) across multiple solid tumor types, including MSI-H/dMMR, HRR altered cancers, and other tumors, as shown below, which could provide a potential signature for REC-1245 sensitivity.

The data also suggests greater sensitivity to REC-1245 for tumors with high replicative stress signatures and DNA repair vulnerabilities, as shown below.

In vitro cell viability following REC-1245 treatment.

Cell lines were assigned to broad pathway dysregulation contexts based on 1 or more documented alteration from CCLE/GSDC databases.

14 Data on file.

15 Data on file.

Reduction in tumor volume across different tumors with high replication stress and DNA repair vulnerabilities.

N=4 mice per group.

In December 2024, we initiated a Phase 1/2 open-label, multicenter study to characterize the safety, tolerability, PK, PD, and preliminary anti-tumor activity of REC-1245 in participants with unresectable locally advanced or metastatic cancer.

As of December 31, 2024, the trial is currently active and enrolling at 5 US sites.

We expect to share an update on the Phase 1 dose escalation portion in the first half of 2026.

As of December 31, 2025, the trial is currently active and enrolling at sites in the US and Canada.

We expect to share early safety and PK data from the Phase 1 monotherapy dose-escalation portion of the study in the first half of 2026.

DAHLIA study design.

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16 Data on file.

We are aware of only one other RBM39 development program, which is known to be active:

• ST-01156 (SEED Therapeutics):

In IND-enabling studies

The clinical development landscape for RBM39 degraders remains limited.

While the mechanism of RBM39 degradation has been explored historically through legacy aryl-sulfonamide compounds, only a small number of programs are currently believed to be under active clinical development as purpose-built RBM39 degraders.

Active RBM39-focused development programs

• ST-01156 (SEED Therapeutics) — An investigational RBM39 degrader that initiated a Phase 1a open-label clinical trial in patients with advanced solid tumors, with first patient dosed in January 2026.

• E7820 (Eisai) — A legacy aryl-sulfonamide compound now understood to induce RBM39 degradation via DCAF15.

Eisai is collaborating with the National Cancer Center (NCC) Japan, which is conducting a Phase 1 investigator-initiated trial (CIRCUS) evaluating E7820 in Japanese patients with unresectable tumors.

Advancement to Phase 2 is expected to be considered following determination of tolerability and a recommended Phase 2 dose.

REC-3565 for B-Cell Malignancies – Phase 1

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There are currently no MALT1 inhibitors approved by the FDA.

Following clearance of a CTA by the MHRA in December 2024, we plan to initiate EXCELERIZE, a Phase 1 open-label, multicenter, dose escalation study to evaluate the safety, tolerability, PK, PD, and preliminary anti-tumor activity of REC-3565.

We expect the first patient to be dosed in the first half of 2025.

Following clearance of a CTA by the MHRA in December 2024, we initiated EXCELERIZE, a Phase 1 open-label, multicenter, dose escalation study to evaluate the safety, tolerability, PK, PD, and preliminary anti-tumor activity of REC-3565 in 2025.

The first patient was dosed in April 2025, and we expect to share early safety and PK monotherapy data in the first half of 2027.

Disease Overview

B-cell malignancies encompass a range of hematological cancers, including lymphomas such as diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), mantle cell lymphoma (MCL), and leukemias such as chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL).

These diseases are characterized by the dysregulated growth or function of B-cells and are often driven by chronic B-cell receptor (BCR) signaling, which leads to unchecked NF-κB activation.

MALT1 functions downstream of the BCR and the widely targeted Bruton’s tyrosine kinase (BTK), mediating pro-tumorigenic signals in malignant B-cells.

Current therapies (e.g., BTK inhibitors) have transformed the treatment landscape, yet resistance remains a significant challenge.

Current therapies (e.g.

BTK inhibitors) have transformed the treatment landscape, yet resistance remains a significant challenge.

By inhibiting MALT1, REC-3565 may help overcome resistance and improve therapeutic outcomes, either as a monotherapy or in combination with BTK and/or BCL2 inhibitors.

Notably, the total addressable population for MALT1 inhibitors spans multiple hematologic indications, with approximately 41,000 relapsed and/or refractory (R/R) patients with CLL and B-cell lymphomas in the U.S.

and EU5 annually.

Insight from Recursion OS

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Part A will assess monotherapy dosing to identify a recommended dose for combination in Part B, which will evaluate combination regimens to inform future studies in B-cell cancers.

Following CTA clearance by the MHRA in December 2024, we anticipate dosing the first patient in the first quarter of 2025.

The first patient was dosed in the second quarter of 2025, and we expect to share early safety and PK monotherapy data in the first half of 2027.

EXCELERIZE study design.

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18 Data on file.

We are aware of five active MALT1 inhibitor programs currently in clinical development:

• ABBV-525 (AbbVie/Lupin):

In Phase 1/2a trial in R/R B-cell malignancies

• JNJ-6786633 (Johnson & Johnson):

Completed Phase 1/1b for NHL/CLL

• MPT-0118 (Monopteros):

In Phase 1/1b in solid tumors with a planned Phase 1/2a in combination PD-L1

• SGR-1505 (Schrödinger):

In Phase 1 in combination with BTK and BCL2 inhibitors for R/R B-cell lymphomas

• CTX-177/ONO-7018 (Chordia/ONO):

In Phase 1 trial for patients with R/R NHL/CLL

REC-4539 for Small-Cell Lung Cancer – Phase 1/2

REC-4539 is an orally bioavailable, highly potent and selective, CNS penetrant, and potential best-in-class LSD1 inhibitor under development for the treatment of small-cell lung cancer (SCLC).

Early MALT1 inhibitors have shown UGT1A1 liability that has led to instances of hyperbilirubinemia in the clinic and limited combinability, while also potentially leaving efficacy on the table.

The following competitors have or are currently generating data in the clinic with a strategic focus on B-cell lymphomas:

• JNJ-6786633 (Johnson & Johnson) - An oral MALT1 inhibitor, that showed significant hyperbilirubinemia in the clinic.

Ph2 trials in combination with BTK inhibitors have since started and been marked complete, though no further data has been disclosed.

• SGR-1505 (Schrödinger) - An oral MALT1 inhibitor with Phase 1 monotherapy results reported for the ongoing trial in R/R B-cell lymphomas.

Received US orphan drug designation for Waldenström's macroglobulinemia (WM) and mantle cell lymphomas (MCL), along with a fast track designation for treatment of WM patients in post BTK 3L+ setting.

• ABBV-525 (AbbVie/Lupin) - An oral MALT1 inhibitor with a Phase 1/2a trial ongoing in R/R B-cell malignancies.

Primary completion of the trial is expected in 2029.

• AUR-112 (Aurigene) - An oral MALT1 protease inhibitor, with Phase I trial (AUR112-101) ongoing for relapsed advanced lymphoma.

Initial results were reported at December 2025 press release, which showed limited Gr3 hyperbilirubinemiand 64% response rate (6 PR, 1CR) across B-cell lymphomas.

Other assets that have been discontinued or have a different strategic focus includes:

• CTX-177/ONO-7018 (Chordia/ONO) - An oral MALT1 inhibitor that was in Phase 1 trial for patients with R/R NHL/CLL which has recently been discontinued with the company looking to out license the asset.

• RB-201 (Rarefied Biosciences) - An oral MALT1 inhibitor currently in a healthy volunteer's study, with a strategic focus on autoimmune diseases.

REC-4539 for Solid Tumors and Hematology Oncology – Phase 1

REC-4539 is an orally bioavailable, highly potent and selective, CNS penetrant, and potential best-in-class inhibitor under development for the treatment of solid tumors and hematological malignancies.

LSD1 is an epigenetic regulator that removes methyl groups from histones, thereby controlling the expression of tumor suppressors and oncogenes.

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There are currently no LSD1 inhibitors approved by the FDA.

In January 2025, the FDA cleared an IND application for ENLYGHT, a Phase 1/2 open-label, multicenter study evaluating REC-4539 patients with advanced SCLC.

We expect the first patient to be dosed in the first half of 2025.

In January 2025, the FDA cleared an IND application for ENLYGHT, a Phase 1 open-label multicenter study evaluating REC-4359.

In May 2025, the program was placed on strategic pause, to allow review of emerging clinical data and to ensure the program has a competitive Target Product Profile.

Following completion of this review, we now expect to initiate a Phase 1 trial in the first half of 2026, with the dose escalation study evaluating REC-4539 in patients with SCLC or other select solid tumors.

We expect to share early safety and PK data in the second half of 2027.

Disease Overview

Small-cell lung cancer (SCLC) is a poorly differentiated neuroendocrine tumor, representing roughly 15% of all lung cancer diagnoses.

It is commonly categorized as limited stage (LS-SCLC) or extensive stage (ES-SCLC), with the majority of patients presenting with metastatic (extensive) or unresectable disease.

SCLC is strongly linked to smoking, tends to grow rapidly, and frequently spreads early.

Notably, over 50% of patients eventually develop brain metastases.

LSD1 is abnormally overexpressed in a broad spectrum of solid tumors including lung, breast, prostate, esophageal, and bladder cancers, as well as acute myeloid leukemia (AML), with evidence suggesting that LSD1 is a promising therapeutic target.

One indication of focus is SCLC, a poorly differentiated neuroendocrine tumor, representing roughly 15% of all lung cancer diagnoses.

The majority of SCLC patients present with metastatic (extensive) or unresectable disease and, notably, over 50% of patients eventually develop brain metastases.

Despite some improvements in frontline therapy such as chemotherapy plus immunotherapy, treatment options after progression remain limited.

Median survival in ES-SCLC is poor, with a 5-year overall survival rate of approximately 3%.

Across the US and EU5, more than 45,000 patients have a treatable Stage III/IV SCLC each year.

Across the US and EU5, approximately 45,000 patients have a treatable Stage III/IV SCLC each year.

Within SCLC, LSD1 plays a key epigenetic role by demethylating histones that regulate critical tumor suppressor genes.

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Many LSD1 inhibitors have failed to achieve these parameters, particularly brain penetration and controlled on-target effects, highlighting the unmet need that REC-4539 aims to address.

A second indication of focus is acute myeloid leukemia (AML), which is the most prevalent adult leukemia.

The disease accounts for approximately 80% of cases and is characterized by the aggressive expansion of immature "blast cells." While advancements in management have improved outcomes for younger patients, the prognosis for the elderly population remains poor, with cure rates as low as 15%.

At the molecular level, LSD1 is abnormally overexpressed, acting as an epigenetic master regulator that complexes with GFI1 to arrest myeloid differentiation and drive the self-renewal of leukemic stem cells.

While the therapeutic potential of LSD1 inhibition is well-documented across various genetic profiles, the broader clinical field has been limited by significant safety hurdles.

REC-4539 addresses this critical unmet need with an optimized profile designed to maximize anti-leukemic efficacy while mitigating the systemic risks that have hindered previous candidates, offering a highly differentiated solution for a patient population with few remaining options.

Insight from Recursion OS

Developing a selective LSD1 inhibitor for SCLC requires a reversible mechanism, a short half-life to minimize on-target toxicity (e.g., thrombocytopenia), and the ability to penetrate the blood-brain barrier to address frequent metastases.

Developing a selective LSD1 inhibitor for solid tumor indications requires a reversible mechanism, a short half-life to minimize on-target toxicity (e.g.

thrombocytopenia), and the ability to penetrate the blood-brain barrier to address frequent metastases seen in indications such as SCLC.

Many existing LSD1 agents fail to meet these criteria, resulting in dose-limiting toxicity and poor CNS exposure.

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Active learning identified counterintuitive yet informative compounds, enabling a rapid design breakthrough.

As a result, we created REC-4539 – a potent, selective, reversible, brain-penetrant, and potential best-in-class LSD1 inhibitor with a short predicted half-life.

As a result, we created REC-4539 – a potent, selective, reversible, brain-penetrant, and potential best-in-class LSD1 inhibitor with a short predicted half-life and potential improved therapeutic index through better management of on-target toxicities such as reduced impact on platelets.

We believe these key attributes provide competitive differentiation for REC-4539 versus prior LSD1-targeted molecules.

REC-4539 demonstrated potent anti-tumor activity across multiple preclinical models, including the NCI-H1417 human SCLC xenograft.

In this model, dose-dependent tumor regression correlated with a corresponding decrease in the neuroendocrine tumor biomarker progastrin-releasing peptide (proGRP).

In this model, dose-dependent tumor growth inhibition correlated with a corresponding decrease in the neuroendocrine tumor biomarker progastrin-releasing peptide (proGRP).

Additionally, REC-4539 treatment was well-tolerated, with minimal impact on platelet counts.

REC-4539 preclinical assessment in SCLC xenograft model.

(Left) REC-4539 induces dose dependent tumor regression in the NCI-H1417 SCLC cell line derived xenograft mouse model.

BALB/c mice, REC-4539 dosed BID, 28 day study.

(Right) REC-4539 induces dose dependent tumor reductions in plasma proGRP.

BALB/c mice, REC-4539 dosed BID, 28 day study.

ENLYGHT is a Phase 1/2, open-label, multicenter study designed to evaluate the safety, tolerability, and preliminary efficacy of REC-4539 in patients with SCLC.

The FDA cleared an IND application in January 2025, and we expect the first patient to be dosed in the first half of 2025.

Phase 1 will include both monotherapy dose escalation and REC-4539 combination with durvalumab, determining safety, tolerability, and a recommended dose.

Phase 2 will focus on dose optimization for both monotherapy and combination arms, followed by expansion to further assess efficacy.

ENLYGHT study design.

Phase 1/2 trial design to assess the safety, tolerability, and recommended dose of REC-4539 with dose escalation as monotherapy and in combination with durvalumab.

BALB/c mice, REC-4539 dosed BID, 28 day study (Left) REC-4539 induces dose-dependent tumor growth inhibition in the NCI-H1417 SCLC cell line derived xenograft mouse model.

(Right) REC-4539 induces dose dependent reductions in plasma proGRP.

19 Payne, et al.

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20 Data on file.

We are aware of three LSD1 inhibitor programs in various stages of clinical development:

• Bomedemstat (Merck):

In Phase 3 trial in essential thrombocythemia (ET), a Phase 2 study in myelofibrosis (MF) and polycythemia vera (PV), and a Phase 1 study in AML (in combination with venetoclax);

previously terminated Phase 1/2 SCLC trial in combination with PD-L1 maintenance

• Iadademstat (Oryzon):

In Phase 2 for relapsed/refractory (R/R) SCLC and extrapulmonary high-grade NETs (in combination with paclitaxel), as well as a Phase 1b/2 trial in first-line extensive-stage SCLC (ES-SCLC) in combination with a checkpoint inhibitor;

further trials are ongoing in AML

• JBI-802 (Jubilant Life Sciences):

In Phase 1/2 basket study, with expansion cohorts planned in SCLC, neuroendocrine prostate cancer (NEPC), and other NETs

REC-994 for Cerebral Cavernous Malformation – Phase 2

REC-994 is an orally bioavailable superoxide scavenger under development as a potential first-in-disease therapy for symptomatic cerebral cavernous malformation (CCM).

CCMs are rare neurovascular lesions characterized by abnormal capillary-venous structures, recurrent bleeding, and stroke-like symptoms.

REC-994 emerged from an early version of Recursion’s phenotypic platform, showing robust rescue in CCM2-deficient endothelial cells.

In animal models, it reduced lesion burden by approximately 50% and improved vascular permeability.

Phase 1 studies established its safety and tolerability, supporting the ongoing Phase 2 SYCAMORE trial, which to date has shown encouraging safety and preliminary efficacy signals.

With no approved therapies for symptomatic CCM, we plan to consult with the FDA and other regulatory authorities on a path forward for this potential first-in-disease program and plan to share additional updates in 2025.

REC-994 has received Orphan Drug Designation (ODD) in the United States and Europe.

Disease Overview

CCM is a neurovascular disorder affecting roughly 360,000 symptomatic individuals in the US and EU5, although actual prevalence may exceed one million due to underdiagnosis.

CCM arises from mutations in any of three genes (CCM1, CCM2, or CCM3) that regulate endothelial function.

These mutations result in enlarged capillary cavities with no intervening brain parenchyma, placing patients at high risk for seizures, progressive neurological deficits, and life-threatening hemorrhagic strokes.

Up to 20% of cases are familial and inherited in an autosomal dominant pattern;

sporadic disease makes up the remainder.

Surgical resection and stereotactic radiosurgery are the primary interventions, yet many lesions – especially in the brainstem – are not amenable to resection.

For approximately 25% of symptomatic cavernomas that occur in the brainstem, such invasive approaches carry substantial risks.

Currently, there is no pharmacologic agent that reduces CCM lesion growth or bleeding propensity, highlighting a critical unmet need.

Insight from Recursion OS

Using a CCM2 loss-of-function screen in human endothelial cells, our early phenotypic platform rapidly identified drug candidates capable of reversing disease-relevant phenotypes.

REC-994 emerged from this unbiased approach as a potent molecule that modulated CCM pathology in vitro.

These discoveries laid the groundwork for preclinical validation and subsequent clinical development, exemplifying how our platform can accelerate therapeutic innovation.

Rescue of structural phenotypes associated with loss of CCM2.

Immunofluorescence images of endothelial cells modified with siCTRL, siCCM2, or siCCM2 and treated with REC-994.

Cells stained for DNA (blue), actin (green) and VE-cadherin (red).

REC-994 demonstrated image-based phenotypic rescue, as analyzed by a machine learning classifier trained on images.

23 Gibson, et al.

Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation.

131(3), 289-99.

REC-994 is a therapeutic designed to alleviate neurological symptoms associated with CCM and potentially reduce the accumulation of new lesions with pharmacokinetics supporting once-daily dosing in humans.

The putative mechanism of action of REC-994 is through reduction of reactive oxygen species and decreased oxidative stress that leads to stabilization of endothelial barrier function.

In addition, REC-994 exhibits anti-inflammatory properties which could be beneficial in reducing disease-associated pathology.

REC-994 mechanism of action and proposed potential therapeutic impact.

In CCM mouse models (including Ccm1 - and Ccm2 -deficient strains), chronic REC-994 administration significantly reduced lesion number and size while improving vascular permeability parameters.

These data supported further clinical evaluation of REC-994 investigation.

REC-994 reduces lesion severity and vascular permeability defects in CCM loss of function mouse models.

(Left) Mice treated with REC-994 demonstrated a statistically significant decrease in the number of small-size lesions, with a trend towards a decrease in the number of mid-size lesions.

(Right) REC-994 rescues the dermal permeability defects in Ccm2 endothelial specific knockout mice.

Single- and multiple-ascending dose (SAD/MAD) studies in healthy volunteers established the safety, tolerability, and pharmacokinetics of REC-994.

The compound was well tolerated with no treatment-related discontinuations or serious adverse events, supporting once-daily dosing for chronic use.

24 Alfa R, et al.

Clinical pharmacology and tolerability of REC-994, a redox-cycling nitroxide compound, in randomized phase 1 dose-finding studies.

Pharmacology Research Perspectives.

25 Gibson, et al.

Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation.

131(3), 289-99.

26 Data on file.

Phase 2 (SYCAMORE)

Initiated in March 2022, the SYCAMORE study is a two-part Phase 2 trial in patients with symptomatic CCM.

Part 1 was a 12-month, randomized, double-blind, placebo-controlled comparison of 200 mg or 400 mg REC-994 vs.

placebo daily and as of December 31, 2024, was completed.

Part 2 is an optional long-term extension (LTE) for eligible participants and is currently ongoing.

Approximately 80% of participants who completed 12 months of treatment opted to continue into the long-term extension portion of the study.

SYCAMORE Phase 2 study schema.

Phase 2 trial design to assess the efficacy and safety of REC-994 in patients with symptomatic CCM.

There was no patient enrichment by symptom, nor stratification.

13 US sites were enrolled in 18 months.

Secondary and exploratory endpoints were not statistically powered.

Topline 12-month data from Part 1, shared in September 2024 and at the ISC annual meeting in February 2025, showed that REC-994 met its primary endpoints of safety and tolerability, in-line with Phase 1 results and with no new safety signals observed.

Adverse events were similar between treatment and placebo groups.

Common adverse events that occurred in ≥10% of patients included:

dizziness, headache, back pain, constipation, COVID-19.

There were no SAEs attributed to REC-994 or treatment-related adverse events leading to discontinuation.

Data is highlighted in the table below.

Summary of Treatment Emergent Adverse Events from 12-month data in Part 1 of Phase 2 Study.

In the REC-994 400 mg arm these consisted of dizziness, rash, anemia, nausea and peripheral edema.

In the placebo arm these consisted of dizziness and erythema multiforme.

Across both arms, TEAEs related to study drug were Grade 1 or 2.

TEAE=treatment-emergent adverse event.

27 SYCAMORE data on file.

Secondary and exploratory endpoints were centered around MRI assessments.

These evaluations were performed by a single, blinded, central neuroradiologist according to a study specified protocol.

Up to 10 of the most relevant CCM lesions were captured and evaluated longitudinally.

Key aspects measured were lesions size, location, and acuteness of hemorrhage, if present.

An exploratory efficacy endpoint assessed lesion volume size and the changes from baseline to month 12.

Patients receiving REC-994 400 mg showed an absolute mean decrease in total lesion volume of −457 mm 3 vs.

61 mm 3 increase and 53 mm 3 increase in the 200 mg and placebo arms, respectively.

Notably, 50% of patients on 400 mg achieved a reduction in total lesion volume versus 28% observed in placebo.

Patients treated with 200 mg REC-994 had similar changes in lesion volume compared to placebo.

Change in total lesion volume from baseline to 12 months across all patients.

Analysis of change from baseline between treatment and placebo in lesion volume (LV) at month 12 for REC-994 200 mg (p=0.912) and REC-994 400 mg (p-0.089) assessed by mixed model for repeated measures (MMRM) analysis.

Further exploratory analyses suggested functional improvement in patients who received REC-994 400 mg as evaluated by the Modified Rankin Scale (mRS) score from baseline to month 12.

The mRS is widely recognized and approved by the FDA as a clinically meaningful endpoint for assessing functional outcomes in acute stroke trials.

A single point change on the mRS is clinically relevant, with the agency previously utilizing the scale as an endpoint in Phase 3 studies.

At baseline, patients who received 400 mg REC-994 had a greater proportion of mRS scores ≥ 3, including an mRS score of 4-5, indicating that at the start of study these patients had worse clinical function compared to the placebo arm.

Following 12 months of treatment, patients who received 400 mg REC-994 demonstrated trends toward improvement and/or stabilization of symptoms compared with the placebo arm, which observed trends towards functional decline.

Summary of modified Rankin Scale Score at 12 Months for all lesions.

All patients at baseline were required to have mRS >1.

These observations are exploratory in nature and while not powered for statistical significance, we observed patterns that merit further investigation, and also observed a few patients transitioning down to mRS scores of 0.

A single point change on the mRS is clinically relevant.

28 Burkhardt, et al.

The SYCAMORE Study Results:

First Randomized, Placebo-Controlled Phase 2 Trial in Symptomatic Cerebral Cavernous Malformation (CCM) Evaluating REC-994 [late-breaking abstract].

International Stroke Conference (ISC);

29 Burkhardt, et al.

The SYCAMORE Study Results:

First Randomized, Placebo-Controlled Phase 2 Trial in Symptomatic Cerebral Cavernous Malformation (CCM) Evaluating REC-994 [late-breaking abstract].

International Stroke Conference (ISC);

30 Broderick, et al.

Evolution of the Modified Rankin Scale and Its Use in Future Stroke Trials.

48(7):2007-2012.

Given the high unmet need in patients with brainstem lesions, where lesion volume can influence symptomatology, we evaluated lesion volume changes and mRS scores in this specific patient cohort.

Patients on 400mg REC-994 had a −256mm 3 reduction in absolute mean change in lesion volume.

In contrast, placebo patients had a 23mm 3 decrease in absolute mean change from baseline to month 12.

Notably, 50% of patients on 400 mg also showed a reduction in total lesion volume versus 27% in the placebo arm.

When evaluating the mRS score for this subgroup, a similar trend in improvement or stabilization in the REC-994 400mg arm was observed while patients in the placebo arm appeared to trend worse.

Summary of Total Lesion Volume at 12 months for Brainstem Only.

Analysis of change from baseline between treatment and placebo for lesion volume (LV) at month 12 for REC-994 200 mg (p=0.987) and REC-994 400 mg (p-0.449) assessed by mixed model for repeated measures (MMRM) analysis.

Additional secondary and exploratory analyses are summarized below:

• Time-dependent reductions in hemosiderin ring size observed in the 400 mg arm as compared to 200 mg and placebo

• Seizure frequency appeared to be reduced in the 400 mg arm as compared to 200 mg and placebo arms;

however, there was imbalance with respect to seizure history and frequency across the arms

• Incidence of new symptomatic hemorrhage events were comparable across arms and in line with natural history studies

• Other PROs including PROMIS29, CCM-HI, NIHSS, SMSS, CGI, and PGI did not demonstrate differences between the treatment arms of the study nor placebo

All efficacy analyses were exploratory in nature and not powered for statistical significance.

While we observed patterns that merit further investigation, these data require prospective validation.

Approximately 80% of participants completing 12 months of therapy opted to continue in a long-term extension (LTE), which remains ongoing.

Given the absence of approved therapies for CCM, we plan to discuss next steps with regulatory authorities and anticipate providing an update in 2025.

To our knowledge, the REC-994 program is the first industry sponsored therapeutic program in clinical trials for CCM.

If approved, REC-994 would be the first pharmacologic disease-modifying treatment for CCM, one of the largest areas of unmet need in the rare disease space.

We are aware of two other programs currently active in clinical development for CCM:

• NRL-1049 (Neurelis):

In Phase 1 SAD study

• RLY-2608 (Relay Therapeutics):

Expected to initiate FIH study Q1 2025

REC-2282 for Neurofibromatosis Type 2 - Phase 2/3

REC-2282 is a small molecule potential best-in-class HDAC inhibitor currently under development for the treatment of NF2 -mutant meningiomas.

In prior clinical trials, the molecule was well tolerated, including in patients who were dosed for multiple years.

In contrast to approved HDAC inhibitors, REC-2282 is CNS-penetrant and orally bioavailable.

An adaptive, Phase 2/3, randomized, multicenter study is ongoing with Phase 2 data continuing to mature.

As of December 31, 2024, enrollment in Phase 2 is complete.

Orphan Drug Designation in the US and EU as well as Fast Track Designation in the US were granted to REC-2282 for NF2.

Results from the futility analysis (PFS6 rate) of the Phase 2 portion of the study expected in the first half of 2025.

31 SYCAMORE data on file.

Disease Overview

Neurofibromatosis type 2 (NF2) is a rare, inherited tumor syndrome characterized by multiple nervous system tumors, primarily bilateral vestibular schwannomas and meningiomas.

This autosomal dominant condition typically manifests in late teens or early 20s, with initial symptoms including unilateral hearing loss and focal neurological deficits.

As the disease progresses, patients may experience bilateral hearing loss, facial paralysis, balance issues, and visual problems.

Approximately 50% of NF2 patients develop meningiomas, often multiple, with a lifetime risk reaching 75%.

Treatment is challenging due to tumor locations that often preclude complete resection, leading to significant morbidity and early mortality.

With an estimated 33,000 NF2 -driven meningioma patients annually in the US and EU5, there is an urgent need for new treatment approaches to reduce tumor burden and improve patient outcomes.

There is currently no cure or approved treatment for NF2 -driven meningioma.

Insight from Recursion OS

We selected REC-2282 as a candidate for our NF2 program using our brute-force phenotypic screening approach in NF2 -deficent HUVEC cells.

REC-2282 was uniquely identified as reversing the cellular and structural defects back to a wildtype like morphological state.

The compound demonstrated concentration dependent rescue, showing no significant activity on other tumor suppressors or oncogene knockdown models.

These data validated REC-2282’s selective activity, supporting advancement into preclinical studies for NF2 mutant tumors.

Discovery of REC-2282 in Recursion OS.

REC-2282 rescued the high-dimensional disease phenotype as evidenced by a concentration dependent rescue from the disease state to the healthy state.

REC-2282 is an oral, CNS-penetrant pan-HDAC inhibitor with PI3K/AKT/mTOR pathway modulatory activity.

With high oral bioavailability, CNS exposure, and no reported cardiovascular liabilities to date, REC-2282 is differentiated over existing HDAC inhibitors for treating NF2 and NF2-mutant CNS tumors.

NF2 mutations disrupt merlin, a tumor suppressor that normally inhibits PI3K/AKT/mTOR signaling.

REC-2282 targets this pathology by disrupting the PP1-HDAC interaction, suppressing PI3K/AKT signaling to induce cancer cell growth arrest and apoptosis.

This mechanism addresses both HDAC-mediated epigenetic dysregulation and NF2-driven pathway hyperactivation.

REC-2282 acts on an important pathway in tumor development to inhibit the growth of tumor cells.

A potential mechanism of action of REC-2282 in NF2.

REC-2282 demonstrated potent anti-tumor activity in NF2-relevant models, inhibiting proliferation of vestibular schwannoma (VS) and meningioma cells via AKT inactivation (cell cycle arrest/apoptosis).

It suppressed tumor growth in NF2-deficient mouse VS allografts, human VS xenografts (25 mg/kg/day for 45 days), and orthotopic NF2-deficient meningioma models (Ben-Men-1 cells).

REC-2282 prevents growth & regrowth of tumors in the NF2-deficient meningioma mouse model.

REC-2282 suppressed the growth of Ben-Men-1-LucB tumor xenografts as measured by tumor bioluminescence.

32 Adapted from Petrilli and Fernández-Valle.

Role of Merlin/NF2 inactivation in tumor biology.

Oncogene, 35(5), 537-48.

33 Burns SS, et al.

Histone Deacetylase Inhibitor AR-42 Differentially Affects Cell-cycle Transit in Meningeal and Meningioma Cells, Potently Inhibiting NF2-Deficient Meningioma Growth.

73(2), 792-803.

Four investigator-sponsored trials (ISTs) of REC-2282 established a 60 mg TIW MTD for solid tumors with manageable cytopenia.

In an early Phase 1 pharmacodynamic IST, REC-2282 suppressed aberrant activation of ERK/AKT/S6 pathways in resected human, results which may be potentially difficult to achieve with single pathway inhibitors of ALK or MEK.

An adaptive, Phase 2/3, randomized, multicenter study (POPLAR) to evaluate the efficacy and safety of REC-2282 in patients with progressive NF2-mutated meningiomas with underlying NF2 disease and sporadic meningiomas with documented NF2 mutations is currently ongoing.

As of December 31, 2024, the Phase 2 portion is fully accrued with 25 adult participants enrolled.

Once all 25 subjects complete six months of treatment, a futility analysis will be conducted to determine a go/no-go for the Phase 3 portion of the study.

We expect to share this data in the first half of 2025.

POPLAR Phase 2/3 study schema.

Phase 2/3 study design to assess the safety, tolerability, and preliminary efficacy of REC-2282 in patients with progressive NF2-mutated meningiomas.

We are aware of 4 programs currently in clinical development targeting NF2-driven meningiomas

• Selumetinib (AstraZeneca):

Completed Phase 2 single-center study

• VT3989 (Vivace Therapeutics):

In Phase 1/2 study

• Brigatinib and Neratinib (Takeda in collaboration with CTF and DFCI):

Completed Phase 2 IST

• GSK225609 (Alliance for Clinical Trials in Oncology):

Completed Phase 2 IST for meningiomas

REC-4881 for Familial Adenomatous Polyposis (FAP) - Phase 1b/2

REC-4881 is an orally bioavailable, non-ATP-competitive, allosteric small molecule inhibitor of MEK1 and MEK2 currently under development for familial adenomatous polyposis (FAP).

REC-4881 was well tolerated in prior clinical studies, demonstrating dose-dependent increases in exposure and pharmacological activity.

We are currently enrolling patients in TUPELO, a Phase 1b/2, open-label, multicenter study to evaluate the effect of REC-4881 on polyp burden reduction.

Orphan Drug Designation in the US and EU as well as Fast Track Designation in the US were granted to REC-4881 for FAP.

We expect to share Phase 2 safety and preliminary efficacy data in the first half of 2025.

Disease Overview

FAP is a rare, inherited tumor predisposition syndrome affecting approximately 50,000 patients in the US and EU5, resulting from heterogeneous mutations in the APC gene, a key negative regulator of the Wnt signaling pathway.

FAP is characterized by the progressive development of hundreds to thousands of adenomas in the colon and rectum, with an almost 100% lifetime risk of colorectal cancer by early adulthood if untreated.

While prophylactic colectomy during adolescence is the standard of care, many patients continue to develop adenomatous lesions in the rectum/pouch and duodenum sustain cancer risk, necessitating further endoscopic or surgical interventions.

In advanced cases, larger adenomas and carcinoma may require localized surgeries, such as radical Whipple procedures, which carry significant morbidity and mortality.

Despite this substantial disease burden, no approved therapies currently exist for FAP.

Insights from Recursion OS

REC-4881 was identified as a potential first-in-disease therapy for FAP using a high-content phenotypic screening approach targeting APC-deficient human cells.

In this screen, REC-4881 emerged as a potent allosteric MEK1/2 inhibitor that rescued an APC siRNA genetic knockdown-associated morphological phenotype.

Compared to other MEK inhibitors, REC-4881 demonstrated a highly selective and concentration-dependent response, suggesting best-in-class potential.

As a result, REC-4881 was in-licensed from Takeda and subsequently advanced into preclinical studies.

Discovery of REC-4881 in Recursion OS.

Compared to thousands of other molecules tested, REC-4881 rescued phenotypic defects associated with APC siRNA genetic knockdown.

REC-4881 is an orally bioavailable, non-ATP-competitive allosteric inhibitor of MEK1 (IC 50 :

2-3 nM) and MEK2 (IC 50 :

3-5 nM) being developed as a potential first-in-disease therapy for FAP.

Loss of APC disrupts β-catenin regulation, leading to uncontrolled Wnt signaling, RAS stabilization, and ERK pathway activation, which drives MYC-dependent proliferation.

REC-4881 inhibits MEK1/2, and blocks ERK phosphorylation downstream.

This reduces MYC expression levels in the cell and potentially restores Wnt pathway control.

REC-4881 inhibits APC-mutation induced MAPK signaling to block cell proliferation in the context of FAP.

A potential mechanism of action of REC-4881 in cells with loss of function mutations in APC.

34 Jeon, WJ, et al.

Interaction between Wnt/β-catenin and RAS-ERK pathways and an anti-cancer strategy via degradations of β-catenin and RAS by targeting the Wnt/β-catenin pathway.

NPJ Precision Oncology, 2(5).

REC-4881’s activity was validated in tumor cell lines and spheroid models derived from APC-mutant human epithelial tumor cells.

In these systems, REC-4881 inhibited spheroid growth and disrupted cellular organization, demonstrating over 1,000-fold selectivity in APC-mutant cells.

In a disease-relevant FAP model, Apc Min/+ mice were treated with multiple oral doses of REC-4881 or celecoxib over eight weeks.

While celecoxib reduced polyp formation by approximately 30% compared to vehicle, REC-4881 treatment led to a reduction of 50% (1-3 mg/kg), and 70% (10 mg/kg).

Mice that were treated with 10 mg/kg REC-4881, the highest dose tested, exhibited an approximately 70% reduction in total polyps.

REC-4881 reduces GI polyp count and pre-cancerous, high-grade adenomas in the Apc Min/+ mouse model of FAP.

GI polyp count (left) and the percentage of high-grade adenomas (right) after oral administration of indicated dose of REC-4881, celecoxib, or vehicle control for 8 weeks.

Polyp count at the start of dosing reflects animals sacrificed at the start of study (15 weeks of age).

P < 0.001 for all REC-4881 treatment groups vs.

vehicle control.

Quantification of high-grade adenomas versus total polyps was based on blinded histological review by a pathologist.

While celecoxib reduces benign polyps, most remaining lesions are high-grade adenomas.

By contrast, REC-4881 reduces both polyps and high-grade adenomas.

REC-4881 has been evaluated in multiple clinical studies, demonstrating a well-tolerated safety profile and pharmacological activity.

Phase 1 Oncology Studies

In a prior dose-escalation study (C20001) conducted by Millennium Pharmaceuticals in 51 participants with non-hematologic malignancies, REC-4881 (formerly TAK-733) was administered at doses ranging from 0.2 mg to 22 mg once daily.

The maximum tolerated dose (MTD) was determined to be 16 mg.

The most common adverse events (AEs) were rash (67%), and treatment-related serious adverse events (SAEs) were infrequent.

No unexpected safety concerns emerged, and pharmacokinetic analyses showed a less-than-dose proportional increase in exposure.

REC-4881-101 (Healthy Volunteers)

We conducted a Phase 1 study to evaluate the safety and pharmacokinetics of REC-4881 in 25 healthy participants receiving single doses of 4 mg, 8 mg, and 12 mg.

REC-4881 was well tolerated, with no SAEs or dose-related safety concerns.

The most common treatment-emergent adverse events (TEAEs) were mild and self-limiting, including transient blurred vision and vitreous floaters.

No QTcF abnormalities were observed.

35 Data on file.

TUPELO (Phase 1b/2 in FAP)

We are currently enrolling patients in TUPELO, a Phase 1b/2 open-label, multicenter study evaluating the efficacy, safety, pharmacokinetics, and pharmacodynamics of REC-4881 in FAP.

Part 1 assessed safety, tolerability, and pharmacokinetics in FAP patients receiving 4 mg once daily for 14 days.

REC-4881 was generally well-tolerated, with a safety profile consistent with other MEK inhibitors.

Preliminary pharmacodynamic data suggests the 4 mg dose is pharmacologically active in FAP.

Part 2 will evaluate efficacy, safety, and pharmacokinetics in post-colectomy FAP patients with confirmed germline APC mutations.

Participants will receive once-daily REC-4881 for three months.

Safety and preliminary efficacy data from Part 2 are expected in the first half of 2025.

Phase 1b/2 study schema for REC-4881.

Phase 1b/2 clinical study to assess the efficacy, safety, and pharmacokinetics of REC-4881 in patients with classical Familial Adenomatous Polyposis (FAP)

We are aware of seven other currently active programs in clinical development for FAP:

• ALFA (SLA Pharma/KD Pharma):

In Phase 3 trial in patients with confirmed APC mutations post-colectomy

• Flynpovi (Panbela Therapeutics):

In Phase 3 combination therapy targeting lower GI disease in FAP

• eRapa (Biodexa Pharmaceuticals):

Planned Phase 3 for FAP

• TPST-1495 (Tempest Therapeutics):

Planned Phase 2 trial in FAP

• Lapatinib (Johnson & Johnson):

Completed Phase 1 trial in FAP

• ST-316 (Sapience Therapeutics):

In Phase 1/2 with dose expansion study ongoing in colorectal cancer

• ZKN-013 (Almirall/Eloxx Pharmaceuticals):

In Phase 1 trial that includes an FAP cohort

REC-3964 for Prevention of Recurrent Clostridioides Difficile Infection - Phase 2

REC-3964 is an orally bioavailable, non-antimicrobial, small molecule designed to prevent recurrence of Clostridioides difficile (C.diff) infection (rCDI) and serve as a secondary prophylactic therapy in high-risk patients.

Unlike antibiotics, which can further disrupt gut microbiota and contribute to relapse, REC-3964 selectively targets C.

difficile toxin B without affecting the host.

Identified using Recursion’s AI-driven phenotypic screening platform, REC-3964 demonstrated potent toxin inhibition and barrier restoration in preclinical studies.

A Phase 1 study established its safety, tolerability, and pharmacokinetics, supporting the initiation of the ALDER Phase 2 trial in Q3 2024.

This trial is evaluating REC-3964’s ability to reduce recurrence rates in patients recovering from a recent C.

diff infection.

We expect to share preliminary data in the first quarter of 2026.

Disease Overview

diff is a significant cause of antibiotic-associated diarrhea, leading to severe colitis and potentially fatal outcomes.

Annually, over 730,000 cases are reported in the U.S.

and EU5, with approximately 29,000 deaths in the U.S.

Standard antibiotic treatments can disrupt the gut microbiome, resulting in recurrence rates of 20 to 30% after initial infection, increasing to 40% after the first recurrence and 45–65% after multiple recurrences.

This escalating pattern underscores the urgent need for novel therapeutic approaches that address rCDI.

Insight Recursion OS

Leveraging the Recursion OS, we identified REC-3964 as a new chemical entity that selectively inhibits the glucosyltransferase activity of C.

difficile toxin B.

This non-antibiotic approach was discovered through a high-content phenotypic screen, where REC-3964 demonstrated potent reversal of toxin-induced cellular damage in HUVEC.

We drove SAR and optimization of REC-3964 directly on the platform and subsequently advanced the molecule into preclinical studies.

REC-3964 rescued the phenotype of human epithelial cells treated with C.

difficile toxin.

REC-3964 was identified as demonstrating concentration-responsive rescue in HUVEC cells treated with C.

difficile toxin B on Recursion’s phenomics platform.

REC-3964 was validated in orthogonal functional assays including the electrical cell-substrate impedance sensing (ECIS) assay where it demonstrated concentration-dependent activity in blocking toxin-mediated barrier disruption.

In a hamster model of C.

diff , REC-3964 treatment significantly prolonged survival compared to bezlotoxumab and control groups, indicating its potential to reduce both initial infection severity and recurrence rates.

REC-3964 selectively inhibits the toxin’s innate UDP-glucose glucosyltransferase.

(Left) Autocatalytic event releases C.

difficile toxin’s glucosyltransferase enzymatic domain into the infected cell, which locks Rho family GTPases in the inactive state.

Inactivation of Rho GTPases alters cytoskeletal dynamics, induces apoptosis and impairs barrier function which drives the pathological effects of C.

difficile infection.

(Right) REC-3964 binds and blocks catalytic activity of the toxin’s innate glucosyltransferase with no effect on the host protein.

Clostridium difficile virulence factors:

Insights into an anaerobic spore-forming pathogen.

Gut Microbes.

5(5), 579-593.

REC-3964 in vivo efficacy in a CDI hamster model.

REC-3964 was administered at 200 mg/kg by oral gavage twice daily for 7 consecutive days along with groups for vehicle and vancomycin (50 mg/kg, QD).

Bezlotoxumab was administered at 10 mg/kg BID 2 days prior to inoculation with C.

difficile (strain 630).

N=10 hamsters per group.

Clinical observations were conducted from Day 0 to Day 7, with surviving animals monitored until Day 14.

REC-3964 demonstrated a significant difference in the probability of survival vs.

bezlotoxumab at the end of treatment (p<0.001, log-rank test).

REC-3964 has been evaluated in a Phase 1 study in healthy volunteers and is currently being investigated in the ALDER Phase 2 trial for rCDI.

Phase 1 (Healthy Volunteers)

A Phase 1 study assessed the safety, tolerability, and pharmacokinetics of REC-3964 in 90 healthy participants, including a cohort of elderly subjects (>65 years).

REC-3964 was well tolerated at single doses up to 1,200 mg and multiple doses up to 900 mg, with no serious adverse events (SAEs), discontinuations, or deaths.

The most common treatment-emergent adverse events (TEAEs) were mild and included fatigue, headache, and abdominal distension, with similar rates between REC-3964 and placebo groups.

Pharmacokinetics demonstrated dose-proportional exposure with a 7 to10 hour half-life, supporting twice-daily (BID) dosing.

No clinically significant effects on ECG parameters, vital signs, or laboratory markers were observed.

Results were presented at the 6th Edition of the World Congress on Infectious Diseases in June 2024.

Phase 2 (ALDER – Ongoing, Initiated Q3 2024)

The ALDER study is a Phase 2 open-label, multicenter trial evaluating REC-3964 as secondary prophylaxis therapy in patients recovering from an initial C.

diff infection.

Participants will be randomized 2:1:1 to receive 500 mg or 250 mg BID for 28 days, compared to an observational cohort.

The primary endpoints are safety, tolerability, and recurrence rates of rCDI.

A Phase 2 data update is expected in the first quarter of 2026.

To our knowledge, REC-3964 is the first orally bioavailable, non-antibiotic, C.

diff toxin inhibitor that selectively targets bacterial toxin, while sparing the host.

37 Stiles, et al.

REC-3964, a First-in-Class Molecule for the Prevention of Recurrent Clostridioides difficile Infection [poster].

World Congress on Infectious Diseases.

Planned Phase 2 study schema of REC-3964 for prevention of rCDI.

Phase 2 open-label, multicenter clinical study to assess the safety, tolerability, PK, and efficacy of REC-3964 at two dose levels.

Enrollment criteria include (1) High risk for rCDI;

difficile associated diarrhea with confirmation of toxin positivity (3) No fulminant CDI;

(4) No history of chronic diarrheal illness due to other causes.

The primary endpoints are safety, tolerability, and efficacy as determined by the rate of reduction of rCDI after initial clinical cure with vancomycin.

There are a number of approved drugs for the treatment and prevention of C.

difficile infection.

• Vancomycin, Fidaxomicin (Merck), and Metronidazole:

Most commonly prescribed antibiotics;

however, the efficacy of antibiotic therapy decreases with each recurrence

• Bezlotoxumab (Merck):

Approved for reducing CDI recurrence in patients receiving antibiotics who are at high-risk for CDI recurrence

• RBX2660 (Ferring) and SER-109 (Seres Therapeutics):

Approved stool derived microbiome products used for recurrent CDI prevention, following antibiotic treatment

We are aware of seven currently active programs in clinical development for the prevention of recurrent C.

difficile infection:

• VE303 (Vedanta Biosciences):

In Phase 3 study for 14-day course in patients with ≥ 1 prior occurrence of CDI, including a high-risk for recurrence population along with an open-label extension if recurrence of CDI occurs during study

• NTCD-M3 (Sebela Pharmaceuticals/Destiny Pharma):

In Phase 3 planning stages for naturally occurring non-toxigenic strain of C.

• LMN-201 (Lumen Bioscience):

In Phase 2 study in patients newly diagnosed with CDI planning to receive antibiotic treatment

• CRS3123 (Crestone):

In Phase 2 study assessing two different doses compared to vancomycin

• IMM-529 (Immuron):

In Phase 2 study for primary and recurrent CDI

• OraCAb (MicroPharm):

In Phase 2 planning stages to assess oral immunotherapeutic for primary and recurrent CDI

• AZD5148 (AstraZeneca):

In Phase 1 study assessing the anti-toxin B neutralizing mAb injectable for the reduction of CDI recurrence

Selected Preclinical Programs:

• REV102 a potential first-in-class and best-in-class ENPP1 inhibitor for Hypophosphatasia (HPP)

• REC-4209, a potential first-in-class NCE for the treatment of Idiopathic Pulmonary Fibrosis (IPF)

REV102 for Hypophosphatasia – IND Enabling

In 2019, Recursion (formerly Exscientia) and Rallybio established a co-development and co-ownership joint venture to apply AI-driven drug discovery to rare diseases.

Using Recursion’s generative AI platform, Gambit, we identified ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) as a target for the treatment of Hypophosphatasia (HPP).

ENPP1 catalyzes the production of inorganic pyrophosphate (PPi), exacerbating the mineralization imbalance in HPP patients.

Inhibiting ENPP1 offers a novel therapeutic approach to restoring PPi balance, promoting proper bone formation.

This led to the discovery and development of REV102, a selective, orally bioavailable ENPP1 inhibitor optimized for chronic dosing with high potency and a favorable safety profile.

As of December 31, 2024, REV102 has advanced to development candidate status, with IND-enabling studies expected in 2025.

If successful, REV102 could provide the first oral treatment for juvenile-onset and adult HPP, addressing the limitations of enzyme replacement therapy (ERT) and expanding treatment options for patients with unmet needs.

Disease Overview

HPP is a rare genetic disorder caused by ALPL mutations, leading to deficient tissue-nonspecific alkaline phosphatase (TNAP) activity and PPi, a potent inhibitor of bone mineralization.

PPi accumulation disrupts hydroxyapatite formation, resulting in skeletal deformities, fractures, and premature tooth loss.

HPP severity varies from severe early-onset cases, presenting in infancy with life-threatening complications, to juvenile-onset and adult forms, which cause progressive fractures, pain, and mobility issues.

Current treatment is limited to enzyme replacement therapy (ERT), and is associated with frequent injections, immunogenicity, and costs exceeding $1 million per year.

By selectively inhibiting ENPP1, REV102 aims to restore physiological mineralization by normalizing PPi levels, offering a non-immunogenic, oral alternative to ERT.

With an estimated 7,800 diagnosed HPP patients at birth in the US and EU5, REV102 has the potential to expand treatment access to underserved patients.

Insight from Recursion OS

Using our GenAI platform, we designed REV102, a potential first-in-class and best-in-class orally bioavailable and highly selective ENPP1 inhibitor for HPP.

Our proprietary generative AU design algorithm, Gambit, guided precision optimization, incorporating rigorous 3D and 2D constraints to ensure high potency and suitability for lifelong chronic dosing.

This AI-driven approach allowed the discovery of a structurally distinct compound with strong target engagement, designed to restore PPi homeostasis and improve bone mineralization in juvenile-onset and adult HPP patients.

In preclinical studies, our first-generation tool compound, REV101, demonstrated improved bone mineralization in HPP mouse models.

Bone morphometry analysis showed that L3 vertebrae in treated HPP mice reached mineralization levels comparable to wildtype mice, while trabecular regions of the distal femur exhibited slight improvement.

Notably, REV101 significantly reduced plasma PPi levels by approximately 30%, restoring them to wildtype levels after 100 days of dosing.

These findings validate ENPP1 inhibition as a viable therapeutic approach for HPP and informed the design and optimization of REV102 for clinical development.

(Left) ENPP1 inhibition results in improved mineralization in mouse models of HPP.

Alpl-/ Prx1 mouse model.

2D Bone morphometric analysis of trabecular bones was performed on Von Kossa-stained sections using the Kawamoto’s film method.

(Right) ENPP1 inhibition reduces PPi levels to those of wild-type mice.

Alpl-/ Prx1 in an adult-onset HPP mouse model.

Plasma levels of PPi following 100 days of dosing.

38 Narisawa, et al.

ENPP1 Inhibition as a Therapeutic Approach for Later-onset Hypophosphatasia [late breaking poster].

American Society for Bone and Mineral Research (ASBMR) Annual Meeting.

REC-4209 for Idiopathic Pulmonary Fibrosis (IPF) – IND Enabling

Recursion identified REC-4209, a potential first-in-class, orally bioavailable immuno-mesenchymal modulator for idiopathic pulmonary fibrosis (IPF) using phenotypic screening of human PBMC-derived fibrocytes.

This approach uncovered Target Epsilon, a novel regulator of fibrotic diseases.

REC-4209 selectively modulates fibrocytes, fibrotic macrophages, and adaptive immune cells, offering a potential disease-modifying approach distinct from current therapies.

REC-4209 is currently undergoing IND-enabling studies in preparation for clinical development.

Disease Overview

IPF is a chronic, progressive interstitial lung disease characterized by fibrotic remodeling of lung tissue, leading to irreversible respiratory decline.

The disease affects approximately 3 million patients globally, with incidence rising significantly in individuals over 50 years old.

Fibroblast accumulation, myofibroblast activation, and excessive extracellular matrix deposition contribute to progressive lung volume loss and impaired gas exchange.

Repeated epithelial injury, coupled with immune dysregulation and fibroblast dysfunction, drives self-perpetuating fibrosis in IPF.

Current antifibrotic therapies, nintedanib and pirfenidone, only slow disease progression, leaving an urgent unmet need for disease-modifying treatments that restore tissue integrity.

Phenotypic screening assay.

Differentiation of human PBMCs into fibrocytes can be reversed by Pentraxin-2, a tissue repair protein, to mimic a healthy state.

Small molecules are identified which rescue disease state to healthy state.

Insight from Recursion OS

We developed a PBMC-derived fibrocyte phenotypic screen to model fibrotic disease and identify novel therapeutic targets in an unbiased manner.

This approach identified multiple small molecules capable of mimicking the effects of pentraxin-2 (PTX-2), an endogenous anti-fibrotic protein involved in monocyte differentiation and macrophage polarization.

Combining our inferential search capabilities within the Recursion OS, we uncovered Target Epsilon, a novel regulator of immuno-mesenchymal cell function.

Biochemical validation confirmed small molecule binding to Target Epsilon, leading to the identification and optimization of REC-4209, a potent and selective compound designed to reverse fibrosis by restoring immune-mesenchymal homeostasis.

Target and compound identification and validation related to Target Epsilon.

(1) Disease Score of 1.0 reflects “disease state” while disease score of 0.0 reflects “healthy state”;

(2) cosine similarity between REC-1169575 and genetic knockout of Epsilon is the cosine of the angle between the two vectors in high-dimensional space.

Values near 1.0 suggest the angle between perturbations is near 0° and is interpreted as directionally phenosimilar;

and (3) Target Epsilon NanoBRET assay.

39 Data on file.

REC-4209 demonstrated potent activity in phenotypic reversal assays, with an EC 50 of 0.40 µM in fibrocyte rescue and an IC 50 of 12 nM to Target Epsilon.

In digital tolerability studies, REC-4209 was well tolerated in C57BL/6 mice at doses up to 300 mg/kg/day (PO, 6 days), with no significant effects on body weight, breathing rate, motion, or body temperature.

In a rodent fibrosis model, REC-4209 significantly reduced collagen deposition, a key histological marker of fibrosis.

These findings support REC-4209’s potential to halt fibrotic progression, positioning it as a novel disease-modifying therapy for IPF.

REC-4209 reduces collagen in a mouse model of fibrosis.

REC-4209 at low doses reduces total lung collagen by 45% to 60% versus vehicle treated mice.

Groups (n=10 per group;

n=6 in control) compared to vehicle.

****p<0.0001;

one-way ANOVA with Tukey’s multiple comparison test.

Data reflects mean ± 95% CI.

Therapeutics Partnerships:

ENLYGHT is a Phase 1, open-label, multicenter dose escalation study designed to evaluate the safety, tolerability, and preliminary efficacy of REC-4539 monotherapy in patients with select solid tumors.

The FDA cleared an IND application in January 2025;

the program was then placed on strategic pause in May 2025.

While the broader field has faced safety challenges, REC-4539 remains highly differentiated by its optimized profile, and we now expect to initiate a Phase 1 trial in the first half of 2026.

The Phase 1 study will evaluate REC-4539 as a monotherapy in patients with SCLC and select other solid tumors, to assess safety and tolerability, PK/PD, to establish the MTD, and to evaluate preliminary efficacy as per the study design diagram below.

We expect to share early safety and PK monotherapy data in the second half of 2027.

ENLYGHT study design.

Phase 1 trial design to assess the safety, tolerability, and preliminary efficacy of REC-4539 monotherapy.

The LSD1 inhibitor competitor landscape is limited to a small number of programs currently advancing in active clinical development.

These programs vary by indication of interest, combination strategy, and development priority.

Active LSD1i clinical development programs:

• Bomedemstat (Merck) - Merck is focusing on myeloproliferative neoplasms (MPNs) as a route to market for bomedemstat.

Bomedemstat is being investigated in a Phase 3 trial in essential thrombocythemia (ET), a Phase 2 study in myelofibrosis (MF) and polycythemia vera (PV), and a Phase 1 IIT study in AML (in combination with venetoclax).

Merck terminated a Phase 1/2 SCLC trial in combination with PD-L1 maintenance in 2024 due to low accrual rates.

• Iadademstat (Oryzon) - Iadademstat is being investigated in AML and SCLC patient populations.

It is in an ongoing Ph1b study for R/R AML with FLT3 mutation in combination with gilteritinib and in a Ph1b study for newly-diagnosed unfit AML in combination with venetoclax and azacitidine.

It is also in a Phase 2 IIT for relapsed/refractory (R/R) SCLC and extrapulmonary high-grade NETs (in combination with paclitaxel), as well as a Phase 1b/2 IIT in first-line extensive-stage SCLC (ES-SCLC) in combination with a checkpoint inhibitor.

• JBI-802 (Jubilant Life Sciences) - JBI-802 is in a Phase 1/2 basket study, with expansion cohorts planned in SCLC, neuroendocrine prostate cancer (NEPC), and other NETs, as well as a Phase 2 study for patients with advanced NSCLC tumors harboring an STK11 Mutation in combination with pembrolizumab.

• TAS1440 (Benz Sciences/ Taiho Pharmaceuticals) - Benz Sciences are preparing for a Phase 1b/2 study for MPN patients, after in-licensing TAS1440 from Taiho Pharmaceuticals in June 2025.

Taiho recently completed a Phase 1 trial targeting AML in the US population.

Partnered Discovery

Driving Innovation Across Multiple Diseases

At the core of Recursion’s mission is the pursuit of breakthrough therapeutics for patients.

Recursion collaborates with leading pharma partners to explore a wide range of disease areas—including fibrosis, neuroscience, oncology, immunology, and inflammation.

Together, these partnerships aim to identify novel targets and therapeutic candidates spanning small molecules, large molecules, gene therapies, and cell therapies.

Recursion collaborates with leading pharma partners to identify novel targets and therapeutic candidates across a wide range of disease areas, including neuroscience, oncology, immunology, and inflammation.

Each partnership is designed to advance therapeutic development, with multiple pathways to success:

• Novel Therapeutics:

By leveraging Recursion’s comprehensive maps of biology capabilities, large compound libraries are rapidly screened, uncovering differentiated therapeutics without preconceived target hypotheses.

This approach allows Recursion to identify unique solutions that address significant medical needs.

With our newly added precision chemistry capabilities, we can support our partners towards potential first-in-class and best-in-class therapies.

• Novel Targets:

Recursion’s platform’s ability to profile diverse biological perturbations—including genetic factors—enables the discovery of novel druggable targets.

Recursion then collaborates with partners to transform these insights into promising therapeutic candidates.

Recursion’s strategic business combination with Exscientia has significantly expanded its partnership value, bringing leaders like Sanofi and Merck KGaA into the fold.

To date, Recursion has secured $450 million in upfront milestone payments, with the potential to unlock over $20 billion in additional milestones before royalties.

These high-impact collaborations not only generate near-term financial value but also leverage Recursion’s combined capabilities in biology, precision chemistry, and automated synthesis to accelerate the development of transformative therapies.

Combining our multi-modal (phenomics, RNA sequencing) maps of human biology with real-world clinical-genomic data, we can identify novel druggable targets with potential therapeutic benefit.

Validated targets may be optioned by our partners or advance within the collaborations as a therapeutic program.

• Novel Therapeutics:

Using our precision chemistry platform, we can design differentiated molecules across a wide variety of targets.

Resulting molecules may be optioned by our partners and advanced for further clinical development.

To date, Recursion has secured over $500 million in upfront milestone payments, with the potential to unlock over $20 billion in additional milestones before royalties.

These high-impact collaborations not only generate near-term financial value but also leverage Recursion’s combined capabilities in biology and precision chemistry to accelerate the development of transformative therapies.

By collaborating with top-tier biopharmaceutical companies, Recursion gains access to invaluable knowledge from some of the most experienced teams in the industry.

Together, with Recursion’s AI-driven platforms, proprietary data, and deep scientific expertise we continuously drive innovation, expand patient impact, and revolutionize the treatment of complex diseases.

Together, we continuously drive innovation and have the potential to expand patient impact, and revolutionize the treatment of complex diseases.

Below are some of the latest milestones reflecting this exciting momentum.

40 Data on file.

Key Highlights

Recursion leveraging its OS across its partnerships.

Potential Roche and Genentech and Sanofi milestones per small molecule program.

Recursion is eligible for tiered royalties up to high single digits (Roche and Genentech) and up to double digits (Sanofi)

Roche and Genentech

In December 2021, we entered into a multi-year, strategic collaboration with Roche and Genentech in key areas of neuroscience and an oncology indication.

Through the partnership, we are working with both Roche and Genentech's R&D units to leverage our Recursion OS and Maps of Biology, along with extensive single-cell perturbation screening data from Roche and Genentech, to rapidly identify novel biological relationships to initiate and advance therapeutic programs.

Together we may initiate up to 40 programs over a decade or longer.

• Gastrointestinal-Oncology Advancements:

• Neuro-specific CRISPR KO Phenomap:

In partnership with Roche and Genentech, we’ve developed the first whole-genome CRISPR knockout map in neural iPSC cells, providing valuable data to identify potential new targets in neuroscience, an area with limited new discoveries.

• Milestones and Collaboration:

The neuroscience phenomap work led to the exercise of a $30M option from Roche and Genentech in August 2024, and we’re moving forward with target validation projects.

Under our collaboration with Roche & Genentech, we are creating multimodal maps of cellular biology to elucidate novel targets and starting points.

In January 2022, we entered into a strategic research collaboration with Sanofi to develop an AI-driven pipeline of precision-engineered, small molecule medicines.

In December 2021, we entered a multi-year, strategic collaboration with Roche and Genentech in the field of neuroscience and a single oncology indication.

Through the partnership, we are leveraging the Recursion OS and extensive single-cell perturbation screening data from Roche and Genentech, to rapidly identify novel biological relationships and advance therapeutic programs.

Together, we may initiate up to 40 small molecule programs over a decade or longer.

As part of this agreement, we received an upfront cash payment of $150 million, with the potential to receive milestones of more than $300 million per small molecule program plus tiered royalties.

Under our collaboration with Roche and Genentech, we are creating multimodal maps of cellular biology to elucidate novel targets and starting points.

In January 2022, we entered a strategic research collaboration with Sanofi to develop an AI-driven pipeline of precision-engineered, small molecule medicines.

Through this collaboration, we are using our end-to-end integrated platform to discover and advance up to 15 novel targets in the oncology and immunology therapeutic areas.

As part of this agreement, we received an upfront cash payment of $100 million, with the potential to receive up to $5.2 billion in total aggregate milestone payments plus tiered royalties.

• Immunology & Oncology Achievements:

in 2024, we reached milestones in two programs, generating $15M in aggregate payments from Sanofi in 2024.

In November 2023, we announced an updated collaboration with our established partner, Bayer, for a select set of precision oncology programs.

The collaboration will leverage our state-of-the-art capabilities to initiate and advance the identification of novel therapeutic targets for challenging oncology indications with high unmet need.

Under the terms of the agreement, we may initiate up to seven oncology programs and Recursion is eligible to receive potential, success-based, future payments of up to $1.5 billion plus royalties on net sales.

• Oncology Achievements:

Completed 25 multimodal oncology data packages utilizing the Recursion OS platform, with programs rapidly progressing to Lead Series nomination.

Additionally, Bayer has adopted our LOWE LLM-orchestrated workflow software to enhance their research capabilities.

Leveraging the Recursion OS with Sanofi to design small molecules against challenging targets using AI

In November 2023, we announced an amended and restated collaboration with Bayer.

We are using the Recursion OS to identify and advance up to 7 therapeutic targets for challenging oncology indications with high unmet need.

Under the terms of the agreement, Recursion is eligible to receive potential, success-based, future payments of up to $1.5 billion plus royalties on net sales.

Merck KGaA (Darmstadt, Germany)

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This multi-year collaboration utilizes our AI-driven precision drug design and discovery capabilities while leveraging Merck KGaA, Darmstadt, Germany’s disease expertise in oncology and immunology, clinical development capabilities, and global footprint.

• Recursion is continuing to focus on leveraging our discovery engine to identify first-in-class and best-in-class targets across oncology and immunology, driving innovation in these key therapeutic areas.

Case Study 1:

Delivering the World’s First Neuromap

Recursion launched a transformational collaboration with Roche-Genentech, delivering the world’s first whole-genome neuromap in 2024.

In 2021, Recursion launched a transformational collaboration with Roche-Genentech to create the world’s first Neuromap—a comprehensive and scalable neuronal data model powered by machine learning.

Recursion launched a transformational collaboration with Roche and Genentech, delivering the world’s first whole-genome neuromap in 2024.

In 2021, Recursion launched a transformational collaboration with Roche and Genentech to create the world’s first neuromap—a comprehensive and scalable neuronal data model powered by machine learning.

This effort aimed to uncover novel insights into neurodegenerative diseases, a category of illnesses that has long been difficult to tackle using traditional drug discovery methods.

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Neurodegenerative diseases had long been a difficult area for drug development.

The traditional approaches has yielded limited breakthroughs, and the complexity of the biological system presented a higher bar for success.

Recursion needed to develop new technologies and methodologies to produce and analyze neuronal data on a scale never before attempted in drug discovery.

Traditional approaches had yielded limited breakthroughs, and the complexity of the biological system presented a higher bar for success.

Recursion needed to develop new technologies and methodologies to produce and analyze neuronal data on a scale not attempted before in drug discovery.

Recursion had already proven its ability to create large-scale cell maps in other disease areas, notably in gastrointestinal oncology, as part of its partnership with Roche and Genentech.

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However, creating a neuromap would require more than just expanding on previous work - it required adapting the process to handle the unique challenges posed by neuronal biology.

To tackle this challenge, Recursion collaborated with Genentech to develop and refine a model using human-induced pluripotent stem cells (hiPSCs), which could be differentiated into neurons.

To tackle this challenge, Recursion collaborated with Roche and Genentech to develop and refine a model using human-induced pluripotent stem cells (hiPSCs), which could be differentiated into neurons.

This protocol enabled Recursion to produce large quantities of neurons, ultimately generating over 1 trillion hiPSC-derived neuronal cells.

These neurons served as the foundation for the Neuromap, a data-rich resource that Recursion, Genentech and Roche could use to gain deeper insights into the genetic underpinnings of neurodegenerative diseases.

These neurons served as the foundation for the neuromap, a data-rich resource that Recursion, Roche and Genentech could use to gain deeper insights into the genetic underpinnings of neurodegenerative diseases.

In addition to the joint development of the neuronal cell context, Recursion’s machine learning team played a pivotal role in developing algorithms capable of processing the massive amounts of data generated by the neuromap.

The combination of scalable cell production and cutting-edge computational models allowed Recursion to generate the first whole-genome neuronal phenomap that can be utilized by the partnership to uncover new relationships between genes and the phenotypes associated with neurodegeneration.

Our work led to the exercise of a $30M option by Roche and Genentech in August 2024 with the Neuromap offering an unbiased view of the genetic relationships related to neurodegenerative diseases and providing insights that could pave the way for development of novel therapies in neuroscience.

Our work led to the exercise of a $30 million option by Roche and Genentech in August 2024 with the neuromap offering an unbiased view of the genetic relationships related to neurodegenerative diseases and providing insights that could pave the way for development of novel therapies in neuroscience.

Unlike traditional approaches that are often guided by pre-existing hypotheses, researchers in the collaboration can now explore new biological pathways and identify potential therapeutic targets that may not have been considered before.

Even as these avenues are being explored, the team is also pursuing the development of even more robust Neuromaps.

This first map is a genetics-only map, with the whole genome knockout and many additional perturbations related to neurodegenerative diseases.

Future maps could comprise additional cell types or large compound libraries.

Technology Partnerships

As Recursion continues to generate and leverage highly relatable and reliable datasets to support our internal pipeline and therapeutic partnerships, we continue to invest in advanced compute capabilities and data-centric solutions to strengthen our drug discovery and development efforts.

Expanding on our previous release of select datasets and models, we are exploring additional opportunities to make more datasets and foundational models available to the broader scientific community.

Our collaborations with NVIDIA.

Google Cloud, Helix, and Faro Health underline our commitment to implementing AI and technology-enabled solutions to support our efforts to bring better medicines to patients faster.

In July 2023, we entered a strategic collaboration with NVIDIA to accelerate the development of our groundbreaking AI foundation models for biology and chemistry using our supercomputer, BioHive-1, and priority access on NVIDIA DGX™ Cloud.

In May 2024, we completed BioHive-2, Recursion’s new NVIDIA DGX SuperPOD AI supercomputer, powered by 63 DGX H100 systems with a total of 504 NVIDIA H100 Tensor Core GPUs increasing the computational capacity by over 4X.

The BioHive-2 supercomputer is believed to be the most powerful supercomputer wholly owned and operated by any pharmaceutical company and was ranked as number 54 in the top supercomputers globally by the Top500 list in 2024.

In May 2024, we entered into a multi-year agreement with Helix to access hundreds of thousands of de-identified clinic-genomic records consisting of longitudinal clinical records paired with Helix’s Exome+® genomic data.

The Helix dataset expands our efforts to use real-world patient data to train causal AI models and design biomarker and patient stratification strategies across broad disease areas.

In October 2024, we announced an expanded collaboration with Google Cloud leveraging their technologies to accelerate drug discovery research and further enhance our ability to bring new medicines to patients faster.

Through this collaboration, we will explore generative AI capabilities, including Gemini models, to support the RecursionOS.

We will improve data search and access from our proprietary dataset with BigQuery and facilitate the scaling of compute resources to run large inference workflows effectively.

Additionally, in November 2024, we announced the release of OpenPhenom-S/16 in Google Cloud’s Vertex AI Model Garden.

OpenPhenom, a non-commercial, publicly available foundation model built on microscopy data, sets a new “gold standard” for the industry, outperforming CellProfiler.

This model offers the potential for researchers to replace their existing workflows with an off-the-shelf model that outperforms traditional microscopy analysis pipelines without requiring any additional tuning or training.

In December 2024, we entered into an agreement with Faro Health to leverage their AI-powered platform for clinical protocol design to reduce clinical trial costs and complexity while minimizing burden to trial participants and sites.

We plan to use the Faro platform to optimize the protocol design for upcoming clinical trials.

We also anticipate utilizing the structured study definitions created through Faro’s software to automate traditionally labor-intensive and time-consuming historically downstream tasks, such as building the Electronic Data Capture system for each study.

Together, Recursion, Roche and Genentech have identified a number of biological insights from this first neuroscience-focused phenomap, that could become novel targets of interest.

Case Study 2:

Delivering the World’s First Microglia Map

Recursion launched a transformational collaboration with Roche and Genentech, delivering the first-of-its-kind microglia map in 2025.

In 2025, building on the success of the original neuromap, Recursion reached another milestone in its collaboration with Roche and Genentech by launching the world’s first microglia map.

Microglia are the resident immune cells of the brain and play a central role in neuroinflammation and the progression of neurodegenerative diseases.

By mapping the whole genome within these complex cells, the microglia map represents a completely new approach to explore the cellular mechanisms underlying neurodegenerative diseases, offering a new approach to explore novel targets and pathways.

The Challenge

Despite decades of research, FDA approvals for neuroscience drugs are less than half of those for other therapeutic areas, and drugs targeting the CNS have some of the highest failure rates in medicine.

Attrition rates are high, and traditional approaches can be biased to dominating hypotheses e.g.

the "Amyloid Hypothesis" in Alzheimer’s disease.

This is the idea that a build-up of the amyloid protein is a major contributor to the disease, and while this hypothesis has historically guided research and led to deep insights into the condition, the underlying biology is both extremely complex and still poorly understood.

To provide an unbiased approach to explore novel targets and pathways, the team studied microglia.

However, microglia are very difficult to work with, proving difficult to grow and keep alive and stable outside of the body, in a laboratory setting.

Because microglia are the resident immune cells of the brain, they can be highly sensitive to their environment, changing states from relatively stable to becoming more reactive and inflammatory, and they are also highly variable from batch to batch.

To create a reliable map, Recursion had to overcome the technical hurdle of producing these sensitive immune cells at a massive, industrial scale while ensuring they remained stable enough to provide a clear biological signal for machine learning models.

Tackling this effort was a multi-year collaboration that required Recursion and the Roche and Genentech microglia team to develop new protocols for the manufacture of microglial cells.

Starting with human-induced pluripotent stem cells (hiPSCs), the team developed a protocol that allowed the most phenotypically active cell Recursion has ever tried to map to be grown at massive scale.

Over 100 billion microglial cells were grown in a standardized way and confirmed to be as stable as possible for the start of the mapping process.

The collaborative team also worked together to determine the most interesting disease-like perturbations to the microglia from a neuroscience perspective, to generate a rich dataset containing some novel knockdowns and overexpressions not previously tried in other maps.

This resulted in 100,000 single guide RNA being used spanning more than 17,000 genes, 46 million microglial cell images, and thousands of chemical compound perturbations.

Recursion foundation models, powered by the supercomputer BioHive-2, extracted insights to generate the first-of-its-kind microglia map, allowing scientists to use AI to systematically explore how different genes and compounds may be implicated in a wide range of neurological diseases.

The successful completion of the microglia map led to a $30 million milestone payment from Roche and Genentech in October 2025.

The microglia map provides a holistic, unbiased approach to drug discovery for neurodegenerative diseases compared with the slow traditional approach, which has yielded very few new therapeutic targets.

The map allows for the systematic, unbiased evaluation of thousands of gene targets at once, allowing AI to uncover novel biological connections that humans might miss.

Overall, this offers a new approach to exploring novel targets and pathways, addressing a major challenge in neuroscience drug discovery.

Following on from development of the map, it will be mined for novel biological insights, which will move forward to robust experimental validation from Recursion in partnership with Roche and Genentech.

This could lead to program selection and development, and potential new therapeutic approaches in neurological diseases.

A Unified, AI-Native Platform for Drug Discovery & Development

Recursion is leading the evolution of how medicines are discovered and developed with the Recursion OS:

a unified, AI-native intelligence platform designed to translate complex science into medicines that matter — faster, better, and at scale for the patients who are waiting.

Our approach combines proprietary experimental data, purpose-built computational models, and scaled compute infrastructure to support decision-making across the full lifecycle of drug discovery and development.

Rather than optimizing isolated tools or workflows, we organize our platform around three tightly connected stages of value creation:

novel biological discoveries, precision design, and next-generation clinical development.

Together, these stages enable us to initiate programs with stronger biological grounding, design differentiated molecules more efficiently, and advance medicines into the clinic with improved patient relevance.

Across all three stages, Recursion integrates automated wet-lab experimentation with in-house computational analysis.

Our laboratories generate large volumes of standardized, high-quality biological and chemical data, while our dry-lab capabilities apply machine learning, physics-based modeling, and statistical inference to extract actionable insights from those data.

This tight integration allows experimental results to directly inform computational models, and model outputs to guide subsequent experiments, enabling faster iteration and more consistent decision-making across programs.

Additionally, the integration of agentic and automated systems underpins our approach at Recursion and enables us to accelerate learning and decision-making throughout the R&D process.

The Recursion OS

The Recursion OS.

The Recursion OS is designed to use AI to advance and accelerate decision-making and insight across the entire R&D value chain with the end goal to make novel medicines that matter.

The Recursion OS generates value by advancing a pipeline of differentiated investigational medicines, in addition to building pipelines for our partners.

By leveraging the Recursion OS to explore and advance our programs, we have shown leading indicators of improvement when compared to the traditional drug discovery process, particularly with respect to cost and time.

We also use AI/ML tools to better understand which molecules to make and test and ultimately design better quality molecules that can solve complex problems – on average, the industry synthesizes about 2,500 molecules to candidate, compared to the approximately 330 we synthesize per program to advanced candidate.

Biology to Insight

The first stage of the Recursion OS focuses on translating complex biological signals into actionable insights that support program initiation.

Recursion combines large-scale cellular phenomics, high-throughput transcriptomics, in silico binding affinity predictions, and real-world patient data to identify disease-relevant mechanisms, validate targets, and prioritize opportunities with stronger biological grounding and patient relevance.

These capabilities allow us to systematically interrogate biology at scale and reduce biological uncertainty earlier in the discovery process.

A core differentiator of this approach is the integration of complementary data modalities.

Patient-derived data are the most directly relevant to human disease but are often noisy, heterogeneous, and limited in scale.

In contrast, cellular phenomics data can be generated reproducibly, at scale, with high completeness and consistency.

By integrating these and other modalities through joint forward- and reverse-genetics approaches, Recursion can connect robust experimental signals with patient biology, enabling more confident identification and prioritization of translatable targets.

• Generated and aggregated >50 petabytes of high-quality, multimodal data

• Over 100 novel insights triaged into ~10 actionable and translatable targets for experimental validation within a matter of weeks

• ~1.9B-parameter phenomics foundation model delivers ~25–30% gains in biological signal accuracy

• New transcriptional foundation model delivers a 70% improvement in operational efficiency

Phenomics-based Discovery

Phenomics is Recursion’s large-scale, image-based cellular profiling capability that measures functional cellular responses to genetic and chemical perturbations and serves as a foundational input to biological discovery and program initiation.

Using high-content microscopy, automated experiment design and execution, and purpose-built machine learning models, we generate rich, high-dimensional phenotypic data that capture cellular behavior across diverse biological contexts.

Our platform is differentiated by its scale, precision, and breadth, operating both Cell Painting and live-cell brightfield microscopy across nearly 50 distinct cell types, including differentiated iPSC-derived neuronal and microglial cells.

These experimental capabilities directly enhance our advanced computer vision and foundation models, including our Phenom-2 model series, by enabling our models to learn true biology as opposed to experimental design patterns.

The impact of this capability is reflected in both our internal pipeline and strategic partnerships, including the development of two first-of-their-kind whole-genome neuronal and microglia phenotypic maps as part of our collaboration with Roche and Genentech.

More broadly, phenomics has enabled Recursion to initiate and advance multiple internal and partnered programs by supporting unbiased discovery, rapid hypothesis triage, and identification of novel biological insights that may translate into new therapeutic opportunities.

Transcriptional Foundation Model (TxFM)

TxFM is Recursion’s self-supervised transcriptomics foundation model designed for representation learning of complex gene expression data.

Built on a transformer-based architecture optimized for biological structure rather than natural language analogies, TxFM harmonizes diverse transcriptomic datasets—including bulk and single-cell RNA sequencing across multiple assays, cell types, and translational systems—into a unified embedding space.

Many transcriptomic models rely on large, heterogeneous public atlases that limit cross-experimental comparability and translational consistency.

TxFM leverages Recursion’s proprietary data strategy and architecture decisions to improve cross-sample and cross-experiment relatability, enabling consistent integration of in vitro experiments, in vivo models, and patient-derived samples.

This not only captures a more universal biological grammar but also allows us to outperform larger models trained on datasets up to 50x larger in size.

By representing experimental perturbations and patient transcriptomes within the same high-dimensional space, we can begin to perform in silico perturbations on digital patient representations, serving as a practical translational bridge between laboratory biology and human disease.

TxFM has demonstrated state-of-the-art performance across multiple zero-shot benchmarks, outperforming existing foundation models and classical baselines.

Within the Recursion OS, TxFM improves batch correction and multi-dataset integration, enhances signal recovery from low-read-depth transcriptomic data, and enables consistent mapping of gene–gene and gene–compound relationships.

By improving data consistency and reducing the need for experimental re-runs, TxFM has delivered an approximate 70% improvement in operational efficiency for transcriptomics-driven workflows.

Furthermore, the model’s learned gene-specific parameters recover known protein complexes and pathways without supervision, providing a non-perturbational gene-gene map for over 40,000 genes, including non-coding RNAs.

These capabilities strengthen target discovery, accelerate hypothesis validation, and improve the biological and patient relevance of programs entering the pipeline.

Insight to Molecule

Once we have nominated a program, either through insights derived from our phenomics and multiomics platforms or through the careful selection and validation of a high-potential target, we transition from biological discovery to precision molecular design.

Our precision design platform, anchored by Centaur Chemist, represents a transformative shift from traditional trial-and-error drug discovery to a fully integrated, AI-first industrialized process.

By fusing massive, high-dimensional biological and chemical datasets with advanced generative AI and automated synthesis, the platform enables the rapid design, prioritization, and physical testing of novel small molecules.

This modular end-to-end engine is designed to navigate trillions of biological and chemical relationships with unprecedented speed and efficiency, aiming to deliver higher-quality drug candidates to the clinic while significantly reducing development timelines and costs.

Centaur Chemist serves as a critical component of our unified operating system, driving a continuous "design-make-test-learn" or DMTL cycle that refines its predictive capabilities with every successive iteration.

◦ 100 million+ molecules generated virtually using synthetically aware design in 2025

◦ ~90% of synthesized molecules are AI-generated, scored, and prioritized – all patentable

◦ On average, only ~330 compounds are synthesized per program to achieve an advanced candidate in ~17 months, compared to industry average of over 2,500 compounds and 42 months, respectively,

◦ To date, the platform has designed >10 development candidates that address a wide variety of previously unsolved biological or chemistry problems

Centaur Chemist Methods and Models

At its core, Centaur Chemist is an AI-first learning system that automates the design, prioritization, and optimization of novel small molecules.

It is not a single piece of software but an integrated platform within the Recursion OS that enables the development and deployment of a vast number of design tools that have been developed in-house, including the following proprietary models:

• Generative AI and Evolutionary Models:

These create novel chemical structures based on target profiles

• Synthesis-Aware Methods:

The platform employs an expansive synthesis-driven design toolkit that couples advanced billion-scale search algorithms (e.g.

SALSA) and accurate chemo- and regioselectivity models with up-to-date vendor logistics to rigorously generate synthetically feasible compounds and expedite their reduction to practice

• Protein and Target Tractability predictions.

These methods predict protein structures with and without the presence of ligands, enabling ligandability and druggability of targets.

• Property Prediction and Scoring:

Our industry leading advanced models, including our proprietary version of Boltz-2 that allows us to fine-tune the model on internal program data, predict potency (see figure below), selectivity, and ADMET (absorption, distribution, metabolism, excretion, and toxicity).

• Physics Methods:

A toolkit of physics-based methods that apply molecular dynamics and quantum mechanics, which enables us to more accurately predict target-ligand interactions and properties, fully integrated with our generative design capabilities.

The platform not only incorporates our in-house proprietary methods and algorithms but makes it simple to deploy open-source and licensed software, ensuring that we are using state-of-the-art methods developed by the community as well.

Recursion potency models MolE and MolGPS outperform (lower is better on the Y-axis in figure) all other entrants in the 2025 blind challenge for potency predictions 21

DMTL (Design-Make-Test-Learn) and Automation

With these tools in place, our DMTL procedure begins by defining program objectives via a Target Product Profile (TPP), which is encoded using a multi-parameter optimization (MPO) function.

This ensures that potency and affinity are balanced with other critical ADMET properties, such as clearance, solubility, stability, and permeability.

Every generated molecule is scored by an integrated function called Merit, allowing us to monitor the quality of chemical matter across the program lifecycle in an unbiased, holistic manner.

This allows us to focus our efforts from the start on high-quality molecules that meet the needs of our drug discovery programs, optimizing for both cost and operational efficiency.

Once the Design phase is complete, synthesis (Make) is triggered through the platform, which can be routed through to our in-house chemistry automation studio or dedicated CROs.

Because our generative tools prioritize synthesizability from the outset, the platform utilizes property prediction models to guide design toward compounds that are both biologically optimized and amenable to efficient synthesis.

To achieve this "synthesis awareness," we account for building-block availability and logistics across different CROs, ensuring the system suggests the most cost- and time-effective synthetic routes.

A critical enabler of this physical execution is our in-house chemistry automation studio located in Milton Park, shown in the figure below, designed to support high-throughput DMTL cycles with minimal manual intervention (see Figure 40).

The modular, automated lab is designed to accelerate DMTL cycles by utilizing automation flexibly across the full Make workflow, with over 1000 compounds having now been made and tested at Milton Park.

The core mission of this DMTL procedure is to automate processes that reduce costs, optimize efficiency, and deliver high quality results to drive program success, not just making compounds that can easily be synthesized with automation.

Through 2025 there was a 4-fold increase in reaction classes executed with automation, including 14 reactions that are not typically automated.

21 Polaris hub competition results.

https://polarishub.io/competitions/asap-discovery/antiviral-drug-discovery-2025#competiton-results 12 February 2026

Recursion's automated chemistry wet lab, a modular system for chemical synthesis preparation, execution, analysis, work-up, and purification.

Following the Make phase, an assay cascade is initiated (Test).

Depending on program needs, this includes ADMET, affinity, and phenomic responses via our proprietary -omics platform in either Salt Lake City or Milton Park facilities.

Once an assay is completed, results are ingested back into the platform for analysis alongside all other relevant program data.

This data automatically updates our ML models, ensuring the most accurate information informs the next cycle and closes the Learning loop.

An example of this improvement is shown in Figure 38, which demonstrates that iterative learning has led to an approximately 50% improvement in a property prediction model.

Our models improve over time, not by chance, but by learning.

LogD model improvement over time as DMTL cycles progress, showing an approximately 50% increase in accuracy over time.

By tracking all data centrally we can monitor Design, Make, and Test durations, as well as lag times between phases.

Streamlining these workflows, both in-house and with CROs, allows us to identify and resolve bottlenecks in real time.

This continuous monitoring has driven significant productivity gains:

in 2025, our Design-to-Test times improved by 20% over 2024 benchmarks.

To further support our learning system, we also employ our RADME-01 platform.

This platform performs high-throughput ADME evaluations through intelligent software prioritization and automation.

The system generated over 35,000 total data points across >15,000 novel compounds, including >13,500 human and >5,000 mouse microsomal stability results, alongside thousands of points for PAMPA, protein binding, and rat stability.

RADME data is integrated into our proprietary datasets and automatically fed into our suite of ML models for comprehensive ADMET property prediction, which drives drug discovery during Nominations and Design.

We employed Active Learning with RADME to generate thousands of datapoints, expanding model training sets and boosting accuracy across design programs.

Additionally, new multi-task models optimally combine RADME and CRO assay data for related properties, delivering enhanced predictions to our design programs.

Molecule to Patient

The final stage of the Recursion OS focuses on translating molecules into clinical impact.

Recursion utilizes large scale multi-modal datasets to rigorously design and execute clinical trials.

As an example, by applying causal AI on human genomics, we select the indications and patient sub-populations most likely to benefit from our investigational therapies.

Our AI-driven study planning algorithms applied to our operational data recommend site selection to enhance enrollment in minutes.

Our clinical trials incorporate advanced statistical methods across several design elements from selecting optimal doses to forming external control arms to expanding the eligible patient population for our studies.

These capabilities form Recursion’s Clinical Development Technology (ClinTech) platform, an AI-enabled clinical development system that unifies molecule-to-patient decisions within an integrated workflow.

It combines global site intelligence data, real-world patient data—including ~300 million real world lives and 1 million molecularly profiled lives—with causal inference, simulation, and agentic automation to continuously inform trial strategy and execution.

By embedding patient relevance and operational feasibility earlier in development, ClinTech supports more disciplined trial design and execution at portfolio scale.

◦ ~1 million molecularly profiled lives between Tempus, Helix, and UK Biobank.

Used across our clinical and preclinical portfolio for target validation and patient selection.

Impact includes but not limited to:

▪ Expansion into ovarian cancer for the CDK7 program

◦ De-identified records covering ~300 million real-world lives, including electronic health records, diagnostics, and medical & pharmacy, leading to.

▪ 10-40% increase in eligible population

▪ ~1.5X improvement in enrollment rates

◦ Global clinical trial site intelligence database covering a wide swath of historical clinical trials

▪ Data driven country & site selection in hours vs.

In practice, ClinTech shortens the cycle from protocol to site activation and enrollment by turning fragmented clinical operations data into actionable, real-time recommendations.

For example, the platform can shorten the time to prioritize countries and sites from months (industry standard) to hours using multimodal site intelligence data.

It can forecast enrollment trajectories as criteria evolve—enabling benefit-risk tradeoffs that can meaningfully expand the eligible population and improve enrollment performance.

It can reinforce upstream portfolio decisions through genetically informed target validation and patient selection.

Across the trial lifecycle, these capabilities translate into increased probability of success and timely execution of our clinical studies.

AI-driven clinical development platform for trial design and execution

Natural History Data in Familial Adenomatous Polyposis (FAP)

Recursion applied its ClinTech platform to generate high-quality natural history evidence to contextualize the single-arm efficacy of REC-4881 in the TUPELO study.

Natural history data are increasingly important to regulators in rare diseases, yet for FAP there has historically been limited quantified evidence describing disease progression outside of clinical trials.

To address this gap, Recursion leveraged real-world evidence analytics and AI-enabled data extraction to build a comprehensive view of the lived FAP patient experience across routine clinical practice and long-term registry data.

Using ClinTech’s real-world data capabilities, Recursion analyzed records from more than 1,000 US patients with FAP, including over 250,000 unstructured physician notes processed using a custom large language model–based workflow.

This analysis enabled systematic characterization of disease burden, intervention frequency, and the progressive nature of polyp growth in everyday clinical care.

Recursion extended this work through an academic collaboration with Amsterdam UMC, analyzing nearly 20 years of longitudinal follow-up data from approximately 200 patients enrolled in one of the largest and longest running FAP registries globally.

Together, these datasets enabled a level of real-world disease characterization that is rarely available in rare disease development.

Across both real-world and registry datasets, the findings were consistent and clinically meaningful:

untreated FAP is characterized by predictable, year-over-year progression of polyp burden in 87% of the trial-relevant patient populations, with a mean annualized increase of 60%.

These insights provided a robust, data-driven benchmark for contextualizing therapeutic impact and directly informed the clinical development strategy for REC-4881, including support for a single-arm study design aligned with regulatory expectations.

More broadly, this work illustrates how ClinTech augments clinical development with unbiased real-world insight, strengthens the translational path from molecule to patient, and enables more confident engagement with regulators in rare disease programs.

Processing and Data Storage Infrastructure

The need to understand pathways, targets, compounds, and mechanisms of action requires obtaining, synthesizing, or predicting large volumes of data.

To store this data in an efficient and low-risk way, Recursion makes use of a combination of cloud storage, and on-premises storage.

To process this data efficiently, we bring it close to where the compute will run – either in our HPC datacenter (BioHive) or to our cloud (partnering with Google Cloud).

People and Culture

Essential to leading and defining TechBio is our team of over 800 Recursionauts, comprising life scientists such as chemists and biologists (approximately 43% of employees) and computational and technical experts such as data scientists and software engineers (approximately 36% of employees).

This kind of functional balance intentionally stands in contrast to traditional biotechnology companies.

Essential to leading and defining TechBio is our team of close to 600 employees, comprising of life scientists, such as chemists and biologists (approximately 35% of employees) and computational and technical experts such as data scientists and software engineers (approximately 43% of employees).

Together our team creates an environment where empirical data, statistical rigor and creative thinking is brought to bear on the problems we address.

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Deliberately building and cultivating this culture is critical to achieving our audacious goals.

Breakdown of Recursion’s over 800 employees across life sciences, technology and strategic operations.

One of the most critical elements supporting Recursion’s leadership in TechBio is what we call the Recursion Mindset – a deep belief and commitment to industrialization through automation, systems-thinking, algorithms and data to deliver our mission.

This mindset fuels our creative energy focused on Recursion’s hardest problems.

The Recursion Mindset is made manifest through our Founding Principles and supported by our culture and values.

Our Founding Principles are the guideposts for our technical and scientific decision-making.

Our values are the core standards and behaviors that define how we work together to achieve our mission.

Combined they shape our culture and inspire us to reimagine how medicines are made.

Recursion’s Founding Principles.

These six founding principles differentiate our approach from nearly every other biopharma company, enable us to lead TechBio and form the foundation for a mindset we teach and enrich for at Recursion.

Recursion’s Values.

These five values support our founding principles and guide our culture at Recursion.

Maximizing Delivery through Diversity

At Recursion we believe a diversity of experiences, backgrounds, ideas and expertise will create high performing teams.

Varied and diverse perspectives support better complex decision-making, foster greater innovation and ultimately result in greater company performance and success.

We seek the best talent by maximizing diversity at the top of the recruiting funnel and then mitigating bias through objective decision-making throughout the hiring process.

We foster an environment of inclusion for candidates and employees to unleash the strength of our differences.

In 2025, we made significant progress to deploy agentic and automated AI solutions across the workforce to enhance enterprise productivity and efficiency.

In our technology organization, approximately 91% of employees are actively using AI coding tools to accelerate their work.

As a result, 35% of our code is authored by AI, allowing our teams to focus on solving the problems and trusting AI to accelerate creating the solution.

This saves an average of 4.3 hours of work per week, per employee.

Employee Recruitment, Development and Training

At Recursion, we believe a diversity of experiences, backgrounds, ideas and expertise will create high performing teams.

We are intentional about the employee experience at Recursion, with a fit-for-purpose system that finds, grows and retains top talent to deliver our mission.

Our people are mission-driven, humble, bright, generous of spirit and constructively dissatisfied with the status quo.

We employ a targeted approach to identify, attract and hire diverse employees across highly technical scientific disciplines including:

biology, chemistry, data science, machine learning, engineering, robotics, clinical development and more.

We seek people that are aligned with – and emboldened by - our commitment to industrialization as defined by our Recursion Mindset.

We expect our employees to be constantly learning and adapting in order to evolve as quickly as Recursion.

Learning and development happens through daily work and projects, as well as formal training and industry conferences and engagements.

We offer a unique 2-day immersive experience to all employees called Decoding Recursion.

It is an opportunity for close interaction with senior leaders who teach the Recursion Mindset through stories.

Continual learning is reinforced throughout our performance system which creates accountability for our learning, delivery and impact on others.

We employ a targeted approach to identify, attract and hire diverse employees across highly technical scientific disciplines including biology, chemistry, data science, machine learning, engineering, robotics, clinical development and more.

People stay at Recursion because of the opportunity to impact the world and grow in a place where they feel challenged, supported, and connected.

Throughout the employee experience we create moments, rituals, programs and spaces that inspire ambition, reward contributions and growth and foster belonging.

Employee Health and Safety

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Compliance is mandatory for all laboratory employees per requirements of the Occupational Safety and Health Administration standard on Hazardous Chemicals in Laboratories.

Our Co-Founder and CEO is the Director of Public Safety at the company and has the ultimate responsibility for chemical hygiene within the organization.

Our Chemical Hygiene Officer and Lab Manager oversees the day-to-day management of institutional chemical hygiene.

Read more about how we invest in and motivate our people to achieve our mission in Recursion’s latest Environmental, Social and Governance Report, available at our corporate website.

Facilities Headquarters

Our United States headquarters is in downtown Salt Lake City, Utah where we lease ~200,000 square feet of office and laboratory space.

The lease for half of this space expires in May 2028 with the remainder expiring in May 2032.

Our modern headquarters is a draw for local, national and international talent.

Our European headquarters is in London’s Kings Cross neighborhood, where we lease 6,792 square feet of office through January 2029.

We also have laboratory space in Milton Park, Oxfordshire for our automation laboratory with approximately 20,151 square feet.

Our US headquarters is centrally located in downtown Salt Lake City, Utah and our EU headquarters in London with laboratory space in Milton Park, Oxfordshire.

Working with state and local government, we are helping to create a burgeoning life science ecosystem around a downtown cluster of companies centered around our headquarters.

Core Satellite Offices and Facilities

In addition to our two major headquarters in Salt Lake City, UT and London-Oxford, UK, we operate core satellite offices and a digital vivarium in key markets to attract top talent.

Toronto and Montréal

In Toronto, we operate a 28,110 square foot space in Toronto’s Queen Street West Neighborhood.

The lease for this space expires in November 2032.

In addition to our Toronto office, we have a 8,367 square foot site in Montréal that houses our semi-autonomous artificial intelligence research engine, Valence Labs, which is located in the world-renowned artificial intelligence and machine learning hub MILA.

Recursion’s global footprint is architected around two primary pillars:

industrialized wet lab infrastructure that powers platform operations and offices that allow us to attract and retain top talent.

Industrialized Wet Lab & Platform Operations Hubs

Our two heavy-infrastructure sites in Salt Lake City, Utah and Milton Park, Oxfordshire are designed for the massive-scale data generation that drives our platform.

These facilities house our robotics, automation, biology, and chemistry capabilities.

Our Salt Lake City site has capacity to generate phenomics and transcriptomics data, and at Milton Park, the automated lab assembles the vision of autonomous DTML loops.

• Salt Lake City, Utah:

We utilize 140,000 square feet of laboratory and office space in downtown Salt Lake City.

This campus houses our high throughput screening labs, generating large volumes of standardized high quality biological data across phenomic and transcriptomic endpoints.

• Milton Park, Oxfordshire:

This 20,151 square foot laboratory and office space serves as our primary European wet lab, focused on DMTL, quantitative pharmacology, complex bioassays, target validation, and automation engineering.

Strategic Talent and Office Hub

Our office locations in New York City, Montreal, and London are positioned in global centers for AI, scientific innovation, clinical development, and executive leadership.

• New York City:

In January 2025, we opened a new 11,655 square foot office in New York City’s Hudson Yards neighborhood.

This office serves as a key location for our clinical development team and executive functions.

Recursion’s satellite offices and facilities in key markets to attract top talent.

Digital Vivarium

We lease a 25,557 square foot property that serves as a rodent vivarium.

This lease expires in May 2028.

We use this facility to conduct drug-discovery enabling pharmacokinetic, pharmacodynamic and exploratory safety studies.

The facility is equipped with proprietary, digitally enabled cage technology.

Corporate Social Responsibility

We believe that to achieve our mission, we must act like the company we aim to be, which means we must be a good corporate citizen.

In recognition of our commitment to excellence in environmental, social and governance stewardship, Recursion received a Prime Rating in 2024 for ESG performance from Institutional Shareholder Services (ISS).

The ISS ESG Corporate Rating provides an assessment of a company's environmental, social and governance activity.

A Prime Rating is awarded to companies with ESG performance above a sector-specific threshold and is defined by ISS as "absolute best in class." Additionally, as of January 2024, Recursion was ranked 6 out of 367 companies (approximately top 2%) in the Biotech category by Morningstar Sustainalytics.

To date, we have focused our community efforts in areas of impact that are aligned with our Values and our strengths, including:

(i) diversity, equity and inclusion in technology and biotechnology (e.g., in 2020 the Recursion Foundation launched Altitude Lab, a life science incubator and accelerator for diverse health care entrepreneurs);

(ii) the growth and sustainability of our local life science and technology ecosystems (e.g., Recursion is a founding member of BioHive, a Utah life science collective);

and (iii) the promotion of sustainable environmental practices (e.g., Recursion aims to achieve net-zero greenhouse gas emissions across our operations by the year 2030).

We believe that through these principles of community engagement, we can extend our mission of radically improving lives to those in our communities.

Read more about how we are delivering on that belief in Recursion’s Environmental, Social and Governance Report.

This office serves as a key location for our executive leadership, strategy and clinical development teams,

We have a 8,367 square foot site in Montréal that houses our semi-autonomous artificial intelligence research engine, Valence Labs

Located in the knowledge quarter and heart of King’s Cross neighborhood, our 6,792 square foot office serves as a magnet for Europe’s top AI and computational talent.

Commercialization

We may retain significant development and commercial rights to some of our drug candidates.

If marketing approval is obtained, we may commercialize our drug candidates on our own, or potentially with a partner, in the United States and other geographies.

We retain significant development and commercial rights to some of our drug candidates.

If marketing approval is obtained, we may commercialize our drug candidates on our own, or potentially with a partner, in the US and other geographies.

We currently have no sales, marketing, or commercial product distribution capabilities.

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To date, we have obtained drug substance and drug product for our drug candidates from third party contract manufacturers.

We are in the process of developing our supply chain for each of our drug candidates on a project-by-project basis based on our development needs.

Strategic Partnership and Collaboration Agreements

To achieve our mission, we may partner with leading biotechnology companies, pharmaceutical companies and academic research institutions to access datasets, molecules, or other intellectual property.

Roche & Genentech Collaboration and License Agreement

Roche and Genentech Collaboration and License Agreement

On December 5, 2021, we entered into a Collaboration and License Agreement with Genentech, Inc.

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Upfront Payment.

In January 2022, Roche paid us an upfront cash payment of $150.0 million.

In January 2022, Roche and Genentech paid us an upfront cash payment of $150.0 million.

Phenomap Creation, Acceptance and Access.

Under the Collaboration Agreement, we are responsible for creating a certain number of phenomaps in each of the Exclusive Fields.

We will also provide Roche results to requested queries, at Recursion’s discretion, of our pre-existing human umbilical vein endothelial cells (HUVEC) phenomap.

Roche will have specified rights to request queries or have direct access to the Phenomaps to generate novel inferences that may lead to the discovery or development of therapeutic products.

We will also provide Roche and Genentech results to requested queries, at Recursion’s discretion, of our pre-existing human umbilical vein endothelial cells (HUVEC) phenomap.

Roche and Genentech will have specified rights to request queries or have direct access to the phenomaps to generate novel inferences that may lead to the discovery or development of therapeutic products.

Phenomap-Related Options in neuroscience.

Each of the neuroscience phenomaps requested by Roche and created by Recursion may be subject to either an initiation fee, acceptance fee or both.

Each of the neuroscience phenomaps requested by Roche and Genentech and created by Recursion may be subject to either an initiation fee, acceptance fee or both.

Such fees could exceed $250.0 million for sixteen (16) accepted phenomaps.

In addition, for a period of time after Roche’s acceptance of certain phenomaps, Roche will have the option to obtain, subject to payment of an exercise fee, rights to use outside the collaboration the raw images generated in the course of creating those phenomaps.

If Roche exercises its External Use Option for all twelve (12) eligible phenomaps, Roche’s associated exercise fee payments to Recursion could exceed $250.0 million.

Collaboration Programs and Roche Options.

Roche and Recursion will collaborate to select certain novel inferences with respect to small molecules or targets generated from the phenomaps for further validation and optimization as collaboration programs.

In addition, for a period of time after Roche and Genentech’s acceptance of certain phenomaps, Roche and Genentech will have the option to obtain, subject to payment of an exercise fee, rights to use outside the collaboration the raw images generated in the course of creating those phenomaps.

If Roche and Genentech exercises its External Use Option for all twelve (12) eligible phenomaps, Roche and Genentech’s associated exercise fee payments to Recursion could exceed $250.0 million.

Collaboration Programs and Roche and Genentech Options.

Roche and Genentech and Recursion will collaborate to select certain novel inferences with respect to small molecules or targets generated from the phenomaps for further validation and optimization as collaboration programs.

There can be up to 40 programs initiated as part of this collaboration.

Roche and Recursion may also combine sequencing datasets from Roche with Recursion’s phenomic imaging data and collaborate to generate new algorithms to produce multimodal maps from which additional collaboration programs may be initiated.

For every collaboration program that successfully identifies potential therapeutic small molecules or validates a target, Roche will have an option to obtain an exclusive license to develop and commercialize such potential therapeutic small molecules or to exploit such target in the applicable Exclusive Field.

In October 2023, Roche exercised its Small Molecule Validated Hit Option to further advance our first partnership program in GI-oncology.

This program continues in the hit to lead series phase.

Payments if Roche Exercises Option for a Collaboration Program.

Under the collaboration, Roche may initiate up to forty (40) small molecule programs.

Each small molecule collaboration program, if optioned and successfully developed and commercialized by Roche, could yield more than $300.0 million in research, development, commercialization and net sales milestones for Recursion, as well as mid- to high-single digit tiered royalties on net sales.

Recursion is also eligible for research, development, commercialization and net sales milestones for target collaboration programs optioned by Roche.

Roche and Genentech and Recursion may also combine sequencing datasets from Roche and Genentech with Recursion’s phenomic imaging data and collaborate to generate new algorithms to produce multimodal maps from which additional collaboration programs may be initiated.

For every collaboration program that successfully identifies potential therapeutic small molecules or validates a target, Roche and Genentech will have an option to obtain an exclusive license to develop and commercialize such potential therapeutic small molecules or to exploit such target.

Payments if Roche and Genentech Exercises Option for a Collaboration Program.

Under the collaboration, Roche and Genentech may initiate up to forty (40) small molecule programs.

Each small molecule collaboration program, if optioned and successfully developed and commercialized by Roche and Genentech, could yield more than $300.0 million in research, development, commercialization and net sales milestones for Recursion, as well as mid- to high-single digit tiered royalties on net sales.

Recursion is also eligible for research, development, commercialization and net sales milestones for target collaboration programs optioned by Roche and Genentech.

Recursion Programs.

If Roche does not exercise its options in the Collaboration Agreement for certain collaboration programs, we may, with Roche’s prior consent, choose to independently validate, develop and commercialize products in a limited number of such programs, subject to agreed milestones and royalties to Roche.

Roche will have rights to obtain an exclusive license to exploit such products by providing notice and paying us an opt-in fee and economics exceeding those that would otherwise be applicable if Roche had exercised its option for such program.

During an agreed period of time after the Collaboration Agreement’s effective date, we are subject to certain exclusivities that limit our ability to conduct certain research and development activities with respect to compounds and targets in the Exclusive Fields, other than pursuant to the collaboration with Roche.

If Roche and Genentech does not exercise its options in the Collaboration Agreement for certain collaboration programs, we may, with Roche and Genentech’s prior consent, choose to independently validate, develop and commercialize products in a limited number of such programs, subject to agreed milestones and royalties to Roche and Genentech.

Roche and Genentech will have rights to obtain an exclusive license to exploit such products by providing notice and paying us an opt-in fee and economics exceeding those that would otherwise be applicable if Roche and Genentech had exercised its option for such program.

However, we may continue pursuing products that we are researching and developing in the Exclusive Fields as of the effective date of the Collaboration Agreement.

The Collaboration Agreement includes standard termination provisions, including for material breach or insolvency and for Roche’s convenience.

The Collaboration Agreement includes standard termination provisions, including for material breach or insolvency and for Roche and Genentech’s convenience.

Certain of these termination rights can be exercised with respect to a particular Exclusive Field or exclusive license, as well as with respect to the entire Collaboration Agreement.

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If any additional target is identified for the collaboration, we would be eligible to receive additional milestone payments on such target.

Pursuant to the RCA, we granted to Merck KGaA, Darmstadt, Germany a worldwide, exclusive, transferable license (with the right to grant sublicenses through multiple tiers) to the intellectual property that is necessary or reasonably useful for development or commercialization of the target compounds and resulting products, if any, in order to develop, manufacture, commercialize and sell the target compounds

and resulting products, if any.

Merck KGaA, Darmstadt, Germany has the right to control the prosecution and maintenance of any patent rights related to intellectual property that is the subject of each program.

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After such 180-day period, The Company may elect to license such downloaded records for a longer period subject to additional terms and the payment of additional fees.

In exchange for these rights, the Company will pay Tempus an initial license fee in an amount equal to $22.0 million, or the Initial License Fee and annual license fees during the Term ranging between $22.0 million and $42.0 million, which, together with the Initial License Fee, totals up to $160.0 million over the Term, subject to the Company’s early termination, which may be triggered only following the third anniversary of the Master Agreement’s effective date, and payment by the Company of an early termination fee (as further discussed below).

In exchange for these rights, the Company paid Tempus an initial license fee in an amount equal to $22.0 million, or the Initial License Fee and agreed to pay annual license fees during the Term ranging between $22.0 million and $42.0 million, which, together with the Initial License Fee, totals up to $160.0 million over the Term, subject to the Company’s early termination, which may be triggered only following the third anniversary of the Master Agreement’s effective date, and payment by the Company of an early termination fee (as further discussed below).

The Initial License Fee and each annual license fee shall be payable at the Company’s option either in the form of (x) cash, (y) shares of Class A common stock of the Company or (z) a combination of cash and shares of Class A common stock in such proportion as is determined by the Company in its sole discretion;

provided that (a) the aggregate number of shares of Class A Common Stock that the Company may issue in connection with all payments under this Agreement shall not exceed 19.9% of the aggregate total of shares of Class A Common Stock and the Company’s Class B Common Stock outstanding on November 2, 2023 or the date immediately preceding the date of any shares of Class A Common Stock issued pursuant to the Tempus Agreement, whichever is less (the “Share Maximum”).

that (a) the aggregate number of shares of Class A common stock that the Company may issue in connection with all payments under this Agreement shall not exceed 19.9% of the aggregate total of shares of Class A common stock and the Company’s Class B common stock outstanding on November 2, 2023 or the date immediately preceding the date of any shares of Class A common stock issued pursuant to the Tempus Agreement, whichever is less (the “Share Maximum”).

In the event that all or any portion of the Initial License Fee or any annual license fee is payable in the form of shares of Class A common stock, the Company shall, subject to the Share Maximum, issue to Tempus a number of shares of Class A common stock equal to (1) the amount of such fee divided by (2) the volume weighted average price of Class A common stock for the seven trading day period ending on the trading day immediately preceding (and including) the date that is five business days before the date on which such fee is paid (any shares so issued, the “Tempus Shares”).

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Either party may assign its rights under the Tempus Agreement subject to limited restrictions, but the Company may not assign the Tempus Agreement without Tempus’s consent if the proposed assignee is a large pharmaceutical company.

University of Utah Research Foundation Agreements

In February 2016, we entered into an Amended and Restated License Agreement with the University of Utah Research Foundation, or UURF, pursuant to which we obtained an exclusive license under certain patents and a non-exclusive license under certain know-how, in each case controlled by UURF and related to the drug tempol, or REC-994, to make, have made, use, offer to sell, sell, import and distribute products incorporating REC-994 worldwide for the treatment of cerebral cavernous malformation, or CCM.

In partial consideration for the license rights, we issued UURF equity in our company.

In addition, we agreed to reimburse UURF for a specified portion of costs associated with the filing, maintenance and prosecution of the licensed patent rights.

The Amended and Restated License Agreement will expire on a country-by-country basis upon the expiration of the last-to-expire patent within the patent rights in the applicable country.

UURF may terminate the agreement for an uncured material breach, if we cease commercially diligent efforts to develop or commercialize a licensed product or service, or our bankruptcy or insolvency.

Ohio State Innovation Foundation In-License

In December 2018, we entered into an Exclusive License Agreement with the Ohio State Innovation Foundation, or OSIF, pursuant to which we obtained an exclusive, sublicensable, non-transferable, royalty-bearing license under certain patents and fully-paid up, royalty-free, nonexclusive license under certain know-how, in each case controlled by OSIF and related to the pan-histone deacetylase inhibitor, OSU-HDAC42, or REC-2282, to develop, make, have made, use, sell, offer for sale and import products incorporating OSU-HDAC42 worldwide.

OSIF also assigned certain assets to us, relating to the pharmaceutical composition known as AR-42.

OSIF retains the right to use and allow other academic, nonprofit and government institutions to use the licensed intellectual property for research, non-commercial and educational purposes.

OSIF shall not practice, have practiced, or transfer such reserved rights for any clinical purpose other than completion of the existing clinical trials at the time of the license agreement without our prior written consent.

We are developing REC-2282 for the treatment of NF2 and are evaluating the utility of the compound in additional disease states using our platform.

Pursuant to the agreement, we must use commercially reasonable efforts to commercialize licensed products and are required to meet certain diligence milestones within two years following the execution of the agreement, including the initiation of clinical trials.

The license agreement is also limited by and made subject to certain rights and regulations of the government, including the Bayh-Dole Act.

In consideration for the license, we paid OSIF, an upfront payment of $2.0 million dollars and are obligated to pay OSIF certain milestones, totaling up to $20.0 million dollars, as well as mid-single digit royalties on net sales of the licensed products.

In addition, we owe 25% of any non-royalty sublicensing consideration prior to a Phase II clinical trial or 15% of such sublicensing consideration after initiation of a Phase II clinical trial, provided that milestone payments are creditable against these sublicensing fees.

In 2022, we paid OSIF $1.0 million dollars upon dosing of the first patient in the Phase 2 study of REC-2282 for the treatment of NF2.

The agreement expires on the expiration of the last valid claim within the licensed patents.

We may terminate this agreement on 90 days prior written notice to OSIF.

Either party may terminate the agreement on 60 days prior written notice for an uncured, material breach by the other party, or bankruptcy or insolvency of the other party.

Takeda License Agreement

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Our obligation to pay royalties continues on a country-by-country basis until the latest of expiration of the last to expire patent licensed by Takeda that covers the product, expiration of any regulatory exclusivity period for the product and ten years after the first commercial sale of the product, in such country.

As of the date of this filing, we have not made any milestone or royalty payments to Takeda.

Each party has the right to terminate the license agreement for the other party’s material uncured breach, insolvency or bankruptcy.

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Upon termination for any reason other than for Takeda’s breach of the license agreement, upon Takeda’s request we are obligated to negotiate in good faith, for a period of 120 days, terms and conditions of a license to Takeda under certain technology developed by us during the term of the agreement for the purpose of developing, commercializing and otherwise exploiting the licensed compounds and products containing the licensed compounds.

Target Epsilon:

Bayer License Agreement

In December 2023, we entered into a License Agreement with Bayer, the Bayer License Agreement, pursuant to which we obtained (a) an assignment of certain compounds, know-how and inventions related primarily to fibrosis, and (b) an exclusive, sublicensable and royalty-bearing license under certain project know-how related to fibrosis to research, develop, manufacture and commercialize products as independent research tools in all fields worldwide, subject to a non-exclusive, royalty-free license back to Bayer to use such licensed project know-how solely for internal research and development purposes.

We are required to use commercially reasonable efforts to develop and commercialize at least one product in one of the following countries:

(a) the US, (b) Japan, or (c) a country of the European Union.

Under the Bayer License Agreement, we are obligated to pay Bayer milestone amounts totaling up to approximately $34 million upon achievement of specified development, regulatory and sales milestones.

In addition, we are obligated to pay Bayer low single-digit royalties based on net sales of products containing certain compounds by us, our affiliates, or sublicensees, subject to specified reductions.

Our obligation to pay royalties continues on a product-by-product and country-by-country basis until the latest of:

(a) expiration of the last to expire patent filed by us, our affiliates or sublicensees that covers the product, and (b) ten years after the first commercial sale of the product in such country.

As of the date of this filing, we have not made any milestone or royalty payments to Bayer.

Each party has the right to terminate the license agreement for the other party’s material uncured breach.

In addition, we may terminate the agreement without cause.

Upon termination by us without cause or by Bayer for our breach, Bayer would have the right to use, practice, develop and exploit (including the right to sublicense) certain assigned know-how solely for Bayer’s internal research and development purposes.

Rallybio Purchase Agreement

In July 2025, we entered into a Membership Interest Purchase Agreement (the “Purchase Agreement”) with RallyBio Corporation and certain of its affiliates (“RallyBio”).

Pursuant to the Purchase Agreement, we acquired 50% of the issued and outstanding membership interests (the “Membership Interests”) of RE Ventures I, LLC (“ENPP1 JV”) from RallyBio in exchange for cash and shares of Class A common stock of the Company (the “RallyBio Shares”) with a value of $7.5 million.

Prior to the closing of the acquisition, we indirectly held 50% of the membership interests of ENPP1 JV.

As a result of the acquisition, ENPP1 JV is an indirect wholly-owned subsidiary of Recursion.

In August 2025, following the satisfaction of certain milestones with respect to the compound developed by the ENPP1 JV, we paid to RallyBio a milestone payment with a value of $12.5 million.

The Purchase Agreement also provides that Recursion will make additional cash payments to the Seller contingent upon the occurrence of certain future events, including based on the amount of the proceeds received by the Seller from the sale of the RallyBio Shares under certain circumstances and the occurrence of certain milestones or other events with respect to the compound developed by the ENPP1 JV.

Apeiron Asset Purchase Agreement

In July 2024, Exscientia and GT Apeiron Therapeutics Inc.

(“Apeiron”) announced that they had entered into an Asset Purchase Agreement, IP Assignment Agreement, Subscription Agreement and Share Surrender Agreement, pursuant to which Exscientia owned the full rights to the intellectual property in REC-617 as well as took full control of the CDK7 inhibitor program (the “IP Rights”) for the purpose of continuing independent research, development and commercialization efforts.

Concurrent to the transaction, Exscientia AI and Apeiron terminated the Collaboration Agreement, dated July 1, 2021, by and between Exscientia and Apeiron.

As consideration for the IP Rights, Exscientia made an upfront payment to Apeiron in the amount of $10 million and forgave Apeiron of all outstanding debt.

The Company also issued Apeiron $10 million of the Company’s equity in the form of restricted American Depositary Shares.

In addition, Exscientia AI surrendered 9,173,021 ordinary shares and 1,549,942 Series Pre-A preferred shares that Exscientia then held in Apeiron with no consideration being due from Apeiron to Exscientia or the Company.

Pursuant to the Asset Purchase Agreement, we shall pay Apeiron a single digit royalty, net of any applicable withholding taxes, if we or a third party commercializes REC-617.

We will take on all development costs and shall also pay Apeiron a single digit percentage of any outlicensing income received by us or our affiliates if we enter into an outlicensing agreement with a third party.

Technology Partnerships

Expanding on our previous release of select datasets and models, we are exploring additional opportunities to make more datasets and foundational models available to the broader scientific community.

Our technology and data collaborations underline our commitment to implementing data- and technology-enabled solutions to support our efforts to bring better medicines to patients faster.

The BioHive-2 supercomputer was ranked as number 76 in the top supercomputers globally by the Top500 list in 2025.

Through this strategic partnership, we will explore generative AI capabilities, including Gemini models, to support the Recursion OS.

We will improve data search and access from our proprietary dataset with BigQuery and facilitate the scaling of compute resources to run large inference workflows effectively.

Additionally, in November 2024, we announced the release of OpenPhenom-S/16 in Google Cloud’s Vertex AI Model Garden.

OpenPhenom, a non-commercial, publicly available foundation model built on microscopy data, sets a new “gold standard” for the industry, outperforming CellProfiler.

In May 2024, we entered into a multi-year agreement with Helix to access hundreds of thousands of de-identified records including Helix’s Exome+® genomic data and data from longitudinal health records.

Recursion continues to use this data to train causal AI models and design biomarker and patient stratification strategies across broad disease areas.

The Helix dataset expands Recursion's integration of real-world patient data and complements Recursion's access to Tempus' oncology data.

In April 2025, we entered into a license agreement with HealthVerity to access de-identified records for over 340M covered lives in the US.

Recursion is leveraging this real-world data to enhance clinical development by enabling smarter clinical trial design, accelerating patient recruitment and generating evidence to support clinical and regulatory decisions.

Our efforts to date have resulted in several clinical-stage programs, an expansive pipeline of differentiated programs in early discovery and preclinical development, several partnerships with large pharma and technology companies, as well as an intellectual property portfolio comprising patents, trademarks, software and trade secrets.

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Approximately one-half of the patents and patent applications that we own or license worldwide relate to the Recursion platform, including patents and applications related to the Recursion OS IP, as well as many other inventions related to Recursion’s machine learning and artificial intelligence capabilities, cell perturbations, gene editing, drug discovery, drug development and hardware solutions.

We also pursue a strategy of seeking patent protection on smaller discrete inventions throughout the breadth of our pipeline, ranging from experiment design, operations within our labs, data collection and analysis (including deep learning insights).

We also pursue a strategy of seeking patent protection on

smaller discrete inventions throughout the breadth of our pipeline, ranging from experiment design, operations within our labs, data collection and analysis (including deep learning insights).

• Recursion Program IP:

A breakdown of our Program IP portfolio is below:

We exclusively license OSIF’s interest in patents and patent applications related to REC-2282 from OSIF;

these patents and patent applications relate to composition of matter and methods of use treating cancer cachexia for REC-2282.

Currently, we expect our licensed issued patents related to REC-2282 to generally expire between 2030 and 2035, excluding any patent term extension, or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity or other governmental fee.

With respect to NF-2, orphan drug exclusivity in the U.S.

would run seven years from marketing authorization.

We exclusively license UURF’s interest in patents and patent applications related to use of REC-994 for treatment or prevention of CCM from UURF.

Currently, we expect our licensed issued patents related to REC-994 to generally expire in 2035, excluding any patent term extension, or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity or other governmental fee.

With respect to CCM, orphan drug exclusivity in the U.S.

would run seven years from marketing authorization.

We own patent applications, or exclusively license Takeda’s interest in patents and patent applications from Takeda, related to composition of matter and methods of reducing polyp burden in people living with FAP using REC-4881.

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For these reasons, we may have competition for our drug candidates.

Moreover, the time required for the development, testing and regulatory review of our candidate products may shorten the length of effective patent protection following commercialization.

Moreover, the time required for the development, testing and regulatory review of our candidate products may shorten the length of effective patent protection

following commercialization.

For this and other risks related to our proprietary technology, inventions, improvements, platforms and drug candidates, please see the section titled “Risk Factors—Risks Related to Our Intellectual Property.”

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Government Regulation

Government authorities in the United States at the federal, state and local level and in other countries regulate, among other things, the research, development, testing, manufacture, quality control, approval, labeling, packaging, storage, record-keeping, promotion, advertising, distribution, post-approval monitoring and reporting, marketing and export and import of drug and

biological products.

Generally, before a new drug can be marketed, considerable data demonstrating its quality, safety and efficacy must be obtained, organized into a format specific for each regulatory authority, submitted for review and approved by the relevant regulatory authority.

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As a result, submission of an IND may not result in the FDA allowing clinical trials, which are generally required for FDA approval of an NDA, to commence.

separate submission to an existing IND must also be made for each successive clinical trial conducted during product development along with any subsequent changes to the investigational plan.

A separate submission to an existing IND must also be made for each successive clinical trial conducted during product development along with any subsequent changes to the investigational plan.

Some long-term nonclinical testing, such as animal tests of reproductive adverse events and carcinogenicity, may continue after the IND is submitted.

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• Phase 1 clinical trials generally involve a small number of healthy volunteers or disease-affected patients who are initially exposed to a single dose and then multiple doses of the drug candidate.

The primary purpose of these clinical trials is to assess the metabolism, pharmacologic action, tolerability and safety of the drug, the side effects associated with increasing doses, and if possible to gain early evidence on effectiveness.

The primary purpose of these clinical

trials is to assess the metabolism, pharmacologic action, tolerability and safety of the drug, the side effects associated with increasing doses, and if possible to gain early evidence on effectiveness.

• Phase 2 clinical trials involve studies in disease-affected patients to determine the dose and dosing schedule required to produce the desired benefits.

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Concurrent with clinical trials, companies usually complete additional animal safety studies and also must develop additional information about the chemistry and physical characteristics of the drug as well as finalize a process for manufacturing the product in commercial quantities in accordance with cGMP requirements.

The manufacturing process, as performed by the

manufacturing facility, must be capable of consistently producing quality batches of our drug candidates.

The manufacturing process, as performed by the manufacturing facility, must be capable of consistently producing quality batches of our drug candidates.

Additionally, appropriate packaging must be selected and tested, and stability studies must be conducted to demonstrate that our drug candidates do not undergo unacceptable deterioration over their labeled shelf life.

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The FDA must make a decision on accepting an NDA for filing within 60 days of receipt.

Once the submission is accepted for filing, the FDA begins an in-depth review of the NDA.

submission is accepted for filing, the FDA begins an in-depth review of the NDA.

Under the goals and policies agreed to by the FDA under PDUFA, the FDA has ten months, from the filing date, in which to complete its initial review of a new molecular-entity NDA and respond to the applicant, and six months from the filing date of a new molecular-entity NDA designated for priority review.

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Data obtained from clinical trials are not always conclusive and the FDA may interpret data differently than we interpret the same data.

Further, FDA’s “real-time” release of newly issued Complete Response Letters associated with withdrawn or abandoned applications, if applicable to any of our product candidates, can materially impact our business and competitive advantage.

Under the Pediatric Research Equity Act, or PREA, NDAs or supplements to NDAs must contain data to assess the safety and effectiveness of the drug for the claimed indications in all relevant pediatric subpopulations and to support dosing and administration for each pediatric subpopulation for which the drug is safe and effective.

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However, competitors may receive approval of either a different product for the same indication or the same product for a different indication but that could be used off-label in the orphan indication.

Orphan drug exclusivity also could block the approval of one of our products for seven years if a competitor obtains approval before we do for the same product, as defined by the FDA, for the same indication we are seeking approval, or if a drug candidate is determined to be contained within the scope of the competitor’s product for the same indication.

seeking approval, or if a drug candidate is determined to be contained within the scope of the competitor’s product for the same indication.

If one of our products designated as an orphan drug receives marketing approval for an indication broader than that which is designated, it may not be entitled to orphan drug exclusivity.

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Prescription drug promotional materials must be submitted to the FDA in conjunction with their first use.

Further, if there are

any modifications to the drug, including changes in indications, labeling, or manufacturing processes or facilities, the applicant may be required to submit and obtain FDA approval of a new NDA or NDA supplement, which may require the development of additional data or preclinical studies and clinical trials.

Further, if there are any modifications to the drug, including changes in indications, labeling, or manufacturing processes or facilities, the applicant may be required to submit and obtain FDA approval of a new NDA or NDA supplement, which may require the development of additional data or preclinical studies and clinical trials.

The FDA may also place other conditions on approvals including the requirement for REMS, to assure the safe use of the product.

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Manufacturers and other entities involved in the manufacture and distribution of approved drugs are required to register their establishments with the FDA and certain state agencies, and are subject to periodic unannounced inspections by the FDA and certain state agencies for compliance with cGMP requirements and other laws.

Accordingly, manufacturers must continue to expend time, money and effort in the area of production and quality control to maintain cGMP compliance.

Accordingly, manufacturers must continue to

expend time, money and effort in the area of production and quality control to maintain cGMP compliance.

The discovery of violative conditions, including failure to conform to cGMP regulations, could result in enforcement actions, and the discovery of problems with a product after approval may result in restrictions on a product, its manufacturer or the NDA holder, including recalls.

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According to FDA guidance, an unapproved or uncleared companion diagnostic device used to make treatment decisions in clinical trials of a drug generally will be considered an investigational medical device unless it is employed for an intended use for which the device is already approved or cleared.

If used to make critical treatment decisions, such as patient selection, the diagnostic device generally will be considered a significant risk device under the FDA’s Investigational Device Exemption, or IDE, regulations.

The sponsor of the diagnostic device will be required to comply with the IDE regulations for clinical studies involving the investigational diagnostic device.

If used to make critical treatment decisions, such as patient selection, the diagnostic device generally will likely be considered a significant-risk device, which requires the sponsor to obtain an Investigational Device Exemption, or IDE, from FDA before commencing any testing in humans.

The sponsor of a significant-risk diagnostic device will be required to comply with the IDE regulations for clinical studies involving the investigational diagnostic device.

According to the guidance, if a diagnostic device and a drug are to be studied together to support their respective approvals, both products can be studied in the same clinical trial, if the trial meets both the requirements of the IDE regulations and the IND regulations.

The guidance provides that depending on the details of the clinical trial protocol, the investigational product(s), and subjects involved, a sponsor may seek to submit an IDE alone (e.g., if the drug has already been approved by FDA and is used consistent with its approved labeling), or both an IND and an IDE.

The guidance provides that depending on the details of the clinical trial protocol, the investigational product(s), and subjects involved, a sponsor may seek to submit an IDE alone (e.g.

if the drug has already been approved by FDA and is used consistent with its approved labeling), or both an IND and an IDE.

Pursuing FDA approval/clearance of an in vitro companion diagnostic would require either a pre-market notification, also called 510(k) clearance, or a pre-market approval, or PMA, or a de novo classification for that diagnostic.

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In particular, for a diagnostic, the applicant must demonstrate that the diagnostic produces reproducible results.

As part of the PMA review, the FDA will typically inspect the manufacturer’s facilities for compliance with the Quality System Regulation, or QSR, which imposes extensive testing, control, documentation and other quality assurance and GMP requirements.

As part of the PMA review, the FDA will typically inspect the manufacturer’s facilities for compliance with the Quality Management System Regulation, or QSMR, which went into effect in February 2026, replacing the former Quality System Regulation.

The QSMR imposes extensive testing, control, documentation and other quality assurance and GMP requirements.

After a device is placed on the market, it remains subject to significant regulatory requirements.

Among other requirements, medical devices may be marketed only for the uses and indications for which they are cleared or approved, device manufacturers must establish registration and device listings with the FDA and a medical device manufacturer’s manufacturing processes and those of its suppliers are required to comply with the applicable portions of the Quality System Regulation, or QSR, which cover the methods and documentation of the design, testing, production, processes, controls, quality assurance, labeling, packaging and shipping of medical devices.

Among other requirements, medical devices may be marketed only for the uses and indications for which they are cleared or approved, device manufacturers must establish registration and device listings with the FDA and a medical device manufacturer’s manufacturing processes and those of its suppliers are required to comply with the applicable portions of the QSMR, which cover the methods and documentation of the design, testing, production, processes, controls, quality assurance, labeling, packaging and shipping of medical devices.

Domestic facility records and manufacturing processes are subject to periodic unscheduled inspections by the FDA and the FDA also may inspect foreign facilities that export products to the U.S.

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Moreover, the ACA (as defined below) provides that the government may assert that a claim including items or services resulting from a violation of the federal Anti-Kickback Statute constitutes a false or fraudulent claim for purposes of the civil False Claims Act;

• The federal criminal False Claims Act and Civil Monetary Penalties Laws, and the civil False Claims Act that can be enforced by private citizens through civil whistleblower or qui tam actions, prohibit individuals or entities from, among other things, knowingly presenting, or causing to be presented, to the federal government, claims for payment that are false or fraudulent or making a false statement to avoid, decrease or conceal an obligation to pay money to the federal government and/or impose exclusions from federal health care programs and/or penalties for parties who engage in such prohibited conduct;

false or fraudulent or making a false statement to avoid, decrease or conceal an obligation to pay money to the federal government and/or impose exclusions from federal health care programs and/or penalties for parties who engage in such prohibited conduct;

• The Federal Health Insurance Portability and Accountability Act of 1996, or HIPAA, prohibits, among other things, executing or attempting to execute a scheme to defraud any healthcare benefit program or making false statements relating to healthcare matters;

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• the FD&C Act, which prohibits, among other things, the adulteration or misbranding of drugs, biologics and medical devices;

• The federal Physician Payments Sunshine Act requires applicable manufacturers of covered drugs, devices, biologics and medical supplies for which payment is available under Medicare, Medicaid or the Children’s Health Insurance Program, with specific exceptions, to annually report to Centers for Medicare & Medicaid Services, or CMS, information regarding certain payments and other transfers of value to physicians and teaching hospitals as well as information regarding ownership and investment interests held by physicians and their immediate family members;

• The federal Physician Payments Sunshine Act requires applicable manufacturers of covered drugs, devices, biologics and medical supplies for which payment is available under Medicare, Medicaid or the Children’s Health Insurance Program, with specific exceptions, to annually report to Centers for Medicare & Medicaid Services, or CMS, information regarding certain payments and other transfers of value to physicians, certain non-physician healthcare professionals, and teaching hospitals as well as information regarding ownership and investment interests held by physicians and their immediate family members;

• Analogous state and foreign laws and regulations, such as state anti-kickback and false claims laws which may apply to sales or marketing arrangements and claims involving healthcare items or services reimbursed by non-governmental third-party payors, including private insurers, state laws that require biotechnology companies to comply with the biotechnology industry’s voluntary compliance guidelines and the relevant compliance guidance promulgated by the federal government;

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Only one patent applicable to an approved drug, a method for using it, or a method of manufacturing it, is eligible for the extension and the application for the extension must be submitted prior to the expiration of the patent.

The USPTO, in consultation with the FDA, reviews and approves the application

for any patent term extension or restoration.

The USPTO, in consultation with the FDA, reviews and approves the application for any patent term extension or restoration.

In the future, if and when our products receive FDA approval, we may apply for restoration of patent term for our currently owned or licensed patents covering products eligible for patent term extension to add patent life beyond its current expiration date, depending on the expected length of the clinical trials and other factors involved in the filing of the relevant NDA.

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Under the current regime all suspected unexpected serious adverse reactions to the investigated drug that occur during the clinical trial have to be reported to the NCA and ECs of the Member State where they occurred.

The EU clinical trials legislation currently is undergoing a transition process mainly aimed at harmonizing and streamlining clinical-trial authorization, simplifying adverse-event reporting procedures, improving the supervision of clinical trials and increasing their transparency.

Recently enacted Clinical Trials Regulation EU No 536/2014 ensures that the rules for conducting clinical trials in the EU will be identical.

In the meantime, Clinical Trials Directive 2001/20/EC continues to govern all clinical trials performed in the EU.

The Clinical Trials Regulation EU No 536/2014 repealed the Clinical Trials Directive No.

2001/20/EC and harmonizes the processes for assessment and supervision of clinical trials throughout the European Union.

From January 31, 2023, all initial clinical trial applications in the European Union must be submitted via the Clinical Trials Information System (CTIS), which provides a single-entry point for sponsors and regulators of clinical trials for the submission and assessment of clinical trial data.

European Union Drug Review and Approval

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Under the Decentralized Procedure an identical dossier is submitted to the competent authorities of each of the Member States in which the MA is sought, one of which is selected by the applicant as the Reference Member State, or RMS.

The competent authority of the RMS prepares a draft assessment report, a

draft summary of the product characteristics, or SOPC, and a draft of the labeling and package leaflet, which are sent to the other Member States (referred to as the Member States Concerned) for their approval.

If the Member States Concerned raise no objections, based on a potential serious risk to public health, to the assessment, SOPC, labeling or packaging proposed by the RMS, the product is subsequently granted a national MA in all the Member States (i.e., in the RMS and the Member States Concerned).

The competent authority of the RMS prepares a draft assessment report, a draft summary of the product characteristics, or SOPC, and a draft of the labeling and package leaflet, which are sent to the other Member States (referred to as the Member States Concerned) for their approval.

in the RMS and the Member States Concerned).

Under the above described procedures, before granting the MA, EMA or the competent authorities of the Member States of the EEA make an assessment of the risk-benefit balance of the product on the basis of scientific criteria concerning its quality, safety and efficacy.

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Department of Health and Human Services, or HHS, Secretary as a condition for states to receive federal matching funds for the manufacturer’s outpatient drugs furnished to Medicaid patients.

The ACA made several changes to the Medicaid Drug Rebate Program, including increasing pharmaceutical manufacturers’ rebate liability by raising the minimum basic Medicaid rebate on most branded prescription drugs from 15.1% of average manufacturer price, or AMP, to 23.1% of AMP and adding a rebate calculation for “line extensions” (i.e., new formulations, such as extended release formulations) of solid oral dosage forms of branded products, as well as potentially impacting their rebate liability by modifying the statutory definition of AMP.

new formulations, such as extended release formulations) of solid oral dosage forms of branded products, as well as potentially impacting their rebate liability by modifying the statutory definition of AMP.

The ACA also expanded the universe of Medicaid utilization subject to drug rebates by requiring pharmaceutical manufacturers to pay rebates on Medicaid managed care utilization and by enlarging the population potentially eligible for Medicaid drug benefits.

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While Congress has not passed comprehensive repeal legislation, two bills affecting the implementation of certain taxes under the ACA have passed.

On November 20, 2020, the HHS Office of Inspector General (“OIG”) issued a final rule eliminating the federal Anti-Kickback Statute safe harbors for rebates paid by manufacturers to Medicare Part D plan sponsors, Medicaid managed care organizations, and those entities’ pharmacy benefit managers, the purpose of which is to further reduce the cost of drug products to consumers.

OIG created two safe harbors for certain point-of-sale reductions in price on prescription pharmaceutical products and certain pharmacy benefit manager service fees.

On December 2, 2020, OIG and CMS each issued a final rule that set forth modifications to the federal Anti-Kickback Statute, Civil Monetary Penalties Law and Physician Self-Referral Law (or the Stark Law) (respectively) regulations to remove regulatory barriers to value-based care arrangements.

CMS’s final rule also clarifies and updates certain long-standing terms that appear throughout the Stark Law regulations.

Other legislative changes have been proposed and adopted in the United States since the ACA was enacted.

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Additionally, there has been heightened governmental scrutiny recently over the manner in which drug manufacturers set prices for their marketed products, which has resulted in several Congressional inquiries and proposed and enacted federal and state legislation designed to, among other things, bring more transparency to product pricing, review the relationship between pricing and manufacturer patient programs and reform government program reimbursement methodologies for drug products.

For example, the federal Inflation Reduction Act, signed into law on August 16, 2022, contains multiple provisions that could have an adverse effect on our ability to generate revenue, attain profitability, or commercialize our drug candidates if approved, as the statute includes provisions intended to reduce the cost of prescription drugs under Medicare.

In addition to the direct impact of the IRA on federal drug reimbursement, the statute may also lead to similar reductions in payments from private payers.

Various members of the current U.S.

Congress have indicated that lowering drug prices continues to be a legislative and political priority, and some have introduced other proposals aimed at drug pricing.

In August 2022, Congress passed the Inflation Reduction Act of 2022 (IRA), which includes prescription drug provisions that have significant implications for the pharmaceutical industry and Medicare beneficiaries, including allowing the federal government to negotiate a maximum fair price for certain high-priced single source Medicare drugs, imposing penalties and excise tax for manufacturers that fail to comply with the drug price negotiation requirements, requiring inflation rebates for all Medicare Part B and Part D drugs, with limited exceptions, if their drug prices increase faster than inflation, and redesigning Medicare Part D to reduce out-of-pocket prescription drug costs for beneficiaries, among other changes.

Various stakeholders, including pharmaceutical companies and the Pharmaceutical Research and Manufacturers of America, have initiated lawsuits against the federal government asserting that the price negotiation provisions of the IRA are unconstitutional.

Further, the current administration has issued executive orders focused on decreasing prescription drug prices, including directing the Secretary of HHS to establish a mechanism through which American patients can buy drugs directly from manufacturers who sell at a most-favored-nation price and directing the U.S.

Trade Representative and Secretary of Commerce to take action to ensure foreign countries are not engaged in practices that purposefully and unfairly undercut market prices and drive price hikes in the U.S.

In November 2025, CMS announced a voluntary initiative called the GENEROUS Model (GENErating cost Reductions for U.S.

Medicaid Model) to introduce the option of most-favored-nation pricing to the Medicaid program, whereby a drug manufacturer may voluntarily offer supplemental rebates to participating state Medicaid programs for a manufacturer’s covered outpatient drugs.

Government agreements with pharmaceutical companies and other measures that use most-favored-nation pricing targets for prescription drugs or that increase generic and biosimilar drug entry sooner than expected can have a material adverse effect on our industry, ability to set adequate pricing for new drugs to recover R&D costs, ability to attract potential investors and potential buyers in the future, or the pricing of our approved product in the U.S.

and in foreign countries.

The impact of these legislative, executive, and administrative actions and any future healthcare measures and agency rules implemented by the current administration on us and the pharmaceutical industry as a whole is unclear.

Similarly, at the state level, legislatures have increasingly passed legislation and implemented regulations designed to control pharmaceutical and biological product pricing, including price or patient reimbursement constraints, discounts, restrictions on certain product access and marketing cost disclosure and transparency measures, and, in some cases, designed to encourage importation from other countries and bulk purchasing.

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Compared sentence by sentence after normalising whitespace, quotation marks, case and digits, so re-formatting and restated figures do not read as changed language. Wording changes appear as one removal and one addition. The current filing and the prior one are authoritative.

What changed 10-K

Item 1. Business