Absci Corp 10-K

Item 1. Business Our Mission Our mission is to change the world, one protein at a time. We founded Absci with the goal of creating better medicines and helping them reach patients sooner. We recognized the extraordinary medical and economic potential of protein-based drugs (biologics), but also the significant challenges the biopharmaceutical industry faces to both discover novel biologics and generate cell lines to manufacture them at commercial scale. We looked at the end game – getting better medicines to patients, faster — and asked: how? We built our technology to be that how. We believe we are replacing the fragmented steps and inefficiencies of the conventional biologic drug discovery and cell line development processes with our fully integrated, end-to-end platform designed to create new and better biologics and accelerate their advancement into clinical trials and ultimately into the marketplace where they can serve patients. Combining innovative approaches, including synthetic biology, high-throughput single-cell screening, and deep learning artificial intelligence (AI), we seek to identify optimal drug candidates by exploring expansive protein sequence solution spaces — including considering sequences that nature's evolutionary trajectory has yet to propose. We believe our platform allows us to expand biological possibilities and generate proteins intractable to produce with other technologies to ensure the best drug candidates have the opportunity to become therapeutic realities for patients. Our goal is to enable the creation of better medicines by Translating Ideas into Drugs. We believe commercial applications for novel proteins extend far beyond the realm of therapeutics and into other industries including materials science, industrial chemicals, cosmetics, synthetic foods, and agriculture. Today, we are focused on bringing value to the biopharmaceutical industry and generating better medicines. Our near term vision is to enable discovery of novel, targeted biologic drug candidates, and the cell lines to manufacture them, with the click of a button. Looking ahead, we envision a future in which Absci will be the universal engine creating protein-based solutions to advance the bio-based economy, one protein at a time. Overview We are a drug and target discovery company harnessing deep learning and synthetic biology to expand the therapeutic potential of proteins. We built our Integrated Drug Creation Platform to identify novel drug targets, discover optimal biotherapeutic candidates, and generate the cell lines to manufacture them in a single efficient process. We believe our approach delivers disruptive efficiency, but more importantly enables our partners to create novel and human/AI-designed new-to-nature biologics (next-generation biologics). While next-generation biologics have exciting medical potential and are a rapidly growing field of drug development, because their protein architectures (scaffolds or modalities) are biologically foreign, they present challenges for conventional biologic discovery and cell line development methods. These methods typically involve a linear series of steps to screen and select desired molecular parts and reformat them into their final protein scaffold, and subsequent laborious and often unsuccessful generation of a suitable manufacturing cell line. We are transforming the biologic discovery and cell line development process by rapidly screening up to billions of drug candidates in the desired final protein scaffold that goes into patients and in the scalable manufacturing cell line that scales up for clinical and commercial manufacturing. We couple our powerful deep learning AI models, built to understand and predict determinants of protein function, with our proprietary synthetic biology capabilities, which include high-throughput single cell assays that can evaluate billions of drug sequence variants, each within its production cell line, for target binding affinity, protein quality, and production level (titer). This combination of in silico modeling with wet lab testing allow us to generate immense real-world datasets that we harness to train and refine our deep learning models. These models guide our protein and cell line designs and enable in silico optimization of multiple attributes. In addition, with our “Totient Target” technology, we use machine learning computational methods to evaluate patient tissue samples and, without biological bias, identify disease-relevant fully human antibodies and their disease- and tissue-specific molecular targets. In addition to the direct utility of these antibodies and targets as drug discovery assets, these data comprising antibody-epitope recognition elements expand our AI models’ training sets and may improve predictive capabilities for future discovery campaigns. The virtuous cycle, or flywheel effect, enabled by the cycling of our AI predictions, data generation, and AI training, as illustrated below, is what we believe brings us closer to our vision of fully in silico biologic drug 4 Table of Contents discovery and cell line generation with every turn. On the way to the realization of that vision, we believe our unique Integrated Drug Creation approach has the potential to significantly accelerate preclinical development timelines and expand therapeutic possibilities for the biopharmaceutical industry. Our goal is to become the partner of choice for biologic drug discovery and cell line development. As a technology development company, we generate biologic drug candidates and production cell lines for our partners to develop. Our business model is to establish partnerships with biopharmaceutical companies and use our platform for rapid creation of next-generation biologic drug candidates and production cell lines. We classify our applications into two key categories: Discovery and Cell Line Development (CLD). We define “Discovery” as any projects for which we are evaluating variants of the protein-of-interest, which includes generation of the production cell line, and we define CLD as a program for which the production cell line alone is the goal of the partnership. Our partners are responsible for preclinical and clinical testing of biologics generated using our platform. We expect our partnerships to provide us with the opportunity to participate in the future success of the biologics generated utilizing our platform, through milestone payments as well as royalties on sales by our partners of any approved products. We aim to assemble economic interests in a diversified portfolio of partners’ next-generation biologic drug candidates across multiple indications. As of December 31, 2021, we had drug candidates in twelve Active Programs (across eight current partners’ preclinical or clinical pipelines) for which we have negotiated, or expect to negotiate upon completion of certain technology development activities, license agreements with potential downstream milestone payments and royalties. Eight of these Active Programs are focused on developing production cell lines for drug candidates that our partners (Merck & Co., Inc., Xyphos Biotechnology, an Astellas Company (Astellas), Alpha Cancer Technologies, Inc., PhaseBio Pharmaceuticals, Inc., and other undisclosed biotechnology companies) are developing (five preclinical, one Phase 1, one Phase 3, and one animal health). The remaining four Active Programs comprise Discovery applications, including three Discovery programs through our agreement with EQRx and one lead optimization program with Astellas. We define “Active Programs” as programs that are subject to ongoing technology development activities intended to determine if the program can be pursued by our partner for future clinical development, as well as any program for which our partner obtains and maintains a license to our technology to advance the program after completion of the technology development phase. There is no assurance, however, that our partners will advance any drug candidates that are currently the subject of Active Programs into further preclinical or clinical development or that our partners will elect to license our technologies upon completion of the technology development phase in a timely manner, or at all. 5 Table of Contents Over the last two decades, biologics have emerged as one of the fastest growing class of drugs, with the Evaluate Pharma data reflecting that they account for approximately $254 billion in sales worldwide and represent 12 of the top 20 selling therapeutics in 2020. The majority of recently-approved biologic drugs are monoclonal antibodies, but i nterest and investment are increasingly shifting towards the development of next-generation biologics, which we estimate, based on our analysis of the Evaluate Pharma data, account for 32% of biologics in Phase 1 clinical development today. Despite this increase, we believe that the biopharmaceutical industry remains constrained in pursuing these new biologic modalities because it lacks suitable approaches to efficiently create next-generation biologics. Existing solutions are largely limited to operating within the scope of what nature has already created. They are not adaptable to the full range of possible human-designed scaffolds or to the incorporation of non-standard amino acids (nsAAs) into the protein-of-interest. They do not effectively leverage AI either to derive and apply non-obvious insights across the discovery and manufacturing process development value chain, or to explore potential drug sequences and structures that lie beyond nature’s boundaries. Our Integrated Drug Creation Platform enables novel target identification, and parallel discovery of next-generation biologics and with optimized production cell lines by uniquely incorporating engineered biodiversity, proprietary high-throughput single cell assays, and deep learning AI models. We use our platform to predict, identify, design, construct, screen, select and scale production of biologic drug candidates for our partners, and we learn from the data we generate. Our designs are AI-informed and our technology platform is scaffold-agnostic. Our AI leverages deep learning models that are trained on our growing datasets. Our datasets delineate detailed determinants of protein function and manufacturability across billions of single-cell experiments. Our single-cell experiments are performed in our patented production cell lines. The foundational technologies that power our platform, and generate and harness the Absci proprietary data, are: • SynBio Platform: Our SynBio Platform is our proprietary E. coli -based system for high-throughput evaluation of billions of protein sequence and cell line design variants in parallel. With our SynBio Platform technologies we generate novel drug candidates, manufacturing cell lines, and proprietary data that we use to train our AI models. Our SynBio Platform comprises the four core technology elements described below: ◦ SoluPro & Bionic SoluPro: SoluPro is our patented bioproduction system based on bioengineered E. coli . We further engineered our Bionic SoluPro to facilitate site-specific incorporation of nsAAs into what we call Bionic Proteins. We believe our SoluPro cell lines unlock evolutionary opportunities by expanding the biological repertoire of proteins that can be produced to include new-to-nature proteins such as next-generation biologics. ◦ Custom Scaffold Libraries: We can design and generate up to billions of drug candidate sequence variants for each Discovery program. Our platform creates libraries in any scaffold our partner specifies, whether natural, pre-existing, or newly invented. These drug candidate sequence libraries are custom because they are specifically generated for each program and scaffold. We can also specify nsAA incorporation sites as we design these libraries. ◦ Folding & Expression Solutions: We curate a diverse collection of folding and expression solutions, which are genetic tools that we use to customize SoluPro and optimize production of the desired protein. We create up to billions of different cell lines and measure each cell’s performance to find the solutions that work best for the protein-of-interest. ◦ Breakthrough Assays: Our proprietary Activity-specific Cell Enrichment (ACE) and High-Throughput Proximity Binding (HiPrBind) Assays allow us to evaluate and sort the millions to billions of drug sequences and cell line variants we generate. Tailored for each of our programs, our high-throughput assays can rank and sort billions of cells based on desired parameters such as target affinity, protein quality, and titer. We capture datasets that have the potential to provide us with highly relevant insights about protein function and manufacturability in our system and beyond. • Denovium Engine: Our “Denovium Engine” is an AI technology that includes deep learning computational models of protein function. The Denovium Engine models, trained on our high-quality data that are particularly relevant to our system, generate non-obvious predictions about the impact 6 Table of Contents of amino acid sequence and cell line engineering parameters on a given protein’s function and manufacturability. In the future, we expect to use AI to inform the identification of drug target, selection of epitope, and choice of drug scaffold, define the scope of sequence variants to generate, and design the cell line attributes. We believe this technology may eventually enable us to optimize complex solution space fully in silico without the need to physically screen billions of options. • Totient Target Technology: Our computational antibody and target discovery technology is a bioinformatics and machine learning-based platform that allows us to computationally reconstruct sequences of human antibodies and other disease-specific proteins from bulk RNA sequencing (RNA-Seq) data. We can retrospectively select samples from patients who experienced distinct immune responses and assemble sequences of the most highly expressed monoclonal antibodies present in the tissue of interest. We use these antibodies to identify corresponding target proteins (antigens), and thus we uncover both novel and previously recognized immunogenic targets. We are building a library of tissue- and disease-specific target antigens paired with unique human derived antibodies. Our approach is extensible to identifying other disease state-specific macromolecules relevant to therapeutic responses, such as T-cell receptors. These foundational technologies work together as our Integrated Drug Creation Platform. The diagram below depicts the core activities we accomplish on our platform. Our process using our Integrated Drug Creation Platform involves the following steps: • Predict: We expect to use our Denovium Engine AI models to generate non-obvious predictions about what are likely to be optimal drug candidate sequences and cell line designs for any protein-of-interest. The AI combines the collective learnings available in public databases with our own experimental data specifically documenting protein functionality and manufacturability factors relevant to our system. Importantly, our Denovium Engine considers sequences and solutions that it has not seen before, and it may predict entirely new-to-nature protein scaffold elements and sequence motifs or design new biologic modalities. In addition, with data we produce through computational antibody and target discovery technology, we intend to train our Denovium Engine to predict likely drug targets from antibody or other binding protein sequences. • Identify: Starting with disease tissue samples or bulk RNA sequencing data of interest to our partners, we expect to apply our newly acquired computational antibody and target discovery technology to reconstruct sequences of human monoclonal antibodies that are prevalent in the tissue. With our high-throughput expression system and assay technologies, we believe we can rapidly de- 7 Table of Contents orphan the antibodies, using them as probes to identify their corresponding antigens. Not only are the antigens, whether known or novel, of potential interest as therapeutic targets, but also the fully human antibody sequences themselves may serve as starting points for lead drug candidate design. • Design: Based on the program goals, we design custom libraries of protein-of-interest variants in the desired scaffold architecture and specify any desired nsAA placements. Using our Denovium Engine models, we may recommend modifications to the scaffold architecture, as well as define the scope of protein variation to evaluate options beyond sequences that exist in nature. In addition, we also incorporate designs based on folding and expression solutions predicted as relevant by our Denovium Engine models. This entire step is accomplished in silico . • Construct: Using synthetic biology approaches, we construct up to billions of genetically distinct SoluPro or Bionic SoluPro cells to evaluate. Each cell contains the instructions to make one version of the protein-of-interest, as well as a different assortment of folding and expression solutions. • Screen: Our proprietary high-throughput ACE Assay allows us to evaluate and sort up to billions of cells. We collect subsets of the population of cells that express the best versions of the protein-of-interest (hits), based on target binding, protein quality, and titer. We also collect large datasets on the genetic determinants of protein function and manufacturability in our system that we use to train our Denovium Engine models. • Select: With our HiPrBind Assay, using automated multiplexed plate-based methods, we grow micro-batches of each of the thousands of hits from the ACE Assay and perform quantitative characterization of protein function, quality, and titer. We also perform high-throughput biophysical characterization to collect additional data on relevant biophysical attributes that impact developability. We are able to select the best several candidates (leads) in their putative production cell lines for further analytics, as well as collect further data insights to enhance our Denovium Engine models. • Scale: We optimize fermentation conditions for the selected lead strain(s) to demonstrate desired productivity, quality, and scalability. We perform comprehensive analytics on the lead drug candidate(s) for evaluation and technology transfer to our partners. • Learn: Throughout our process, we generate large and complex datasets specifying determinants of protein function and manufacturability. We use these data to train our Denovium Engine to enable its models to make increasingly refined predictions for target identification, drug scaffold sequence variation, and cell line designs. Our goal is to train the deep learning models with enough data to be able to input a sequence of a new drug target, or even bulk mRNA from a patient, and have the model output a unique, optimal drug candidate sequence and cell line architecture that we construct and confirm: a process that we refer to as de novo biologic drug creation in silico. Because of the flexibility of our platform, we can partner with biopharmaceutical companies to address specific challenges, or we can open up opportunities to create new modalities and generate lead drug candidates that previously had not been possible. Programs we undertake vary across the range of our capabilities, from novel target identification and de novo drug discovery in bespoke scaffolds incorporating nsAAs to development of optimized production systems for existing lead drug candidates. Our goal is to demonstrate the value of our fully integrated approach and expand our work with an increasing number of partners on broad multi-molecule discovery partnerships. We believe we offer a compelling value proposition to our partners by: • Accelerating timelines from idea to drug candidate; • Enabling the creation of new biologic modalities; • Improving the production capability of next-generation biologics; • Designing better drug candidates; and • Raising biologics production yields and lowering manufacturing costs. Our initial focus is on enabling the biopharmaceutical industry by transitioning biologic drug discovery and cell line development processes onto our Integrated Drug Creation Platform and providing access to an 8 Table of Contents expanded solution space for drug creation. Over time we envision deploying our platform into other industries as we live by our mission of changing the world, one protein at a time. Impact of COVID-19 We have been dedicated to prioritizing the health and safety of our employees, contractors, vendors and business partners during the COVID-19 pandemic. We continue to monitor federal, state and local laws and regulations to prevent the spread of COVID-19 at our workplace. We are responsive to updated guidance and work directly with local health authorities, as appropriate. We have limited business travel to that which is critical to continuation of our business operations, and encouraged employees to work from home wherever possible. We have implemented comprehensive COVID-19 policies and communicate closely with our employees to ensure such policies are followed. As a result of the ongoing COVID-19 pandemic, we have experienced minor delays and disruptions to our supply chain. For further discussion of the risks relating to our third-party suppliers, see the section titled “Risk Factors-Risks related to our operations-We rely on a limited number of suppliers or, in many cases, single suppliers, for laboratory equipment and materials and may not be able to find replacements or transition to alternative suppliers on a timely basis, or at all." Strategy We believe we represent a new breed of biotechnology company, integrating powerful artificial intelligence with new synthetic biology technologies to create next-generation biologics. We aim to become a partner of choice to both large pharmaceutical companies and biotechnology companies to enable and empower discovery and cell line development capabilities for biologics. We intend to use our Integrated Drug Creation Platform to empower innovation by identifying new targets, creating new modalities, discovering next-generation biologics, driving efficiencies, broadening pipelines, and accelerating preclinical timelines. Our strategy to accomplish this is as follows: • Enable the discovery and development of next-generation biologics and new modalities through our proprietary platform. Our ability to design, construct and rapidly screen large populations of genetically distinct cells enables us to evaluate billions of unique protein variants and increase the probability of finding the most promising biologic drug candidate. We design and optimize new-to-nature modalities with insights from our Denovium Engine models. We also harness the power of nature, using synthetic biology approaches with our E. coli SoluPro strains to produce complex proteins and new modalities. Unlike other biologic drug discovery methods, we evaluate the variants of these desired proteins in the fully-constructed scaffold to enable creation of next-generation biologics while optimizing for target affinity as well as high-titer expression and scalable manufacturability from the beginning of the discovery process. We believe that our platform will empower our partners to bring new and better drugs to market. • Accelerate biologic drug discovery and cell line development by unifying these processes as “Integrated Drug Creation.” Our platform integrates multiple steps across the biologic drug discovery and cell line development process and our foundational technologies that power our Integrated Drug Creation Platform improve efficiencies at each step. Our approach also has the flexibility to address challenges at specific points in the biologic drug discovery and cell line development process and enable our partners to pursue more efficient biologic drug discovery across expanded solution spaces. By accessing our platform, infrastructure and expertise, our partners have the potential to eliminate extended timelines, reduce costs associated with setting up biologic drug discovery applications and cell line process development, and advance their preclinical programs more efficiently. • Drive rapid adoption by becoming a partner of choice for large pharmaceutical companies and biotechnology companies. Many large pharmaceutical companies and biotechnology companies are seeking a partner with technologies, resources and teams to enable next-generation biologic drug discovery and execute on early stage preclinical programs. We strive to form strong partnerships across our target partner base and to drive rapid market adoption through increased business development activities designed to gain new partners and expand our existing partnerships to cover additional programs. We believe our innovative approach and ability to create better biologics faster, along with the scalability of our platform, will enable us to build a diversified 9 Table of Contents portfolio of potential milestone revenues and royalty streams from a variety of next-generation biologics across multiple indications. • Advance the promise of in silico drug creation by leveraging proprietary data and AI. Our Denovium Engine AI learns with each new program we undertake. We are enhancing the predictive power of Denovium by training its deep learning models with our unique multi-dimensional data sets. With enough data and iterations, we aim to achieve in silico creation of novel drug candidates with desired pharmacologic attributes, in bespoke scaffolds, along with high titer production cell lines. With our Totient Target technology we are expanding the content of our training datasets to develop models that understand immune protein interactions and determinants of antibody-antigen specificity. Our Denovium AI technology is the link that correlates business scale with speed and precision. The more partners we have, the more data we generate, the more our Denovium Engine learns. As our Denovium Engine gets smarter, we can create new and better biologic constructs for our partners faster. • Continuously invest in our platform to push the boundaries of science and unlock the untapped power of biology. We intend to maintain our technological differentiation through investments in teams and technologies, and to continue bolstering our capabilities in areas such as bioinformatics, molecular sciences, biology and chemistry, computation, and protein engineering. We expect to grow and enhance our intellectual property portfolio to protect and secure the value of our innovations. Similar to our acquisitions of Denovium, Inc. and Totient, Inc., we believe we will continue to evaluate strategic technology acquisitions that would be additive to expand and strengthen the capabilities of our platform and deepen our expertise in biologic drug discovery and cell line development. • Maintain an entrepreneurial, founder-led, scientifically rigorous, data-driven and inclusive corporate culture. Our founder-led team lives by the mantra: “believe in the impossible.” We are disrupting the pharmaceutical industry with bold ideas and fulfilling the promise of life-saving medicines for patients by Translating Ideas into Drugs. Each of our team members brings their energy, expertise, and enthusiasm to bear as we pursue the shared mission of changing the world, one protein at a time. Industry Over the last two decades, biologics have been at the forefront of medical advances in a wide range of disease areas including oncology, immunology, infectious and metabolic disease, and many more. Biologics have emerged as one of the fastest growing class of drugs. According to publicly available data aggregated by Evaluate Pharma, the global protein-based biologics market, which we define as including monoclonal antibodies (mAbs), monoclonal antibody conjugates and recombinant products, reached approximately $254 billion in 2020 and is expected to reach $418 billion by 2026, representing a compound annual growth rate of approximately 9%. Fueled by the medical promise of protein-based drugs, the biopharmaceutical industry has continued to expand its horizons in terms of the different diseases targeted by biologic drug developers as well as the design and different modalities of biologics. The desire by drug developers to manipulate biological mechanisms to fight diseases, explore targets that have not yet been addressed, and succeed in conquering difficult-to-drug targets has led to the development of increasingly complex biologic modalities and the emergence of the field of next-generation biologics. As we define them, next-generation biologics comprise a broad class of new protein-based modalities designed by scientists rather than found in nature. They include modified antibodies such as antibody-drug conjugates and bispecific mAbs, scaffolds based on antibody parts such as Fabs, scFvs, and VHHs, hybrid fusion proteins including T-cell engagers, multivalents, cytokine derivatives, and biologics incorporating nsAAs, and any other new-to-nature protein-based drug imaginable. According to our analysis of Evaluate Pharma data, next-generation biologics currently make up approximately 32% of the Phase 1 protein-based biologics in development. Established methods for biologic drug discovery and cell line development The biologics industry has experienced significant growth and technology advancement, but the process of developing a clinical stage-ready biologic drug candidate remains complex, inefficient, and failure-prone, and is typically accomplished through an assembly of isolated technologies. Generating a clinical stage-ready 10 Table of Contents candidate includes two broad sets of technology development processes: biologic drug discovery and cell line development. Conventional Biologic Drug Discovery: Given a target, conventional methods for biologic drug discovery involve fishing for “hits” that bind the target using methods such as phage display, yeast display or immune cell screening. Unless the hits are already in the desired scaffold, they then must undergo a molecular reformatting step to incorporate the hits into the desired scaffold. It is only once assembled that these “leads” can be evaluated. This reformatting is a low throughput one-by-one process that is prone to challenges such as loss of target specificity once the hit is reformatted into the lead scaffold, or inability to make enough of the lead to even evaluate its promise as a drug candidate. The discovery process, including screening, reformatting, and lead optimization, occurs across several technologies outside of the eventual production cell lines. Conventional Cell Line Development: Biologics must be biologically synthesized in bespoke cell lines, rather than chemically synthesized like small molecule drugs. Development of cell lines suitable for manufacturing at scale is undertaken only after lead candidates have been selected using transient cell lines for expression. With conventional methods, stable manufacturing cell line development involves introducing a lead candidate into the host cell line, typically Chinese Hamster Ovary (CHO) cells, and then laboriously optimizing conditions and strain characteristics for scalable production of the new drug candidate, if possible. The limited adaptability of CHO cell lines and engineering challenges have constrained the scope of protein-based drugs that can be successfully developed. This can be particularly true for next-generation biologics, which may be impossible to produce with conventional approaches. The below diagram illustrates the general steps of established approaches for biologic drug discovery and manufacturing cell line development: Limitations of existing approaches With conventional fragmented approaches, preclinical timelines are extensive. According to a 2010 publication in Nature Reviews Drug Discovery authored by Paul and colleagues, the time from target discovery to IND was estimated at approximately 5.5 years. Moreover, the authors concluded that failure rates are high, with roughly only one in three lead drug candidates advancing to clinical testing in patients. For those drug candidates that do enter Phase 1 testing, the same publication estimated that 12% go on to receive marketing authorization, taking another eight years to do so. We believe that these long timelines and high failure rates are reflective of an industry reliant on aging systems and processes. It is our view that existing approaches are burdened by the design constraints of their technologies’ evolution, with the current processes representing the culmination of many iterations on the first technologies employed by the industry. New technologies may be tacked on to add incremental expansion of capabilities, but on the whole, the biologic drug discovery and cell line development processes remain fragmented and reliant on legacy component tools. This fragmentation of the processes discourages innovative potential, especially since the current approaches are not readily adaptable to development of next-generation biologics. We believe the industry suffers from the following challenges and limitations of existing solutions: • Current methods involve fragmented steps and a patchwork of outdated technologies; new technologies generally focus on isolated steps and do not integrate the processes. We believe drug developers primarily use legacy technologies and fragmented processes to accomplish discrete steps in either biologic drug discovery or cell line development. Moving between steps in the process and different technologies may not be seamless, introducing inefficiencies and creating 11 Table of Contents insurmountable hurdles to advancement of a promising drug candidate. While new technologies and new methods for hit identification or cell line development have been commercialized, these methods do not allow for discovery screening to be performed while the candidate is in its production cell line and therefore cannot enable discovery of a new biologic in parallel with generating its production cell line. As a result, even with updated technologies, established methods contribute to long development timelines and low probabilities of success. • Commercially available biologic drug discovery platforms are generally constrained as to the types of biologic modalities they can explore. We believe that most of the current approaches to biologic drug discovery impose technological and biological limitations as to the nature of proteins that can be evaluated. High diversity and high-throughput methods are primarily capable of identifying target specificity of small protein fragments or variants of native mammalian proteins. Consequently, newly-designed proteins in novel scaffolds generally require laborious “one by one” evaluation and/or screening by parts and then iterative assembly into the full scaffold. Similarly, conventional methods do not facilitate efficient discovery of new-to-nature proteins that incorporate nsAAs, a desirable feature for post purification chemical modifications. Constraints on the nature of screenable proteins limit the breadth of opportunities for discovery, and may result in suboptimal lead candidates, extended timelines and susceptibility to failure at different steps throughout the process. • Current approaches to biologic drug production are not readily adaptable to novel protein modalities. Proteins require biological assembly by cellular machinery. Developers of more complex biotherapeutics such as monoclonal antibodies have adapted CHO cells to be reasonably adept bioproduction hosts. However, generation of a CHO cell line to produce any new biologic is not trivial, and an adequate cell line generally takes a year or more to develop. In addition, CHO systems have limited flexibility to produce next-generation modalities; the mammalian cells are difficult to engineer and are not adapted or adaptable to make new-to-nature proteins such as those built in novel scaffolds or incorporating nsAAs. The challenge of generating high-titer manufacturing cell lines is a critical impediment to advancing many novel biologic drug candidates into and through clinical development. • Current approaches do not leverage artificial intelligence to explore beyond opportunities within nature. The scale and complexity of proteins present significant challenges for developing biotherapeutics. There are more potential protein variants than can ever be evaluated even with the highest throughput approaches. While some computational insights are being gained from experimental observations, there are few if any existing biotherapeutic drug design approaches that make impactful use of high-throughput data in combination with machine learning. We believe there is lost opportunity to train and use deep learning models to predict promising new proteins that lie outside the bounds of what already exists in nature or even what human intelligence can rationally design. The biopharmaceutical industry is still in the early days of augmenting human efforts with artificial intelligence, operating within the bounds of sequence similarities to natural precursors, even when considering functional impact. • Existing production organisms, or systems, can be inefficient and costly. The vast majority of biopharmaceutical production processes today rely on CHO cell systems. The ongoing drug product costs of operating CHO cell bioproduction processes are high due to the nature of the cells’ growth characteristics and requirements. As reported by Tripathi and Shrivastava in Frontiers in Bioengineering and Biotechnology (2019), CHO cells grow slowly and at low densities, so a single production run generally requires 10 to 14 days of growth in the bioreactor, which limits batch cycles and plant flexibility. The overall productivity of a CHO cell line producing a drug candidate at a 5 gram/liter titer may be less than half a gram per liter per day on average due to the extended growth cycle. Costly growth media and the requirement for downstream viral clearance steps also contribute to the high cost of CHO processes. As a result of these limitations, we believe the biopharmaceutical industry can benefit from a newly-designed approach that incorporates the best current technologies and AI to accomplish the goal of discovering and advancing promising new biologic drug candidates into clinical development as quickly as possible. 12 Table of Contents Our Integrated Drug Creation Platform We built our Integrated Drug Creation Platform to create next-generation biologics including those that lie beyond the scope of nature. To achieve this, we leverage synthetic biology technologies, engineered biodiversity, proprietary functional assays and data-driven deep learning computational models to discover novel disease- and tissue-specific drug targets and next-generation biologic drug candidates while generating optimized production cell lines in parallel. Our platform enables functional evaluation of billions of variants of desired proteins, including complex biologic drug candidates, with simultaneous generation of scalable production cell lines, all in a time- and cost-effective manner. We screen in the desired scaffold format and in the scalable manufacturing cell line. We believe our platform is the only commercially available solution with this capability, enabling costly and lengthy processes to be collapsed into one integrated step. We use our platform to predict, identify, design, construct, screen, select and scale production of biologic drug candidates for our partners, and learn from the data we generate. Our designs are AI-informed and our technology platform is scaffold-agnostic. Our AI leverages deep learning models that are trained on our growing datasets. Our datasets delineate detailed determinants of protein function and manufacturability across billions of single-cell experiments. Our single-cell experiments are performed in our patented production cell lines. The foundational technologies that power our platform, and generate and harness the Absci proprietary data, are: • SynBio Platform: Our SynBio Platform is our proprietary E. coli -based system for high-throughput evaluation of billions of protein sequence and cell line design variants in parallel. With our SynBio Platform technologies we generate novel drug candidates, manufacturing cell lines, and proprietary data that we use to train our AI models. It comprises the four core technology elements described below: ◦ SoluPro & Bionic SoluPro: SoluPro is our patented bioproduction system based on bioengineered E. coli. Using synthetic biology techniques, we designed SoluPro to be our chassis cell line. We believe our SoluPro unlocks evolutionary opportunities by expanding the biological repertoire of proteins that can be produced to include complex new-to-nature proteins such as next-generation biologics. We further engineered a version of SoluPro to facilitate site-specific incorporation of nsAAs into proteins for scaled production. We refer to these nsAA-containing proteins as Bionic Proteins and the SoluPro strain we use to produce them as Bionic SoluPro. ◦ Custom Scaffold Libraries: We can design and generate custom collections of drug candidate sequence variants for each Discovery program, starting with whatever scaffold our partner specifies, whether natural, pre-existing, or newly-invented, and building out up to billions of different versions to test. These libraries are specifically generated for each program and scaffold, and our AI predictions coupled with our ability to generate libraries in any given scaffold allow us to consider relevant variants that nature could not have proposed. We can also specify nsAA incorporation sites as we design these libraries. ◦ Folding & Expression Solutions: We curate a diverse collection of folding and expression solutions, which are genetic tools that we use to customize SoluPro and optimize production of the desired protein. Each protein we work on has different characteristics when it comes to manufacturability factors, and with the folding and expression solutions parts library and our synthetic biology methods, we create up to billions of different cell lines and measure each cell’s performance to find the solutions that work best for the protein-of-interest. The folding and expression solutions collectively comprise an expansive set of genetic modules and techniques we have assembled including ribosome binding site sequences, molecular chaperones, and codon-optimization conventions. ◦ Breakthrough Assays: Our proprietary ACE and HiPrBind Assays allow us to evaluate and sort the millions to billions of drug sequence and cell line variants we generate. Tailored for each of our programs, our high-throughput assays can rank and sort billions of cells based on desired parameters such as target affinity, protein quality, and titer. We are also able to capture datasets correlating protein sequence variants and folding and expression solutions with cell line characteristics. These large, highly complex datasets have the potential to provide us with highly relevant insights about protein function and manufacturability in our system and beyond. 13 Table of Contents • Denovium Engine: Our Denovium Engine is an AI technology that includes deep learning computational models of protein function. The Denovium Engine models, trained on our high-quality data that are particularly relevant to our system, generate non-obvious predictions about the impact of amino acid sequence and cell line characteristics on a given protein’s function and manufacturability. A deep learning neural network approach is well-suited to our complex datasets because the models learn what is relevant to the specific objective, without human annotation or bias. We expect the capabilities of the Denovium Engine to grow with each new set of data we generate and input. In the future, we intend to use AI to inform the identification of drug target, selection of epitope, and choice of drug scaffold, define the scope of sequence variants to generate, and design the cell line attributes. We believe this technology may eventually enable us to optimize complex solution space fully in silico without the need to physically screen billions of options. • Totient Target Technology: Our computational antibody and target discovery technology is a bioinformatics and machine learning-based platform that allows us to reconstruct sequences of antibodies and other disease-specific proteins from bulk RNA-Seq data. We can retrospectively select samples from patients who experienced distinct immune responses and assemble sequences of the most highly expressed monoclonal antibodies present in the tissue of interest. We use these antibodies to identify corresponding target proteins (antigens), and thus we uncover both novel and previously recognized immunogenic targets. We are building a library of tissue- and disease-specific target antigens paired with unique fully human antibodies. Our approach is extensible to identifying other disease state-specific macromolecules relevant to therapeutic responses, such as T-cell receptors. We perform our process using our Integrated Drug Creation Platform to predict biologically interesting variants, identify novel disease targets, design custom libraries of sequence variants, construct diverse populations of cells with these libraries and our folding and expression solutions, screen and sort these cells based on our desired criteria, select lead drug candidate/cell line combinations having the desired functionality and manufacturability qualities, optimize these leads for scaled manufacturing readiness, and learn by feeding data from our multitude of single cell experiments into our AI models to continually refine our predictions. Our process using our Integrated Drug Creation Platform includes the following steps: • Predict: We expect to use our Denovium Engine AI models to generate non-obvious predictions about what are likely to be optimal drug candidate sequences and cell line designs for any protein-of-interest. The AI combines the collective learnings available in public databases with our own experimental data specifically documenting protein functionality and manufacturability factors relevant to our system. Importantly, our Denovium Engine considers sequences and solutions that it has not seen before, and it may predict entirely new-to-nature protein scaffold elements and sequence motifs or design new biologic modalities. In addition, with data we produce through 14 Table of Contents computational antibody and target discovery technology, we intend to train our Denovium Engine to predict likely drug targets from tissue-derived antibody or other binding protein sequences. • Identify: Starting with disease tissue samples or bulk RNA-Seq data of interest to our partners, we expect to apply our newly acquired computational antibody and target discovery technology to reconstruct sequences of human monoclonal antibodies that are prevalent in the tissue. With our high-throughput expression system and assay technologies, we believe we can rapidly de-orphan the antibodies, using them as probes to identify their corresponding antigens. Not only are the antigens, whether known or novel, of potential interest as therapeutic targets, but also the fully human antibody sequences themselves may serve as starting points for lead drug candidate design. • Design: Based on the program goals we design custom libraries of protein-of-interest variants in the desired scaffold architecture and specify any desired nsAA placements. This entire step is accomplished in silico , and we incorporate predictions our Denovium Engine models have extracted from our proprietary datasets to improve our designs. We design the synthetic biology components at the DNA level, including gene(s) for the protein-of-interest that will encode the potential future drug candidates. We design custom plasmid libraries for each program we undertake. Plasmids are the carriers of the DNA for the protein-of-interest that will ultimately be delivered into the cell line. We may start with a generic DNA sequence for the desired scaffold and, using our AI predictions, define the parameters of the sequence variation to be evaluated for discovery and/or any targeted nsAA placements. Having designed the gene-of-interest sequences, we augment the computational plasmid designs with a random assortment or selected range of our synthetic biology folding and expression solutions that are included to impart characteristics to the cell lines that optimize production of the protein-of-interest. • Construct: Using synthetic biology approaches, we construct up to billions of genetically distinct SoluPro or Bionic SoluPro cells to evaluate. Each cell contains the instructions to make one version of the protein-of-interest, as well as a different assortment of folding and expression solutions. We synthesize the designed plasmid libraries and deliver them into our host organism, creating a large population of these host cells for screening. These populations of distinct plasmids modify our base SoluPro strains and generate a large population of genetically distinct cells. The population of cells is cultivated under manufacturing-relevant fermentation conditions to induce production of the protein-of-interest for screening. • Screen: We screen this large population of cells for the desired characteristics using our proprietary ACE Assay, which enables rapid identification of hits from large genetically diverse populations of cells. The ACE Assay is a binding-based assay that allows us to sort SoluPro cells based on protein-of-interest functionality (such as target affinity) as well as expression level (titer). To accomplish this, we introduce fluorescently labeled binding targets (e.g., the antigen against which we are trying to develop a drug) and use fluorescence activated cell sorting (FACS) to evaluate and sort each cell based on how brightly it fluoresces. Using proprietary methods, we correlate the fluorescent signal with the quantity, quality, and function of the protein-of-interest, and thus we utilize the ACE Assay to characterize millions or billions of independent strains and collect the desired variants based on the parameters we set. In this way we are quickly able to identify the most promising subset of cells from among millions or billions. Our ACE Assay is compatible with a diverse range of protein modalities, including next-generation biologics. We are also generating billions of data points describing sequence modifications and combinations of folding solutions contributing to protein affinity, solubility and manufacturability that we use to train our Denovium Engine deep learning model. • Select: We use our proprietary HiPrBind Assay to select the best leads from among the screened hits. For expanded clonal populations of each of the hits identified we can quantitatively evaluate and characterize functional parameters of the protein-of-interest such as target binding affinity, titer, and product quality. Our proprietary techniques allow us to discriminate between full length properly folded protein and any other improperly folded or incomplete product-related impurities, in a fully quantitative manner, and again collect the data for training the Denovium Engine models. Like the ACE Assay, the HiPrBind Assay is designed to be readily adaptable to a diverse range of protein modalities. We also perform high-throughput biophysical characterization to collect additional data on relevant biophysical attributes that impact developability. We are able to select the best several candidates (leads) in their putative production cell lines for further analytics, as well as collect further data insights to enhance our Denovium Engine models. 15 Table of Contents • Scale: We optimize fermentation conditions for the selected lead strain(s) to demonstrate desired productivity, quality, and scalability. Having narrowed the cell population down from millions or billions to closer to a dozen, we employ several banks of state-of-the-art 250 mL fed batch fermenters to perform fermentation process optimization using design of experiments (DOE) methodologies to identify scalable production processes. To generate purified material for internal analytics and evaluation by our partners, we use standard chromatography purification methods to make small batches of protein-of-interest from the selected strains. We perform comprehensive protein analytics to evaluate product quality and purity, and we generate cell banks and documentation suitable for technology transfer to partners or the contract manufacturers they specify. • Learn: Throughout our process, we generate large and complex datasets specifying determinants of protein function and manufacturability. We use these data to train our Denovium Engine to enable its models to make increasingly refined predictions for target identification, drug scaffold sequence variation and cell line design. Our goal is to train the deep learning models with enough data to be able to input a sequence of a new drug target, or even bulk mRNA from a patient, and have the model output a unique, optimal drug candidate sequence and cell line architecture that we construct and confirm: a process that we refer to as de novo biologic drug creation in silico. Applications of our Integrated Drug Creation Platform Our platform is flexible, and we are able to onboard a given program at multiple points in the biologic target identification, drug discovery, and cell line development process. Starting with a given target and a desired scaffold format for an eventual drug candidate, we may perform comprehensive de novo biologic drug discovery through to cell line development. We may enhance discovery opportunities with our partners by building new scaffolds and designing new molecules to incorporate nsAAs to facilitate post-purification chemical modifications. We may further expand program scope to start with target identification activities incorporating our Totient Target technology. We may also design and optimize a high titer production cell line for a partner’s already-established lead drug candidate. We classify our applications into two key categories: Discovery and CLD. Since we deliver a production cell line for each of our projects, we define Discovery as any projects for which we are evaluating variants of the protein-of-interest, and we define CLD as a program for which the production cell line alone is the goal of the partnership. • Discovery: We commercially launched ou r initial Discovery applications in December 2020, and to date we have one Discovery program underway for lead optimization. Discovery involves screening for lead drug hits directed to the desired target; the target may be provided by a partner or identified using our computational antibody and target discovery technology. Unlike other commonly used screening methods used for biologic drug discovery, we are screening for hit variants in the complete 16 Table of Contents scaffold, not a domain fragment to be subsequently reformatted. We also screen in production cell line variants. Our Discovery applications are scaffold-agnostic. Whether we are screening variants of an antibody, a T-cell engager, a multivalent Fc-fusion, or any other human- or AI-designed modality, our platform is adaptable to simultaneously optimize for functionality and manufacturability of lead candidates. We believe there is no other commercially available solution that enables comprehensive scaffold-agnostic drug discovery in the desired scaffold format. The Discovery applications that we currently or in the future expect to address with our Integrated Drug Creation Platform are the following: ◦ Novel target identification - From tissue samples that are of particular therapeutic interest, we identify prevalent immune-response molecules such as antibodies along with the corresponding antigens, offering new therapeutic targets as well as cognate binding partners for further validation. Whatever the desired biologic modality, we can design, construct, and select the appropriate sequence for lead drug development. And we create an optimized production cell line. ◦ Scaffold design and drug platform development - We are uniquely capable of assembling and producing new-to-nature next-generation biologic scaffolds. We may therefore empower our partners with the ability to execute on theoretical modalities, creative fusions, and multivalent molecular hybrids. Within the context of those assembled scaffolds we can evaluate variants to discover new drug candidates designed for optimal target affinity and other desired characteristics. And we create optimized production cell lines. ◦ De novo discovery - We may perform de novo discovery by starting with a desired scaffold format for the desired drug and creating a library of relevant sequence variants that will establish the target specificity (e.g., CDR regions of antibody). And we create an optimized production cell line. ◦ Bionic Protein creation (nsAA incorporation) - We may engineer a signal into the gene encoding the drug candidate that directs incorporation of an nsAA into the growing protein chain in a site-specific manner. The nsAA provides a handle for chemical modifications including glycosylation, PEGylation, ADC-payload conjugation, and novel branched proteins and chemical conjugates. And we create an optimized production cell line. ◦ Human antibody discovery - From our catalog of human-derived antibody sequences we are building a collection of unique fully-human monoclonal antibodies with specificity for validated targets of interest. We may optimize monoclonal antibodies or next-generation biologics derived from these sequences as lead drug candidates in partnered programs. And we create an optimized production cell line. ◦ Lead optimization - We may start with drug discovery leads and introduce modifications into the sequences to evaluate variants for improved target affinity, manufacturability, and other pharmacologic characteristics. Thus we can optimize leads that our partners may advance through preclinical development. And we create an optimized production cell line. • Cell Line Development: We launched our CLD applications in 2018, as our first commercial offering, and all but one of our ongoing programs are for CLD. We classify a program as CLD only when the production cell line alone is the goal of the partnership, or in other words, when the sequence of the lead drug candidate is locked in. Fundamentally, the process utilizing our Integrated Drug Creation Platform is the same as for our Discovery programs, except that the plasmid libraries we design include a fixed lead drug sequence, with variation limited to the assortment of the folding and expression solutions. Screening and selection steps are aimed at identifying the cell lines with highest titer expression of the drug candidate. Partners typically have come to us with late-preclinical or clinical-stage next-generation biologics for which they have not been able to develop a manufacturing process or for which an existing manufacturing process is poorly performing. As we succeed in these CLD programs, we believe we enable the advancement of next-generation biologic candidates that otherwise would not proceed in development due to manufacturability challenges. 17 Table of Contents Advantages of our Integrated Drug Creation Platform Our platform integrates biologic drug discovery and cell line development processes, accomplishing these activities in parallel rather than sequentially, as illustrated relative to established approaches in the figure below. We have designed our Integrated Drug Creation Platform to provide the following potential benefits for our partners: • Accelerated timelines from idea to drug candidate: Our platform integrates biologic drug discovery and cell line development, collapsing time-consuming fragmented activities into one integrated process. Because from the start we screen for hits in the desired scaffold format and in the cell line that will scale up for manufacturing, we can bypass common failure points and avoid the need for molecular reformatting or subsequent cell line development. We optimize drug candidate properties and cell line performance in parallel from the outset of the project. We leverage our Integrated Drug Creation Platform and foundational technologies to accelerate novel target identification, biologic drug discovery, and cell line development timelines, whether we start with a lead candidate for which a partner needs a cell line, a new target against which a partner wants to create a next-generation drug candidate, or a scope that falls somewhere in between. Depending on the complexity of the project and the priorities specified by the partner, we can create a cell line for a defined biologic in as little as 10 days. Our timelines for CLD may enable transition from gene to production of material designed to comply with current good manufacturing practice (cGMP) requirements in six months, versus one to two years for standard CHO cell line development. Because 18 Table of Contents our discovery occurs in the same process, we expect to meet similar timelines with our Discovery programs. Our timelines relative to industry standards are depicted in the figure below. • Creation of new biologic modalities: Our Discovery applications are scaffold-agnostic. We use a synthetic biology approach and harness the power of nature using our SoluPro strains, which we have bioengineered to produce complex proteins rapidly and effectively. Utilizing our Integrated Drug Creation Platform, we specialize in creating new biologic modalities, discovering next-generation biologics in engineered scaffolds, and creating Bionic Proteins that incorporate nsAAs. Unlike other biologic drug discovery methods, from our initial screens we are looking for hit variants in the fully-constructed scaffold, not a domain fragment to be subsequently reformatted. By screening in the fully assembled molecular format and in the scalable production cell line, any leads we identify are designed to be readily manufacturable. Thus, we expect to enable entirely new biologic opportunities and reduce frustrating and costly preclinical failures that impede advancement of new-to-nature next-generation biologics. • Efficient production of complex biologics: We have bioengineered our SoluPro strains to excel at producing a wide variety of complex proteins. SoluPro overcomes the challenges encountered in using E. coli strains to synthesize complex biologics that first led the industry to turn to CHO cells. With our Integrated Drug Creation Platform, we deploy our synthetic biology toolkit and our folding and expression solutions libraries to customize the scaffold-agnostic base SoluPro strains to enable high titer production of the proteins we address. We are not restricted to making proteins that look like proteins found in nature; our SoluPro strains are readily adaptable to making biologics in new scaffolds or incorporating nsAAs. Because of the scope and throughput of our assays, we can evaluate millions or billions of potential strains to efficiently identify configurations of folding and expression solutions that confer optimal protein production performance. • Design of better drug candidates based on AI predictions: We use deep learning artificial intelligence models trained on our proprietary datasets as well as functional characteristics of millions of proteins represented in public databases to design new drug candidates to have desired pharmacologic performance without constraining ourselves to what nature has already discovered. We evaluate up to billions of distinct cell lines for each project. In addition to identifying the best performing drug sequences and cell lines, we are also generating immense datasets with the goal of substantiating and differentiating the relevant from the irrelevant, the optimal from the contraindicated, in the solution space of target specificity, drug sequence variation, and folding solutions. We harness this evidence to progressively train our deep learning Denovium Engine, which then outputs progressively more relevant and valuable predictions to direct our synthetic constructions. We believe this highly specialized deep learning approach is differentiated by both the technology that underpins the Denovium Engine and the proprietary data we feed it. Our Denovium 19 Table of Contents Engine models enable multi-parameter predictions and simultaneous optimization of attributes in parallel, making predictions that solve for desired attributes such as bioavailability, stability, immunogenicity, as well as target affinity and manufacturability. We believe that insights we achieve through the integration of deep learning will ultimately help identify the new drug candidates with the best chances for clinical success. • Increase manufacturing productivity and reduce costs: Beyond the savings afforded by reduced failure rates and accelerated timelines, we believe our SoluPro cell lines’ high productivity can translate into significant reductions in drug substance cost of goods. We estimate that biologic drug substance cost of goods saving could be on the order of 50% relative to CHO production systems, the most widely used system in the biopharmaceutical industry today. As discussed by Tripathi and Shrivastava in “Recent Developments in Bioprocessing of Recombinant Proteins: Expression Hosts and Process Development” in Frontiers in Bioengineering and Biotechnology (2019), and according to our experience, the primary determinant is the rapid and high-density growth of E. coli SoluPro relative to CHO cell lines; the SoluPro bioreactor growth cycle time is 1-2 days, as compared to 10-14 days for CHO cell lines. Given cell lines that achieve comparable protein production titers in SoluPro and CHO systems, the SoluPro system’s productivity would be roughly 5-10 times that of the CHO system on a grams per liter per day basis. In addition, SoluPro has other advantages associated with the use of E. coli as a biomanufacturing organism. In particular, its growth media ingredients are lower cost relative to the media required for mammalian cells, viral clearance studies are unnecessary, and heterogeneous glycosylation patterns do not hamper drug product quality or characterization. Our Market Our market opportunity is driven by the number of biologic candidates we generate and the successful development and commercialization of these candidates by our partners. As reflected in the Evaluate Pharma data, there are currently 1,250 companies involved in developing and marketing over 4,950 protein-based biologics, which we define as including candidates categorized as monoclonal antibodies (mAbs), monoclonal antibody conjugates (ADCs), and recombinant products (comprising novel fusion proteins as well as numerous conventional recombinant proteins, peptides, and hormones), but excluding those categorized as cell therapies, DNA and RNA based therapies, gene therapies, plasma-derived therapies, and vaccines. In 2020, cumulative global sales of these protein-based biologics reached approximately $254 billion, representing 33% of the sales of all drugs. In 2020, 72 protein-based biologics reached blockbuster status with annual worldwide sales higher than $1.0 billion. Of the total protein-based biologics sales, mAbs represent approximately 63%, with average per product peak sales of $2.7 billion (median $1.3 billion). The protein-based biologics market is expected to reach $418 billion by 2026, representing a compound annual growth rate of approximately 9%. In the near term, we are focused on the next-generation biologics market, which we estimate based on our analysis of the Evaluate Pharma data to represent approximately 32% of protein-based biologics in Phase 1 clinical development. We estimate next-generation biologics represent a similar proportion of the 2,539 preclinical protein-based biologics. While our Integrated Drug Creation Platform is suited to generation of any type of protein-based biologic, we believe our capabilities are especially differentiated in the area of next-generation biologics. We expect our future programs to be principally in this category as we seek to provide an avenue to expand the number and variety of next-generation biologics 20 Table of Contents in development by our existing and future partners, including with the addition of nsAA-containing Bionic Proteins to their pipelines. The figures below illustrate the number of protein-based biologics in each phase of development, including our estimate of the number of next-generation biologics in preclinical development, and the projected sales of protein-based biologics. Other market opportunities Proteins are fundamental components of a wide variety of current or potential biological products. We believe our platform is applicable beyond the biopharmaceutical market, including into markets such as diagnostics, materials science, agriculture, industrial, animal health, cosmetics and synthetic food. While our initial focus is on the biopharmaceutical market, we recognize there are broad market opportunities in these additional industries, and we may pursue those opportunities in due course. For example, we currently have one program in animal health. Our Business Model and Partnerships Our business model differs from the traditional biotechnology company model. As a technology development company, we generate biologic drug candidates and production cell lines for our partners to develop. Our business model is to establish partnerships with biopharmaceutical companies and use our Integrated Drug Creation Platform for rapid creation of next-generation biologic drug candidates and production cell lines. We are invested in the clinical and commercial success of the product candidates generated for our partners using our Integrated Drug Creation Platform. We expect that our partnerships will provide us with the opportunity to participate in the future success of the biologics generated utilizing our platform, through potential clinical, regulatory and commercial milestone payments as well as royalties on net sales of approved products. We aim to assemble economic interests in a diversified portfolio of partners’ next-generation biologics across multiple indications. We believe our business model is capital efficient as our partners fund our technology development work, and we do not invest in clinical development or scaled manufacturing infrastructure. We structure our partnerships as technology development agreements (each molecule we address for Discovery or CLD is a “program”) with options for our partners to license intellectual property rights to the biological assets we create after completion of the technology development phase. For the technology 21 Table of Contents development phase, partners may (i) provide a target for discovery of a new next-generation biologic and/or Bionic Protein or novel scaffold, (ii) supply a specified lead drug candidate sequence for cell line development, or (iii) request a scope that falls somewhere in between (i) and (ii) with optimization of a lead candidate or set of candidates as the primary goal. Regardless of the scope, the biology we ultimately provide to our partners is a manufacturing-ready cell line expressing the new or partner-provided protein-of-interest. For most future partnerships, we expect to negotiate and agree to downstream economic terms of any license to our intellectual property rights before initiating the technology development phase. We anticipate that these technology development and license agreements may provide us with rights to receive payments upon the achievement of various clinical, regulatory and commercial milestones for the applicable product candidates, as well as royalties on net sales at least during the marketing exclusivity period of candidates approved for commercialization. As of December 31, 2021, we had drug candidates in twelve Active Programs (across eight current partners’ preclinical or clinical pipelines) for which we have negotiated, or expect to negotiate upon completion of certain technology development activities, license agreements with potential downstream milestone payments and royalties. Eight of these Active Programs are focused on developing production cell lines for drug candidates that our partners (Merck & Co., Inc., Xyphos Biotechnology, Astellas, Alpha Cancer Technologies, Inc., PhaseBio Pharmaceuticals, Inc., and other undisclosed biotechnology companies) are developing (five preclinical, one Phase 1, one Phase 3, and one animal health). The remaining four Active Programs comprise Discovery applications, including three Discovery programs through our agreement with EQRx and one lead optimization program with Astellas. We define “Active Programs” as programs that are subject to ongoing technology development activities intended to determine if the program can be pursued by our partner for future clinical development, as well as any program for which our partner obtains and maintains a license to our technology to advance the program after completion of the technology development phase. There is no assurance, however, that our partners will advance any drug candidates that are currently the subject of Active Programs into further preclinical or clinical development or that our partners will elect to license our technologies upon completion of the technology development phase in a timely manner, or at all. In addition to our twelve Active Programs, we have also completed CLD technology development for 22 additional molecules. These historical programs were both internal research programs and technology development programs with third parties, and they were intended to demonstrate our platform’s capabilities as we addressed successively broader ranges of biologics and next-generation modalities. We did not transfer technology or grant licenses related to these programs, and we anticipate no further revenue or other downstream payments. The following table summarizes the biologic modalities for all of our current and historical programs, including our Active Programs: Biologic Modality # of Programs Active Programs All Programs Bispecific mAb 1 1 Bispecific T-cell engager 2 3 Cytokine 1 2 Fab* 1 4 Multivalent Fc*-fusion 2 2 Plasma protein 1 1 mAb 1 4 Fc-fusion 3 scFv*-fusion 2 VHH*-fusion 2 Enzyme 2 Hormone 5 Not specified 3 3 Total 12 34 * Fab = antigen-binding fragment; Fc = crystallizable fragment; scFv = single-chain variable fragment; VHH = single variable domain on a heavy chain (nanobody) 22 Table of Contents * Commercial Our commercial strategy centers on entering into technology development partnerships with companies involved in biologic drug development, with a focus on the biopharmaceutical industry. Our goal is to secure new partners and expand our relationships with existing partners by solving challenges they face in discovery and cell line development and by enabling creation of new biologic modalities. With initial success, we aim to increase the number of molecules with each partner, as well as expand the application of our platform across each partner’s discovery and cell line development activities. Our business strategy involves forming partnerships with biopharmaceutical companies of all sizes and enabling our partners to bring their ideas to fruition. We currently have a core business development team raising awareness of our platform within the biopharmaceutical industry and establishing adoption through partnerships. We are initially focusing our business development efforts on large pharmaceutical companies with the potential to create multi-program opportunities, as well as biotechnology companies that are, or desire to be, leaders in next-generation biologics creation. We expect to partner with companies that are highly enabled and at the forefront of next-generation biologics but which may have had limited success due to technological challenges. We also expect to partner with companies that may have some presence in biologics but limited capabilities in novel biologic drug discovery and are looking to expand their pipelines. We also see opportunities to partner with focused biotechnology companies that are highly enabled with a biologics platform or multi-product pipeline but limited capabilities in drug discovery or cell line development. We expect these companies to seek access to our integrated platform to improve the quality of their lead drug candidates and enable development of scalable manufacturing cell lines to accelerate their development efforts and push the frontier of therapeutics. We also have an alliance management team focused on supporting our successful partnership programs and growing our relationships with existing partners to include additional biologic candidates as well as expand to broader discovery programs. We believe that exceptional alliance management execution is critical to the success of our existing partnership programs and to transforming first-time partners into repeat and broad scope collaborators. We emphasize mutually beneficial partnerships through alignment of performance objectives, and we foster our partners as champions of our technology. We expect to expand our business development and alliance management teams significantly as we scale our business in the near term. Our Growth Strategy Our goal is to establish our proprietary, end-to-end platform as the industry standard for biologic drug discovery and cell line development. We are laying the groundwork for integration into our partners’ discovery organizations, with the goal to be the de facto starting point for new drug creation. Our growth strategy is to: • Establish new partnerships to create biologic drug candidates. We believe that our platform has a clear and differentiated value proposition for biologic drug discovery and cell line development. We have been successful in attracting initial partners, and we are continuing to expand our capabilities and enhance our platform to offer an even more powerful integrated solution. Given the increasing level of biopharmaceutical industry interest in creating novel biologics, we believe there is a large untapped market of potential partners ranging from traditional large pharmaceutical companies to emerging biotechnology innovators who can realize benefits from our platform. We believe that we offer a way to transcend the discovery and production challenges faced by the many companies that are investing in developing innovative new protein-based medicines. As we continue to establish our platform as the go-to solution for biologic drug creation, we expect to continue to attract new partners. We employ a business development team focused on raising awareness of our capabilities and establishing new partnerships. • Increase the number of molecules on which we work with our existing partners. We believe that achieving technical success with an existing partner’s drug candidate is the best proof of concept, and we intend to leverage those successes to expand our existing partnerships to address additional molecules in our partners’ respective pipelines. Partners may have a unique scaffold upon which they build successive drug candidates, hence pursuing additional programs based on the same scaffold is a clear opportunity for expanding existing partnerships. Regardless of modality, we expect to generate additional business from existing partners as they experience firsthand the success and efficiency of 23 Table of Contents our platform. Our alliance management team is focused on supporting our partnership success and growing the number of molecules on which work with our partners. • Expand the scope of our partnerships across the biologic drug discovery and cell line development value chain. We launched our CLD applications in 2018 and our initial Discovery applications in December 2020. Our goal is to expand our partnerships to apply a broader set of our platform capabilities, including both Discovery and CLD. Because we launched our CLD applications first, we have historically initiated our partnerships with CLD programs for lead drug candidates that have proven challenging to produce. CLD program partners often become interested in our Discovery applications, which include novel target identification, lead optimization, de novo discovery, Bionic Protein creation (nsAA incorporation), human antibody discovery, and the enablement of novel scaffold designs that could spawn new modalities. We look to expand the scope of partnerships to address additional classes of molecules, thereby presenting additional milestone and royalty opportunities. We intend to continue to invest in growing our platform’s capabilities and aim to expand our applications to offer even more comprehensive solutions for our partners. • Create new biologic modalities and novel conjugates with Bionic Proteins that incorporate nsAAs. We aim to use our platform to pursue a wide range of applications and to enable the creation of new drug modalities and previously inaccessible conjugates. To achieve this, we introduce customized machinery into our Bionic SoluPro strain that empowers it to incorporate nsAAs at specified locations in proteins. We can create entirely new drug modalities and assemble previously inaccessible conjugates using straightforward chemistry in combination with the nsAA incorporation. We expect to apply this differentiated capability repeatedly across numerous programs to add substantial value to our partners’ discovery and development processes. • Grow our platform through R&D and strategic acquisitions. We intend to continue innovating and extending avenues for creating better new biologics and cell lines at a faster pace. Near term, we are investing in research and development activities to refine our nsAA incorporation, de novo discovery, and purification technologies to enable targeted chemical modifications and conjugations in a homogenous manner. With our acquisition of Totient, and the addition of computational antibody and target discovery technology, we expect to engage with partners seeking differentiated disease-specific discovery opportunities for biologics development. We are also integrating our recently-acquired Denovium Engine deep learning artificial intelligence across our technologies, and we are driving toward a future in which the Denovium Engine understands the relevant drug and cell line determinants so comprehensively that its models can predict what we believe is the best scaffold and drug sequence as well as cell line design for any given target, without screening. This would be the realization of our vision of de novo drug creation in silico . We also intend to pursue opportunities for expanding our platform using AI as well as other technologies that we may develop or acquire. Biological validation technologies, preclinical evaluation models, and downstream protein purification technologies are all potential areas of strategic interest that could further enhance our value proposition to partners and provide us with important insights to steer our internal efforts. • Create proprietary assets. We intend to selectively create our own lead drug candidates and advance them through preclinical validation. In such cases we may out-license pre-IND candidates for clinical advancement by a partner, with the expectation of a greater share in the economics relative to the milestones and royalties we may secure for our core platform technology development licenses. • Leverage our platform to address market opportunities outside of biopharmaceuticals. Although we are currently focused on the biopharmaceuticals markets and we intend to maintain this focus in the near term, we believe our platform has the foundational technology and capabilities in place to capitalize on the opportunity to create proteins of value in many other industries. Such potential target applications include materials science, industrial chemicals, cosmetics, synthetic foods, and agriculture. Over the longer term, we may create new biological tools and designer enzymes that lead to applications spanning, but not limited to, bioremediation solutions, bioprocessing achievements, organic agricultural advances, and cost-effective protein-based consumables. Competition The market for technologies that enable biopharmaceutical research and development, such as ours, is global, characterized by intense competition and subject to significant intellectual property barriers. The solutions and applications offered by our competitors vary in size, breadth, and scope, and we face 24 Table of Contents competition from many different sources. Due to the significant interest and growth in biopharmaceutical research and development more broadly, we expect the intensity of this competition to increase. We do not believe there are any other commercially available solutions that enable high-throughput screening of next-generation biologic drug variants in the assembled scaffold in the production cell line. Moreover, we are not aware of technologies that allow for efficient discovery of full length next-generation protein based therapeutics. We are aware of potential competitors addressing certain steps in the target identification, biologic drug discovery, and cell line development processes or adjacent aspects of the broad process, including: • in the field of novel target identification, we may face competition from academic, pharmaceutical, and biotechnology research initiatives, as well as companies focused on novel methods for target identification, including Insitro, Inc., TScan Therapeutics, Inc., and 3T Biosciences, Inc.; • in the field of AI-guided drug design and discovery, we may face competition from companies designing novel proteins such as Generate Biomedicines, Inc., as well as adjacent technology companies pursuing small molecule design such as Schrodinger, Inc., Recursion Pharmaceuticals, Inc., Relay Therapeutics, Inc., Atomwise Inc., Valo Health, Inc., and Exscientia Limited; • in the field of scaffold design and drug platform development, we may face competition from pharmaceutical and biotechnology companies developing novel biologic modalities including Amgen Inc., Crescendo Biologics Limited and Harpoon Therapeutics, Inc., among others; • in the field of novel human/humanized antibody discovery, we may face competition from companies such as AbCellera Biologics Inc., Adimab LLC, and Alloy Therapeutics, Inc.; • in the field of non-standard amino acid protein engineering, we may face competition from companies such as Ambrx Inc. and Sutro Biopharma, Inc. (Sutro); and • in the field of cell line generation and single-cell screening, we may face competition from service providers, such as Lonza Group AG and Selexis SA, companies offering instrumentation, such as Berkeley Lights Inc., and companies with alternative protein production systems, such as Sutro. In addition, we are aware of other synthetic biology companies focused on developing various custom cell lines in a variety of model organisms for biomanufacturing of molecules relevant to other industries. These companies, which include Ginkgo Bioworks, Inc., Zymergen Inc., Geltor, Inc., and Bolt Threads, Inc. may in the future pursue biopharmaceutical applications of their platforms that could compete with our technologies. Our target partners may also elect to develop their own processes on legacy systems, use in house solutions, or use traditional methods, rather than implementing our platform and may decide to stop using our platform. In addition, there are many large established players in the life science technology market that we do not currently compete with but that could develop systems, tools or other products that will compete with us in the future. These large established companies have substantially greater financial and other resources than us, including larger research and development staff or more established marketing and sales forces. For a discussion of the risks we face relating to competition, see “Risk Factors—Risks Related to our Business and Strategy—The biopharmaceutical platform technology market is highly competitive, and if we cannot compete successfully with our competitors, we may be unable to increase or sustain our revenue, or sustain profitability.” Intellectual Property We use a variety of intellectual property protection strategies, including patents, trademarks, trade secrets and other methods of protecting proprietary information. Our success depends in part on our ability to obtain and maintain intellectual property protection for the components of our Integrated Drug Creation Platform; to defend and enforce our patents, to preserve the confidentiality of our trade secrets; to operate without infringing valid and enforceable patents and other proprietary rights of third parties and to identify new opportunities for intellectual property protection. As of December 31, 2021, we own 40 issued or granted patents and 83 pending patent applications worldwide, which includes four issued U.S. patents and 36 pending U.S. patent applications. We also have granted patents in the EU, Australia, Japan, Brazil, Canada, China, Hong Kong, Israel, Mexico, and Republic of Korea. Our patents and patent applications, if issued, are expected to expire between August 2033 and 25 Table of Contents December 2042, in each case without taking into account any possible patent term adjustments or extensions and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees. Our patents and patent applications include the following: Technology Issued Patents Pending Applications Type of Protection Host strains, accessory proteins, expression vectors and other expression technology, including non-standard amino acid technology 4 U.S. 36 foreign 11 U.S. applications (3 provisional) 1 PCT Application 19 foreign applications Compositions, methods, kits Proprietary Assays and Techniques 4 U.S. applications (3 provisional) 2 PCT applications 10 foreign applications Compositions, Methods Antibodies, nucleic acids, vectors, host cells, kits, and methods of treating diseases, such as cancer and COVID 23 U.S. applications (21 provisional) 1 PCT application 13 foreign applications Compositions, methods, kits Antibody discovery computational methods 1 pending application (PCT) Methods The protection provided by a patent varies from country to country, and is dependent on the type of patent granted, the scope of the patent claims, and the legal remedies available in a given country. In addition, the term of individual patents depends upon the legal term of the patents in the countries in which they are obtained. In most countries in which we file, the patent term is 20 years from the earliest non-provisional filing date, subject to any disclaimers or extensions. The term of a patent in the United States can be adjusted due to any failure of the United States Patent and Trademark Office (USPTO) following certain statutory and regulation deadlines for issuing a patent. In addition, in the United States, the term of a U.S. patent that covers an FDA-approved drug may also be eligible for patent term extension, which, if granted, permits patent term restoration as compensation for the patent term lost during the FDA regulatory review process. The Hatch-Waxman Act permits a patent term extension of up to five years beyond the original expiration of the patent. The length of the patent term extension is related to the length of time the drug is under regulatory review. Patent term extension cannot extend the remaining term of a patent beyond a total of 14 years from the date of product approval and only one patent applicable to an approved drug may be extended and only those claims covering the approved drug, a method for using it, or a method for manufacturing it may be extended. Similar provisions are available in Europe and other foreign jurisdictions to extend the term of a patent that covers an approved drug. In the future, if we determine to develop our own product candidates and any such product candidates receive FDA approval, we expect to apply for patent term extensions on patents covering those products. While we may seek patent term extensions of our relevant issued patents in any jurisdiction where such extensions are available, there is no guarantee that the applicable authorities, including the FDA in the United States, will agree with our assessment of whether such extensions should be granted, and if granted, the length of such extensions. As of December 31, 2021, we owned registered trademarks for Absci, SoluPro, SoluPure in the United States, as well as eight trademark registrations in other jurisdictions. In addition to patent and trademark protection, we also utilize other forms of intellectual property protection, including copyright, internal know-how and trade secrets, when such other forms are better suited to protect a particular aspect of our intellectual property position. For example, our trade secrets encompass certain algorithms associated with our deep learning Denovium Engine, our computational antibody and target discovery technology, manufacturing protocols for our E. coli SoluPro strains, libraries of protein folding solutions and design of molecular libraries for drug discovery. We believe our proprietary rights are strengthened by our comprehensive approach to intellectual property protection. It is our policy to require our employees, consultants, advisors and other independent contractors to execute confidentiality and invention assignment agreements upon accepting employment, consulting or similar relationships with us. These agreements provide that all confidential information concerning our business or financial affairs 26 Table of Contents developed or made known to the individual during the course of the individual’s relationship with us is to be kept confidential and not disclosed to third parties except in specific circumstances. We also take precautions through the use of security measures to prevent the release of our proprietary information to third parties. Although we take steps to protect our proprietary information and trade secrets, including through contractual means with our employees, consultants, advisors and other independent contractors, these agreements may be breached and we may not have adequate remedies for any breach. In addition, third parties may independently develop substantially equivalent proprietary information and techniques or otherwise gain access to our trade secrets or disclose our technology. As a result, we may not be able to meaningfully protect our trade secrets and other proprietary technology. For a discussion of the risks we face relating to intellectual property, see “Risk Factors—Risks Related to our Intellectual Property.” Government Regulation Regulations Related to the Discovery, Development, Approval and Commercialization of Biotherapeutics Our focus is on the use of our platform to enable our partners to improve the speed and success of their biologic product discovery and development efforts. As such, while we are subject to a number of regulations, such as those governing our laboratory facilities as well as regulations that apply to businesses in the private sector generally, we are not subject to many of the types of regulations that ordinarily apply to companies in the life sciences, biotechnology and pharmaceutical sectors and industries. However, we believe that the long-term success of our business depends, in part, on our partners’ ability to successfully develop and sell products identified and created through our platform technology. The regulations that govern our pharmaceutical and biotechnology partners are those we therefore believe have the most significant impact on our business. Government authorities in the United States, at the federal, state and local level, and in the European Union and other countries and jurisdictions, extensively regulate, among other things, the research, development, testing, manufacturing, quality control approval, labeling, packaging, storage, record-keeping, promotion, advertising, distribution, post-approval monitoring and reporting, marketing and export and import of pharmaceutical products, including biological products such as those that our partners develop. The processes for obtaining marketing approvals in the United States and in foreign countries and jurisdictions, along with subsequent compliance with applicable statutes and regulations and other regulatory authorities, require the expenditure of substantial time and financial resources. If we or our partners fail to comply with applicable laws or regulations at any time, we or our partners may become subject to administrative or judicial sanctions or other legal consequences, including among other things, restrictions on marketing or manufacturing, withdrawal of products, product recalls, fines, warning letters, untitled letters, clinical holds on clinical studies, refusal of the FDA to approve pending applications or supplements to approved applications, suspension or revocation of product approvals, product seizure or detention, refusal to permit the import or export of products, consent decrees, corporate integrity agreements, debarment or exclusion from federal healthcare programs, mandated modification of promotional materials, issuance of safety alerts, Dear Healthcare Provider letters, injunctions or the imposition of civil or criminal penalties. Our partners must obtain the requisite approvals from the applicable regulatory authority prior to the commencement of clinical studies or marketing of a biological product in those countries. The requirements and process governing the conduct of clinical trials, product licensing, coverage, pricing and reimbursement vary from country to country. In the United States, biological products are subject to regulation under the Federal Food, Drug, and Cosmetic Act, the Public Health Service Act, and other federal, state, local and foreign statutes and regulations. The process required by the FDA before biologics may be marketed in the United States generally involves the following: • completion of preclinical laboratory tests and animal studies performed in accordance with the FDA’s applicable good laboratory practices regulations (GLP); • submission to the FDA of an application for an IND, which must become effective before clinical trials may begin; • approval of the protocol and related documentation by an independent institutional review board (IRB), or ethics committee at each clinical site before each trial may be initiated; 27 Table of Contents • performance of adequate and well-controlled human clinical trials according to the FDA’s regulations commonly referred to as good clinical practices (GCPs), and any additional requirements for the protection of human research subjects and their health information, to establish the safety and efficacy of the proposed biological product for its intended use; • preparation of and submission to the FDA of a biologics license application (BLA), for marketing approval that includes sufficient evidence of establishing the safety, purity, and potency of the proposed biological product for its intended indication, including from results of nonclinical testing and clinical trials; • satisfactory completion of an FDA inspection of the manufacturing facility or facilities where the biological product is produced to assess compliance with cGMPs, to assure that the facilities, methods and controls are adequate to preserve the biological product’s identity, strength, quality and purity; • potential FDA audit of the nonclinical study and clinical trial sites that generated the data in support of the BLA; • review of the product candidate by an FDA advisory committee, where appropriate and if applicable; • payment of user fees for FDA review of the BLA (unless a fee waiver applies); and • FDA review and approval of the BLA, resulting in the licensure of the biological product for commercial marketing. Although we have not historically engaged directly in the discovery of our own biologics, we anticipate that in the future, we may selectively create our own biologic product candidates and advance such candidates through preclinical validation and cGMP manufacturing scale-up. Before testing any biologic product in humans, the product candidate must undergo rigorous preclinical testing. Preclinical studies include laboratory evaluations of drug chemistry, formulation and stability, as well as in vitro and animal studies to assess safety and in some cases to establish the rationale for therapeutic use. The conduct of preclinical studies is subject to applicable federal/national, supranational, state and local level regulations and requirements, including GLP, requirements for safety/toxicology studies. The results of the preclinical studies, together with manufacturing information and analytical data, must be submitted to the FDA as part of an IND or the appropriate regulatory authority in foreign countries as part of a clinical trial application (CTA). An IND is a request for authorization from the FDA to administer an investigational new drug to humans. In the United States, an IND must become effective before human clinical trials may begin. The IND automatically becomes effective 30 days after receipt by the FDA, unless the FDA, within the 30-day time period, raises safety concerns or questions about the proposed clinical trial. In such a case, the IND may be placed on clinical hold and the IND sponsor and the FDA must resolve any outstanding concerns or questions before the clinical trial can begin. Submission of an IND therefore may or may not result in FDA authorization to begin a clinical trial. Clinical trials involve the administration of the investigational product to human subjects under the supervision of qualified investigators in accordance with GCPs, which include the requirement that all research subjects provide their informed consent for their participation in any clinical study. Clinical trials are conducted under written trial protocols detailing, among other things, the objectives of the clinical trial, the parameters to be used in monitoring safety and the effectiveness criteria to be evaluated. A separate submission to the existing IND must be made for each successive clinical trial conducted during product development and for subsequent protocol amendments. Furthermore, an independent IRB for each site proposing to conduct the clinical trial must review and approve the plan for any clinical trial and its informed consent form before the clinical trial begins at that site, and must monitor the study until completed. Regulatory authorities, the IRB or the sponsor may suspend a clinical trial at any time on various grounds, including a finding that the subjects are being exposed to an unacceptable health risk or that the trial is unlikely to meet its stated objectives. Some studies also include oversight by an independent group of qualified experts organized by the clinical study sponsor, known as a data safety monitoring board, which provides authorization for whether or not a study may move forward at designated check points based on access to certain data from the study and may recommend halting the clinical trial if it determines that there is an unacceptable safety risk for subjects or other grounds, such as no demonstration of efficacy. There are also requirements governing the reporting of ongoing clinical studies and clinical study results to public registries. 28 Table of Contents For purposes of BLA approval, human clinical trials are typically conducted in three sequential phases that may overlap or be combined : • Phase 1—The investigational product is initially introduced into healthy human subjects or patients with the target disease or condition. These studies are designed to test the safety, dosage tolerance, absorption, metabolism and distribution of the investigational product in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on effectiveness. • Phase 2—The investigational product is administered to a limited patient population with a specified disease or condition to evaluate the preliminary efficacy, optimal dosages and dosing schedule and to identify possible adverse side effects and safety risks. Multiple Phase 2 clinical trials may be conducted to obtain information prior to beginning larger and more expensive Phase 3 clinical trials. • Phase 3—The investigational product is administered to an expanded patient population to further evaluate dosage, clinical efficacy, potency, and safety in an expanded patient population at geographically dispersed clinical trial sites. These clinical trials are intended to establish the overall risk/benefit ratio of the investigational product and to provide an adequate basis for product approval and product labeling. In some cases, FDA may require, or firms may voluntarily pursue, post-approval clinical trials, sometimes referred to as Phase 4 clinical trials, after initial marketing approval. These clinical trials are used to gain additional experience from the treatment of patients in the intended therapeutic indication, particularly for long-term safety follow-up. During all phases of clinical development, regulatory agencies require extensive monitoring and auditing of all clinical activities, clinical data, and clinical trial investigators. Concurrent with clinical trials, companies usually complete additional animal studies and also must develop additional information about the chemistry and physical characteristics of the biological product and finalize a process for manufacturing the product in commercial quantities in accordance with cGMP. To help reduce the risk of the introduction of adventitious agents with use of biological products, the Public Health Service Act emphasizes the importance of manufacturing control for products whose attributes cannot be precisely defined. The manufacturing process must be capable of consistently producing quality batches of the product candidate and, among other things, the sponsor must develop methods for testing the identity, strength, quality, potency and purity of the final biological product. Additionally, appropriate packaging must be selected and tested and stability studies must be conducted to demonstrate that the biological product candidate does not undergo unacceptable deterioration over its shelf life. Healthcare Laws and Regulations Biopharmaceutical companies are subject to additional healthcare regulation and enforcement by the federal government and by authorities in the states and foreign jurisdictions in which they conduct their business. These laws and regulations may constrain our relationships with our partners. Such laws include, without limitation, state and federal anti-kickback, fraud and abuse, false claims, and transparency laws and regulations related to drug pricing and payments and other transfers of value made to physicians and other healthcare providers. If our partners’ operations are found to be in violation of any of such laws or any other governmental regulations that apply, by extension, we may be subject to penalties, including, without limitation, administrative, civil and criminal penalties, damages, fines, disgorgement, the curtailment or restructuring of operations, integrity oversight and reporting obligations, exclusion from participation in federal and state healthcare programs and responsible individuals may be subject to imprisonment. Additional Regulations In addition to the foregoing, state and federal U.S. laws regarding environmental protection and hazardous substances affect our business. These and other laws govern our use, handling and disposal of various biological, chemical and radioactive substances used in, and wastes generated by, our operations. If our operations result in contamination of the environment or expose individuals to hazardous substances, we could be liable for damages and governmental fines. We believe that we are in material compliance with applicable environmental laws and that continued compliance therewith will not have a material adverse effect on our business. We cannot predict, however, how changes in these laws may affect our future operations. 29 Table of Contents Healthcare Reform Payors, whether domestic or foreign, or governmental or private, are developing increasingly sophisticated methods of controlling healthcare costs and those methods are not always specifically adapted for new technologies. In both the United States and certain foreign jurisdictions, there have been a number of legislative and regulatory changes to the health care system that could impact our ability to sell our products profitably. In particular, in 2010, the Patient Protection and Affordable Care Act, as amended by the Health Care and Education Reconciliation Act of 2010 (ACA) was enacted, which, among other things, subjected biologic products to potential competition by lower-cost biosimilars; addressed a new methodology by which rebates owed by manufacturers under the Medicaid Drug Rebate Program are calculated for drugs that are inhaled, infused, instilled, implanted or injected; increased the minimum Medicaid rebates owed by most manufacturers under the Medicaid Drug Rebate Program; extended the Medicaid Drug Rebate program to utilization of prescriptions of individuals enrolled in Medicaid managed care organizations; subjected manufacturers to new annual fees and taxes for certain branded prescription drugs; created a new Medicare Part D coverage gap discount program, in which manufacturers must agree to offer 50% (increased to 70% pursuant to the Bipartisan Budget Act of 2018, effective as of January 1, 2019) point-of-sale discounts off negotiated prices of applicable brand drugs to eligible beneficiaries during their coverage gap period, as a condition for the manufacturer’s outpatient drugs to be covered under Medicare Part D; and provided incentives to programs that increase the federal government’s comparative effectiveness research. Anti-Corruption Laws We are subject to the U.S. Foreign Corrupt Practices Act of 1977, as amended (FCPA) the U.S. domestic bribery statute contained in 18 U.S.C. § 201, the U.S. Travel Act, the USA PATRIOT Act, and possibly other state and national anti-bribery and anti-money laundering laws in countries in which we conduct activities, such as the UK Bribery Act 2010 and the UK Proceeds of Crime Act 2002 (Anti-Corruption Laws). Among other matters, such Anti-Corruption Laws prohibit corporations and individuals from directly or indirectly paying, offering to pay or authorizing the payment of money or anything of value to any foreign government official, government staff member, political party or political candidate, or certain other persons, in order to obtain, retain or direct business, regulatory approvals or some other advantage in an improper manner. We can also be held liable for the acts of our third party agents under the FCPA, the UK Bribery Act 2010 and possibly other Anti-Corruption Laws. In the healthcare sector, anti-corruption risk can also arise in the context of improper interactions with doctors, key opinion leaders and other healthcare professionals who work for state-affiliated hospitals, research institutions or other organizations. Our Culture We actively engage in evolving our culture every day, throughout our organization. We invite input, consider best practices, and iterate to create the Absci culture that best reflects and projects the nature of our people. The values we embody are: • Believe in the impossible • Proceed with passion and grit • Foster collaboration and communication • Expect integrity and excellence • Enjoy the adventure Collectively and individually we are defying conventions and innovating without boundaries. We are disrupting the biopharmaceutical industry with bold ideas and passionate pursuit of new possibilities. We share the mission of changing the world, one protein at a time. Human Capital Resources As of December 31, 2021, we had 212 employees and 211 full-time employees, many of whom have advanced post-graduate degrees. None of our employees is represented by a labor union with respect to his or her employment with us. We consider our relationship with our employees to be good. Our human capital resources objectives include, as applicable, identifying, recruiting, retaining, incentivizing and integrating our existing and additional employees. The principal purposes of our equity incentive plans are to attract, retain 30 Table of Contents and motivate selected employees, consultants and directors through the granting of stock-based compensation awards and cash-based performance bonus awards. Corporate Information We were originally formed in August 2011 as an Oregon limited liability company and later converted into a Delaware limited liability company in April 2016 under the name AbSci LLC. In October 2020, we completed a reorganization whereby we were converted from a Delaware limited liability company named AbSci LLC to a Delaware corporation under the name Absci Corporation and all outstanding membership interests in AbSci LLC were exchanged for equity interests in Absci Corporation. In June 2021, we completed our acquisition of Totient, Inc., a discovery company harnessing human immune responses to identify novel antibodies and their therapeutic targets, in exchange for a combination of cash and equity consideration. Our principal executive offices are located at 18105 SE Mill Plain Boulevard, Vancouver, Washington 98683. Our telephone number is (360) 949-1041. Our website address is https://www.absci.com/. Information contained on, or that can be accessed through, our website should not be considered to be part of this Annual Report. You are advised to read this Annual Report in conjunction with other reports and documents that we file from time to time with the SEC. In particular, please read our Quarterly Reports on Form 10-Q and any Current Reports on Form 8-K that we may file from time to time. You may obtain copies of these reports directly from us or from the SEC. In addition, the SEC maintains information for electronic filers (including Absci Corporation) at its website at www.sec.gov. We make our periodic and current reports available on our internet website, free of charge, as soon as reasonably practicable after such material is electronically filed with, or furnished to, the SEC. Available information Our Annual Reports on Form 10‑K, Quarterly Reports on Form 10‑Q, Current Reports on Form 8‑K, proxy and information statements and amendments to reports filed pursuant to Sections 13(a), and 15(d) of the Securities Exchange Act of 1934, as amended (the Exchange Act) are filed with the SEC. We are subject to the informational requirements of the Exchange Act and file or furnish reports, proxy statements and other information with the SEC. The SEC maintains an Internet site that contains reports, proxy and information statements and other information regarding issuers that file electronically with the SEC at www.sec.gov. Such documents and other information filed by us with the SEC are available free of charge on our investor relations website (https://investors.absci.com/) when such reports are available on the SEC’s website. Investors and others should note that we may announce material information to the public through filings with the SEC, on our investor relations website (https://investors.absci.com/), press releases, public conference calls, and public webcasts. We encourage our investors and others to review the information disclosed through such channels as such information could be deemed to be material information. Please note that this list may be updated from time to time.