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Item 1. Business

2026-03-31 compared with 2025-04-03 · 210 added, 263 removed, 210 unchanged (69% of the section changed)

We are an Artificial Intelligence (“AI”) technology company developing innovative neuroscientific solutions with goals to improve brain health outcomes for patients with mental illnesses and neurological disorders.

Our FDA-510(k) cleared BNA™, or Brain Network Analytics, is an advanced neurophysiological assessment tool that uses AI and machine learning to analyze EEG data recorded during rest and cognitive activity.

It may enhance neurological assessments by providing objective, data-driven insights that allow for the early and longitudinal detection of neurophysiological deviations.

These insights into brainwave patterns underlying cognitive function may help in tailoring personalized treatment plans and improving patient outcomes more effectively than traditional EEG analysis.

Most neurological disorders affect the neurophysiological state of brain networks.

BNA™ has the potential to detect these subtle changes, aiding the management of various cognitive and neurological disorders where cognitive functions are impacted.

This can include but is not limited to:

Mood and anxiety disorders as well as neurodevelopmental and neurodegenerative diseases and brain injuries.

While it offers significant benefits in these areas, BNA™ is may be most effective when integrated into a comprehensive diagnostic and treatment approach.

We have taken a period of 15 years and an investment of more than $60 million, to develop the software, compile the requisite database of brain wave tests, gain patent protection, and receive Federal Drug Administration (“FDA”) clearance to market and sell the BNA Platform.

The BNA Platform is a software as a medical solution that was developed using AI through unsupervised machine learning (via clustering analysis) on our extensive proprietary database of standardized, high-definition longitudinal electroencephalograms (“EEG”) of over 18,000 patients representing twelve disorders, as well as clinically healthy normal patients.

The AI algorithms underlying the BNA platform play a crucial role throughout the workflow by automating complex computational tasks during the following steps of data analysis:

(1) data pre-processing, (2) data segmentation, (3) clustering data, (4) functional modeling of the data and (5) single subject matching and scoring.

These algorithms find and measure patterns of brain activity, identify locations and measure intensity over time and lastly compare the data generated to an age-matched normative database.

Clustering data further aids in breaking down the dataset by grouping subjects based on EEG outputs and identifying key characteristics of the cluster such as age, gender, alertness or dominant hand.

As of the date of this filing, the BNA Platform has been developed and is in the early stages of a commercial launch.

We believe there is potential for such commercialization, both with respect to pharmaceutical companies in their drug research and clinical trial activities, as well as medical practitioners in their clinics.

In concert with the commercialization of BNA Platform, we are collaborating with neuroscience drug development companies to support their clinical strategies.

We plan to generate revenue through two segments:

through the use of BNA Platform by United States health care professionals and through collaborations with pharmaceutical companies in support of neuroscience drug development.

The proposed business model for healthcare provider clinics consists of a base service fee for licensing the product and a per use fee based on volume.

The proposed business model for pharmaceutical companies will be tailored to each customer based on the volume and costs associated to provide such services.

In order to commercially launch to the medical community, the company has hired sales staff, conducted soft launches into a number of strategic accounts and plans to continue marketing efforts to secure new accounts.

In the first half of 2025, the company will focus on targeted outreach and client engagement to commercialize the BNA Platform in the clinics segment.

Using its database of potential customers and external lead generating services, the company will identify key targets in select markets and connect with them through personalized emails and calls to schedule meetings with decision-makers.

The sales team, equipped with marketing materials, case studies, peer-reviewed publications, and knowledge gained from our current research partners, will present the platform’s benefits and practical applications during these meetings.

Follow-up efforts, including addressing questions and offering assistance by our Clinical Support Team, will aim to build strong client relationships and drive adoption of the platform.

The clinical utility of EEG technology to support better outcomes for patients with mental illnesses and cognitive disorders has been well documented.

Historically, clinical adoption of EEG by medical professionals, including psychiatrists, neurologists, nurse practitioners and general practitioners, has been limited due to the complexity of interpreting EEG recordings and the inability to practically compare a patient’s brain electrophysiology to that of a clinically normal age-matched patient.

Firefly believes that without defining a standard deviation to the norm, it is not possible to objectively assess brain electrophysiology.

By establishing an objective baseline measurement of brain electrophysiology, the BNA Platform enables clinicians to optimize patient care, leading to improved outcomes for people suffering from mental illnesses and cognitive disorders.

Our value proposition is supported by real-world use of the BNA Platform.

Incorporating the BNA Platform as part of a patient management protocol demonstrated improved response rates, enhanced therapy compliance, reduced non-responder rates and a reduction in need for medication switching among patients.

Further, we believe that our extensive clinical database, when combined with advanced AI, provides the opportunity to identify clinically relevant biomarkers that will support better patient outcomes through precision medicine and companion diagnostics.

We expect to gather additional data through the clinical deployments and clinical studies conducted by drug companies.

This additional data should allow us to discover new biomarkers and objectively measure the impact of therapeutic interventions on patients of different types, further enhancing our platform’s effectiveness.

We believe that we will be able to enhance accurate diagnosis and predict what therapy or drug, or a combination thereof, is best suited to optimize patient outcomes.

This represents a paradigm shift in how clinicians manage patients with mental illnesses and cognitive disorders holding the potential to transform brain health.

We are dedicated to transforming brain health with the goal of advancing diagnostic and treatment approaches for people suffering from neurodegenerative diseases, disorders, and cognitive impairment and injuries.

Firefly’s strategy is to develop state-of-the-art technologies that bridge the gap between neuroscience and clinical practice.

Firefly’s next steps to realize this strategy include:

Commercially launching the BNA Platform to medical professionals, including neurologists, psychiatrists, nurse practitioners, and general practitioners in the United States .

Firefly believes that there are significant clinical, societal, and economic benefits that maybe realized when BNA Platform is used as part of a regular patient management protocol.

Firefly aims to realize these benefits by providing medical professionals and their patients with objective, comparative data of brain electrophysiology.

Poor outcomes associated with the treatment of disorders often result from the subjective, trial and error approach to patient treatment.

Firefly believes that by providing clinicians with the ability to compare a patient’s brain electrophysiology (as defined by BNA results to its FDA-cleared normative age-matched database will give both the clinician and the patient an objective baseline comparison of their brain electrophysiology that could aid in the diagnosis and optimization of the patient’s treatment pathway.

This strategy is supported by the fact that real-world clinical use of the BNA Platform has shown that, when used as part of a patient management protocol, patients showed improved response rates, enhanced therapy compliance, and reduced non-responder rates and a reduction in the need for medication switching.

There is a strong motivation for medical professionals, looking to improve outcomes, to integrate the BNA Platform into their clinics.

The BNA Platform could be new recurring revenue stream opportunity for the medical practitioner while providing new patient management strategies.

In addition, the adoption of the BNA Platform represents an opportunity to offer a perceived competitive advantage in their market.

Performing research and clinical studies to identify clinically relevant biomarkers that could support diagnosis and possibly identify patients who are most likely to positively respond to a certain drug or treatment .

Firefly is continuously improving the BNA Platform by actively analyzing its comprehensive database, which includes clinical and behavioral data, to discover biomarkers that may support diagnosis and optimize patient care pathways.

In doing so, Firefly intends to empower the practitioners to apply principles of precision medicine to improve outcomes for people suffering from mental illnesses and cognitive disorders.

By utilizing the Company’s ML pipeline to analyze its database, it could be possible to identify patterns (EEG-based biomarkers) that are useful for predicting treatment outcomes (predictive biomarkers), predicting disease progression (prognostic biomarkers) and monitoring treatment effects (monitoring biomarkers).

Leveraging such biomarkers could inform patient selection and stratification in clinical trials in a way that could optimize trial design, leading to improved outcomes while reducing the cost and time it takes to obtain approval for the drug.

Partnering with leading drug development companies in the central nervous system ( “ CNS ” ) space in support of clinical research and companion diagnostics .

Firefly is focused on growing its CNS pharmaceutical company partnerships for drug development.

Based on the work Firefly has done with pharmaceutical companies like Novartis, Takeda Pharmaceutical Company Limited, Bright Mind Bioscience and others, Firefly believes that EEG data, processed by the BNA Platform, may be effective in CNS drug development by providing objectively measured brain activations that indicate normal or pathological neuronal processes.

The BNA-based EEG data may be used as objective endpoints for pharmacokinetic-pharmacodynamic modelling.

Moreover, by measuring electrophysiology commonly associated with cognitive functions, BNA biomarkers may also assist in understanding the drug’s effects in the cognitive domain and identifying adverse cognitive events.

By enabling a quantitative and objective measurement of the change in brain electrophysiology following a treatment, drug developers could further optimize dose selection for next phases of development.

Management believes that through integration of the BNA Platform into drug development strategies, CNS pharmaceutical companies may realize significant savings of both cost and time by understanding a drug’s effect better and targeting patients who will respond better to the drug (patient enrichment).

Improving patient targeting and effects on patient populations segments could lead to demonstrable improvement in clinical efficacy.

Many new CNS drugs being developed are considered to be high cost, often having annual costs of tens of thousands of dollars.

There is considerable resistance from healthcare providers, governments, and Insurers to absorb the high cost of new CNS drugs without knowing who is most likely to benefit from the drug.

Firefly believes that biomarkers represent a significant opportunity for drug development companies and practicing medical professionals.

For drug development companies, conducting clinical trials with patients who are more likely to respond positively to the drug (patient enrichment) may reduce the clinical trial size required to show positive clinical outcomes (efficacy) and significantly reduce the cost and speed of clinical trials.

Furthermore, the ability to show increased efficacy of the drug within a targeted patient group could expedite regulatory approval and provide justification for the cost of the new drug with payors.

In concert with Firefly’s commercialization strategy, medical professionals who integrate the BNA Platform into their clinic maybe able to prescribe the drug to their patients who will benefit the most based on the companion diagnostic criteria.

Considering strategic acquisitions .

Firefly may consider strategic acquisition opportunities where such transactions may accelerate Firefly’s market positioning through horizontal or vertical integration, expanding capacity, or gaining intellectual property that strengthens its competitive advantage.

Firefly believes that it is in a position to drive the adoption of objective assessment of brain electrophysiology in clinical practice by making the BNA Platform accessible to medical professionals in the United States and other countries around the world.

Initial clinical use of the BNA Platform has demonstrated improvements in patient outcomes.

Based on this, Firefly believes that the BNA Platform has the potential to deliver benefits within the healthcare system to a broad range of stakeholders - patients, clinicians, and payors.

Our Solution - The BNA Platform

The BNA Platform is an FDA 510(k) cleared product and is a direct result of applying data science AI and ML expertise to Firefly’s extensive proprietary database of standardized, high-definition longitudinal EEG recordings of over 18,000 (80,000 BNA assessments) patients spanning 35,000 visits representing twelve disorders, as well as clinically normal patients.

Firefly’s proprietary database will continue to grow with each use of the BNA Platform in the clinical and research settings, which, through its application of AI and ML, allow for insights to continuously evolve and improve with the goal of continually increasing the value proposition of the BNA Platform to clinicians and pharmaceutical company clients.

Firefly believes that this virtuous cycle could result in future product development, like biomarkers that can potentially drive the commercial adoption of the BNA Platform to a wider universe of medical professionals, and also enhance its value proposition to drug development companies.

The BNA Platform

The BNA Platform is intended for the post-hoc statistical analysis of the human electroencephalogram (EEG), utilizing both resting-state EEG and Event-Related Potentials (“ERP”) in a patient’s response to outside stimuli during various states of alertness, disease, diagnostic testing, treatment, surgery, or drug related dysfunction.

An ERP is an electrical potential recorded from the nervous system following the presentation of a stimulus (e.g., as part of a cognitive task).

An ERP signal consists of typical ERP components - positive or negative voltage spatiotemporal peaks within the ERP waveform that are measured within one second post-stimulus presentation.

Each ERP component reflects the activity of brain networks responsible for different cognitive functions.

The system consists of the following components:

a computer environment;

EEG data input software algorithms for BNA calculations;

a report generator and a functionality for data transfer and storage.

In the first step EEG data is measured using a dedicated, commercially available, and FDA-cleared EEG system, which complies with the BNA Platform specifications.

The BNA Platform processes and analyzes the data using Firefly’s BNA Algorithm (as further described below).

Lastly, the results are compiled into individualized reports that provide clinicians with objective insight into brain electrophysiology.

Each incremental scan further supports the growth of Firefly’s reference database.

The steps are described in further detail below.

Overview of the BNA Platform Process

Measure - EEG Data

The BNA Platform is intended to analyze EEG data recorded at rest (“Resting-EEG”) and during the performance of two conventionally used ERP tasks:

the Auditory Oddball (“AOB”) and the Visual Go-No-Go (“VGNG”).

The EEG is recorded continuously while the patient is at rest with eyes-closed or performs one of the ERP tasks.

The acquisition site is asked to provide reliable samples of artifact-free digital EEG for purposes of analysis.

After the recording, the artifact-free EEG data is automatically imported into the BNA™ Platform This is useful to clinicians as the information from the Resting-EEG and ERP tasks are complementary to each other in many ways.

The BNA Platform thus empowers clinicians by providing them with a multi-perspective, objective evaluation of the patient’s brain function in one product.

EEG Data Inputs

Analyze - The BNA Algorithm

After the recording, the artifact-free EEG data is imported into the BNA Platform and is automatically analyzed by the algorithm (the “BNA Algorithm”).

EEG and ERP data quality is assessed through an automatic calculation of various metrics (e.g., correct response, noisy/flat electrodes, length of clean signal, test-retest reliability), followed by a manual review of major issues detected during the previous process.

The BNA Algorithm detects and quantifies the characteristics of EEG and ERP peaks, and behavioral performance:

P50, N100, P200, P3a, P3b;

P200, N200, P3a, P3b).

EEG spectral analysis – absolute and relative power in delta, theta, alpha and beta frequency bands, and alpha peak frequency.

Absolute power:

the average of the raw PSD within the frequency band of interest, calculated per electrode.

Relative power:

calculated by dividing the power in each frequency band by the total power of all frequencies, per electrode.

Alpha peak frequency:

calculated as the weighted average of the frequency sample points within the alpha band (8-12 Hz), taking the power values as weights, per electrode.

AOB and VGNG Tasks – Event-Related Potential (ERP) and behavioral performance analysis.

Brain Network Analytics (BNA) is used to detect the following ERP components:

N200, P200, P3a, P3b

P50, N100, P200, P3a, P3b

BNA scores represent these ERP components in terms of amplitude (in microvolts) and latency (in milliseconds), and Neural Consistency (1- ERP variability).

Behavioral performance measurements are extracted from the AOB and VGNG tasks, including mean of accuracy, response times (with standard deviation), omission (missed responses to stimuli that required a response) and commission (incorrect responses to stimuli that did not require a response) errors.

These behavioral measures complement the ERP measures in assessing cognitive function and are included in the analysis.

The BNA Algorithm then leverages Firefly’s normative database to extract potentially clinically meaningful clinical information from EEG data.

EEG recordings are high-dimensional and complex.

This is the result of the dynamic spatiotemporal nature of the neurophysiological signals.

For example, the event-related potential wave measured at first, at a relatively focal location in time and space on the scalp, and then it evolves and propagates in the cortex while its amplitude changes simultaneously.

Traditional methods for EEG and ERP analysis follow waveform morphology over time at selected electrode locations, using either time-domain or frequency-domain tools, while neglecting the spatiotemporal dynamics associated with the electric field at the scalp.

Moreover, focusing on a specific electrode or subset of electrodes, the traditional methods ignore the expected variability between patients in terms of where the ERP component appears on the scalp due to natural differences between cortex and scalp anatomy.

The aim of the BNA Algorithm is to improve the accuracy of the ERP component detection by considering the spatiotemporal nature of the signal.

It achieves this improvement by parceling the EEG activity into major spatiotemporal events - ERP peaks and their surrounding - spatiotemporal parcels.

The key strengths of the BNA Algorithm are:

Adaptive peak detection - the ERP peaks are detected in a more patient-specific way, by incorporating some degree of freedom in both time and space in a way that is proportional to the normal variability in time and space of the ERP peaks.

Displaying ERP-peak location - due to the adaptive peak detection by the BNA Algorithm, the ERP peak is identified and displayed in the BNA report on a topographical map together with the group ERP-peak position.

This adds potentially clinically useful information to the physician.

Neural-Consistency score - another unique feature of the BNA report is the presentation of the Neural-Consistency score.

Since this is a differentiating score, the Company will describe here shortly what this score is and why Firefly believes it is important.

Since the ERP signal is an average of multiple single-trial ERP signals which can differ largely from each other, assessing the consistency between them may provide complementary functional information to the average measure.

As part of the new peak-analysis, the algorithm calculates a new score - ‘Neural Consistency’ based on the similarity of the amplitude activation between single-ERP trials.

The score is calculated based on averaging the inter-single trials variability of the ERP-peak and its surrounding points.

Act - Individualized Reports

The results of the data processed by the BNA Algorithm are compiled into individualized easy-to-read reports that provide clinicians with objective insight into brain electrophysiology:

Behavioral Report

Summary Report

Resting-EEG Report

Scores are presented as z-scores based on comparing the patient to an age-matched relevant reference group based on Firefly’s proprietary standardized longitudinal normative database.

This presentation expresses the differences between the patient and the reference group.

The reports are intended to be used by clinicians to enable the evaluation of the patient’s brain activity during a specific task compared to an age-range matched reference group.

The following diagram breaks down the components of Firefly’s normative database that underpins the BNA Platform:

Components of the BNA Platform normative database.

The BNA Platform is a clinical decision support software tool that assists with the interpretations of Resting-State EEG and ERP results, where EEG- and ERP-based examinations are indicated and carried out by a qualified health care professional.

The core of the BNA Platform is a unique reference dataset to which the individual patient is compared.

The reference database contains ERP recordings in response to the Auditory Oddball (AOB) and Visual Go No-Go (VGNG) tasks and Resting-State EEG collected from healthy volunteers.

The database also includes demographic data and relevant clinical data (based on patient self-report and medical records, neuro-psychological questionnaires when problems were suspected, urine tests to rule out drug abuse and breath tests to rule out alcohol use) enabling adjudication of brain health status.

The Reference group was generated so that each age-bin contained a sample size of at least 120 eligible cases.

For ERP analysis, groups were divided to reflect normality for similar electrophysiology The Reference-Group Database for the AOB and VGNG tasks is divided into the following age groups:

25-35, 35-50, 50-65, 65-75, and 75-85 years for VGNG, and 12-14, 14-16, 16-18, 18-25, 25-35, 35-50, 50-65, 65-75, and 75-85 years for AOB.

For the Resting-State EEG, the high volume of samples permitted the creation of reference groups in a higher 0.5-year resolution.

Each reference group includes at least 200 individuals selected by their age proximity to the declared age-range of the group.

This resulted in 133 reference groups for the ages 12-85 years.

Patients are compared to the reference group based on their age proximity to the group.

Wherever the data was normally distributed, the reports present scores as Z-Scores indicating the differences between the patient and the age-matched reference group selected from Firefly’s reference database.

A Z-Score is a statistical measure indicating how far a specific value is from the mean of the reference group.

A positive or negative Z-Score suggests that a score is bigger or smaller than the mean of the group, respectively.

The 68%, 95%, 99.7% rule specifies the percentage of scores that fall within the ranges of ± 1, ± 2, ± 3, respectively.

Figure 24 illustrates this concept.

A score outside a range of ± 2 is commonly considered potentially meaningful in the clinic.

Only about 5% of the population would have a result outside this range.

Often a score outside the range of ± 2 is considered potentially meaningful in the clinic.

The rationale for this is the statistical definition of the central 95% of a distribution as the "normal" range, causing scores to fall outside this range to be considered “extreme” ( (Crawford, 2002);

(Curtis, 2016)).

Most of the scores presented in the Behavioral Report showed a skewed distribution within the reference groups.

As a conversion into Z-Scores is not appropriate for skewed distributions, the corresponding scores are presented as raw scores and the 25th-percentile limit is marked on the report as a reference value.

The BNA Platform Database

Real-World Evidence for the BNA Platform Clinical Utility

The findings presented in 2023 white paper study “ Brain Network Analytics (BNA) in the Psychiatric Practice :

Real-Life Data Analysis ” by Charlotte Baumeister, Ph.D., with analysis by Offir Laufer, Ph.D., support the potential of the BNA Platform to transform psychiatric care by automating the analysis of EEG data.

The comprehensive research involved a cohort of 2,253 patients seeking treatment at a prominent psychiatric and multispecialty clinic in the United States.

The study demonstrated that the BNA Platform improved disease management in psychiatric patients suffering from major depressive disorder (MDD), generalized anxiety disorder (“GAD”), and ADHD.

The study has unveiled valuable insights into how the BNA Platform may revolutionize disease management in the field of psychiatry.

Key highlights from the research include:

Enhanced Treatment Compliance :

Patients grappling with depression, who underwent therapy guided by BNA, exhibited a significant 15% increase in their adherence to MDD treatment protocols, encompassing both antidepressant medications and Transcranial Magnetic Stimulation (TMS).

Decreased Medication Alteration Necessity :

The study demonstrated a noteworthy reduction of over 50% in the requirement to switch antidepressant medications among the patient population.

This emphasizes the potential of the BNA Platform in optimizing medication selection and dosing.

Amplified Improvements in General Functionality :

Individuals diagnosed with MDD, GAD, and ADHD experienced more than double the improvement in their overall general functioning when receiving BNA-guided interventions.

This suggests that BNA Platform has the potential to comprehensively enhance patients' quality of life and daily functioning.

Elevated Rates of Antidepressant Response :

The application of the BNA Platform was associated with a notable 10% increase in antidepressant response rates, signaling its potential to augment the effectiveness of traditional treatment approaches.

Reduction in Non-Responder Rates :

Among MDD patients, the study observed a significant 17% decrease in the rate of treatment non-responders, indicating that the BNA Platform holds promise in mitigating treatment resistance and improving positive outcomes.

The study thus demonstrated that the BNA Platform represents a potentially significant advancement in patient care in a real world setting and addresses some of the challenges associated with EEG utilization by medical professionals.

By automating EEG analysis and providing comprehensive insights into brain electrophysiology, the BNA Platform has the potential to revolutionize disease management, enhance treatment outcomes, and improve the overall well-being of patients with mental illnesses and cognitive disorders.

Based on the real-world results highlighted above, Management believes that the societal impact of better outcomes for patients suffering from mental illnesses and cognitive disorders is substantial and the associated cost savings to healthcare systems and payors could be significant.

Firefly intends to study the potential health economic benefits associated with the above findings to support rapid adoption of the BNA Platform into standard patient management protocols.

Research and Development

Firefly focuses its research and development efforts on advancing the treatment of patients suffering from mental illnesses and cognitive disorders.

These efforts may be enhanced by the relationships that Firefly has developed with neurologists, psychiatrists, neuroscientists, and other experts.

Firefly believes the BNA Platform may drive a better standard of care for patients suffering from mental illnesses and cognitive disorders.

Firefly’s research and development activities may encompass basic research and product development.

Firefly’s research and development team has biomedical engineering, neuroscience, software development, project management, data science, and AI and ML expertise.

Firefly believes the strength and strategic vision of its research and development team will continue to drive Firefly’s leadership position in the category of advancing the understanding of brain electrophysiology in support of better outcome for Firefly’s target patient population leveraging EEG hardware with the BNA Platform.

Firefly’s near-term research and development efforts are focused on continuing to improve the BNA Platform, enhancing the patient and provider experience, and expanding the population of patients that can be assessed with the BNA Platform.

Since inception, Firefly’s research and development activities have resulted in significant improvements to the BNA Platform, Firefly’s first clearance and predicate device to the BNA Platform dates back to 2014 when Firefly received Class II medical device 510(k) clearance from FDA for the BNA Analysis System, with indication for use in individuals 14 to 24 years of age.

In December 2020, Firefly received Class II medical device 510(k) clearance from the FDA for Firefly’s current product, the BNA Platform, with indication for use in individuals 12 to 85 years of age.

Additionally, Firefly’s near-term development pipeline includes potential enhancements that leverage its normative database, growing the database, advanced data analysis, ML and AI capabilities to enable medical professionals to enhance their clinical assessments, and to enable drug development companies to improve the success of their drug development programs, potentially bringing new drugs to market faster while reducing the cost and risk.

Market Opportunity

The market for the BNA Platform and Firefly’s future products is vast and growing significantly.

According to the World Health Organization, in 2019, 1 in every 8 people, or 970 million people around the world were living with a mental disorder, with anxiety and depressive disorders being the most common.

The economic burden of people suffering from depression alone in the United States was estimated at $326.2 billion for the year 2020.

As our societies age, the number of cases of mental illness and cognitive disorders is projected to increase, along with the associated economic costs.

For example, the number of people with dementia is estimated to increase from 57.3 million cases globally in 2019 more than 150 million cases in 2050.

Yet, despite the growing need for effective treatment and substantial unmet treatment needs, CNS drug development remains costly, with the cost of developing a new drug typically ranging from $10 to 15 billion per drug, with CNS drugs having the lowest success rate of all other drug categories.

One of our initial areas of commercial focus will be on the sale of the BNA Platform to neurologists in the United States.

Based on assumptions regarding the use of the BNA Platform by neurologists in the United States, this market segment potentially represents a total addressable market (TAM) of approximately $800,000,000 based on the following figures (based on the number of neurologists in the United States currently performing EEGs, the number of times such neurologists may perform a BNA analysis and approximate number of working days per year, summarized as follows).

According to data from Definitive Healthcare for 2023, there are 22,115 neurologists in the United States, of which 8,278 are currently performing EEGs.

Our business model and TAM assumes that neurologists in the United Sates currently performing EEGs will perform a BNA analysis on average of two times per day over approximately 250 working days per year.

Currently, our model assumes that a clinician will be invoiced approximately $200 for each BNA analysis.

Firefly believes that improving outcomes for people suffering from mental illnesses and cognitive disorders requires objective measurement.

The clinical benefit of using EEG to understand how a person’s brain is functioning has been studied for decades.

However, Firefly believes that, due to the complexity and time required to analyze and interpret EEG recordings, the inability to compare EEG recordings to what is clinically normal, and the inability to track changes over time, the clinical use of EEG has been limited.

The BNA Platform holds the potential to transform brain health by allowing integration of EEG testing and analysis into patient care pathways to provide clinicians with an objective tool that may help them diagnosis and assess treatment efficacy, objectively and quickly.

In addition, through Firefly’s research and development initiatives, the Company believes that by introducing biomarkers that could diagnose illnesses or disorders, it would assist in identifying what treatment will provide the most benefit for the patient and may drive adoption by clinicians and payors.

Through ongoing research of Firefly’s growing database, using the BNA Platform, Firefly aspires to enter other markets including, executive medical health and wellness for consumers who want to more actively manage their healthcare and lifestyles.

Firefly plans to offer its BNA Platform on a recurring revenue model basis.

In addition, Firefly plans to provide EEG recording equipment on a monthly rental or purchase basis or as part of a bundle price.

Driving adoption in the specialty of neurology may enable Firefly to reach its full potential.

For this reason, Firefly plans to initially adopt a direct selling model that is supported by field based clinical specialists and medical affairs personnel.

As adoption progresses, supported by clinical validation, biomarkers and improvements to the BNA Platform, Firefly aims to partner with national distributors that complement Firefly’s target markets, including EEG companies and installed bases of EEG systems in use today by medical professionals.

In concert with the commercialization of the BNA Platform to medical professionals, Firefly plans to actively engage with drug development companies and develop extensive strategic partnerships to support their drug development strategies.

As of January 1, 2023, there were 187 trials assessing 141 unique treatments for Alzheimer’s disease.

As of January 4, 2023, there were more than 160 pharmaceutical companies developing drugs to treat mental illnesses.

In order to take full advantage of the opportunity in the CNS drug development market, Firefly intends to invest in business development resources focused on the CNS drug development sector.

Firefly’s industry is competitive and has been evolving rapidly with the introduction of new products and technologies as well as the market activities of industry participants.

The BNA Platform is indicated for use in individuals 12 to 85 years of age for the post-hoc statistical analysis of the human electroencephalogram, including event-related potentials and Firefly currently markets its device to qualified medical professionals.

Firefly competes against other companies that have developed AI-driven platforms, in the target market of neurological disorders.

Firefly believes that the BNA Platform is a paradigm shift on the approach to treating cognitive disorders, mental illnesses, injuries to the brain and degenerative diseases.

Firefly’s believes its BNA Platform offers distinct advantages, including its FDA-cleared BNA Algorithm for data analysis, its proprietary extensive normative age matched database underpinning the BNA Platform, and the ability of the BNA Platform to generate individual reports that clinicians may use to optimize patient care.

Firefly believes the BNA Platform may become a standard of care tool in addressing the primary unmet needs in mental illness and cognitive disorders today.

Firefly also believes that the BNA Platform has a wide range of additional applications, including the ability to leverage data gathered through BNA sessions for additional clinical insight, pharmaceutical drug development and new product development.

The longitudinal nature of the data, along with clinical disease context, provides many future development opportunities.

Furthermore, EEG technology, in concert with BNA Platform, represents a scalable, low-cost solution when compared to other imaging technologies that assess brain electrophysiology, such as functional magnetic resonance imaging (fMRI).

Firefly Neuroscience, Inc.

is an artificial intelligence company advancing precision neuroscience, applying AI and large-scale electrophysiological data to give clinicians a more complete, objective picture of how an individual patient's brain is functioning.

Firefly Neuroscience, Inc.

is rebuilding the foundation of how electrophysiological data flows into clinical decision-making for brain health.

We believe the brain is the most under-measured organ in medicine, and that the tools to change this have, until now, been inaccessible to the clinicians who need them most.

We have built the Firefly Platform:

a vertically integrated hardware, software, and data infrastructure that captures standardized electroencephalographic (EEG) and event-related potential (ERP) assessments at the point of care, analyzes that data through our proprietary analytics engine, and delivers structured, clinician-ready reports back to the provider, all within a single seamless workflow.

Every scan expands and enriches our database.

Every clinic that joins our network increases the depth and diversity of our data.

We describe this compounding relationship between clinical deployment, data acquisition, and report quality as the Firefly Flywheel.

Our FDA-510(k) cleared Evoke System, commercially deployed as the Evoke System, is in active use across more than 85 clinical sites in the United States as of December 31, 2025.

Clinicians use the system to perform EEG and ERP assessments, which are analyzed by our cloud-based platform and returned as structured reports designed to support clinical decision-making.

Our subscription-based commercial model creates a recurring revenue stream that scales in lockstep with clinical utilization, meaning that the more deeply clinicians integrate electrophysiological assessment into their practice, the more revenue we generate and the more our database grows.

The Firefly Flywheel — each clinical assessment simultaneously generates revenue and expands our proprietary database, compounding the intelligence of every future report.

The Problem We Are Solving

Clinicians treating neurological and psychiatric conditions have access to a range of assessment tools, including standardized cognitive and behavioral rating instruments such as the Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), the Generalized Anxiety Disorder scale (GAD-7), and the Patient Health Questionnaire (PHQ-9).

These tools provide valuable, reproducible data points and play an important role in clinical evaluation.

However, they assess behavior, self-reported symptoms, and observable cognitive performance;

they do not directly measure the underlying functional activity of the brain.

As a result, clinicians may have a clear picture of how a patient is presenting clinically, but limited visibility into what is occurring at the neural level:

which regions of the brain are deviating from expected activity for a patient of that age, and in which direction.

The Evoke System is designed to provide exactly this additional layer of insight;

to add a direct electrophysiological signal that complements other testing modalities and gives clinicians a more complete biological picture to inform treatment planning.

We believe four structural problems define the current state of brain health diagnostics, and that Firefly is uniquely positioned to address each of them:

Adding electrophysiological insight to existing assessments.

While standardized rating scales such as the MoCA, MMSE, GAD-7, and PHQ-9 provide reproducible and clinically valuable data, they measure cognitive performance and self-reported symptoms rather than the direct electrical activity of the brain.

Electrophysiological assessment captures what these tools cannot:

which neural circuits are active, how quickly they respond, and how a given patient's brain activity compares to a reference group.

The Evoke System adds this direct biological signal to the clinical picture, helping clinicians understand not just how a patient is presenting, but what is measurably occurring in their brain.

Population-level context at the point of care.

A clinician evaluating a patient's brain activity in isolation may not have a population-level frame of reference for what they are seeing.

Our analytics platform addresses this by comparing each patient's electrophysiological data against a reference group;

giving clinicians a standardized benchmark that reflects what healthy brain activity typically looks like for a patient of that age and gender.

As our database continues to grow, we expect to expand the granularity of these reference populations over time, with the goal of enabling comparisons across increasingly specific clinical subgroups.

The foundation for that future capability is being built with every assessment performed on our network today.

Late detection of cognitive and neurological disease.

Many of the most debilitating neurological conditions;

including Mild Cognitive Impairment (MCI), early-stage Alzheimer's disease, and prodromal psychiatric disorders;

progress substantially before they are clinically detectable through behavioral observation alone.

Electrophysiological biomarkers captured by EEG and ERP can surface neurological change earlier, giving clinicians a window to intervene before disease progression accelerates.

Imprecise treatment selection.

Even when a diagnosis is established, selecting the right treatment plan often remains a process of elimination.

Our growing database is enabling the identification of electrophysiological subtypes within diagnostic categories;

meaning that a patient's specific EEG/ERP signature may predict which therapy is most likely to produce a meaningful response, potentially reducing the time and cost of trial-and-error prescribing.

The Firefly System

The Firefly System is a closed-loop system designed to continuously improve with use.

It combines three interdependent layers:

standardized hardware acquisition through the Evoke System, cloud-based electrophysiological analytics, and a growing proprietary data repository.

Each layer reinforces the others, and the system as a whole, we believe, becomes more beneficial with every assessment performed across our network.

The Evoke System

The Evoke System is our FDA-510(k) cleared EEG and ERP acquisition hardware and associated software, deployed in clinical settings across the United States under the commercial brand name Evoke System.

The system is purpose-built for standardized electrophysiological assessment in clinical environments;

not limited to research laboratories;

and is designed to be operable by clinical staff without specialized neurophysiology training.

The Evoke System captures brain activity using a 19-channel EEG electrode array configured according to the International 10-20 system, the clinical standard for electrode placement.

In addition to the cortical EEG signal, the system incorporates a Heart Rate Variability (HRV) sensor, enabling simultaneous measurement of autonomic nervous system function alongside neural activity.

This multimodal data capture;

cortical EEG across 19 channels plus HRV;

provides a richer physiological signal than single-modality approaches, and we believe distinguishes our hardware from more limited EEG-only assessment tools.

Evoke System hardware configuration — 19 EEG electrode channels (10-20 system) plus integrated HRV sensor for multimodal brain and autonomic nervous system measurement.

The Evoke System captures two principal categories of electrophysiological data.

Resting-state EEG records spontaneous neural oscillatory activity in the absence of deliberate stimulation, providing a baseline measure of brain network function.

Event-Related Potentials (ERPs) are captured during cognitive task paradigms, measuring the brain's time-locked electrical responses to specific stimuli across standardized cognitive task types.

Together, resting EEG and ERPs enable assessment of up to 20 distinct cognitive functional measures per session;

including early sensory processing, attention, working memory, response inhibition, and executive function.

The standardized nature of the Evoke System's acquisition protocol is a critical design requirement, not merely a technical characteristic.

Our analytics engine compares each patient's data against a reference database.

As our database continues to grow, every assessment will add further clinical value.

The Evoke System's standardized protocol enables this comparability, ensuring that each record entering our database can meaningfully inform the interpretation of future assessments.

Analytics Engine — Assessment and Reporting

Electrophysiological data captured by the Evoke System is transmitted to our cloud-based analytics platform for processing.

Our proprietary analytics engine analyzes raw EEG and ERP signals across captured dimensions and compares each patient’s electrophysiological profile to a reference dataset.

As our dataset expands, we intend to further stratify and refine reference comparisons, which may include demographic segmentation, condition-specific cohorts, and longitudinal outcome data, subject to data availability and applicable regulatory considerations.

The output of this analysis is a structured clinical report delivered to the clinician.

This report contextualizes the patient's electrophysiological data relative to a reference database, surfacing deviations in signal characteristics that may be relevant to the clinician’s assessment.

Reports are delivered through our cloud-based portal and are designed to integrate into clinical workflows.

As more assessments are added, the database becomes richer and more diverse;

broadening the body of data against which future assessments may be contextualized and supporting our longer-term goal of developing more granular reference populations for specific clinical subgroups.

The Firefly Database

Our proprietary database, which includes more than 191,000 standardized EEG and ERP assessment records, represents a significant long-term strategic asset of our business.

We continue to analyze and expand this dataset to enhance our understanding of electrophysiological patterns associated with cognitive function.

Over time, we believe that further analysis of this data may support the development of more refined reference populations, including condition-specific cohorts, and may contribute to the identification of potential electrophysiological biomarkers.

Proprietary database growth — records added quarterly through commercial clinical deployment, research collaborations, and clinical trials

The database spans over 12 distinct neurological and psychiatric disorders and includes records from more than 100,000 patients.

We believe there may be value in collecting longitudinal data that enables analysis of how electrophysiological signatures change with disease progression and in response to treatment.

The database also includes records from healthy individuals across the age range of 12 to 85.

The 12+ neuropsychiatric disorder categories represented in Firefly's proprietary EEG/ERP database.

Each assessment performed at any site using the Evoke System enters our data pipeline and, subject to appropriate rules and regulations, may be incorporated into our reference database.

Commercial deployment and database growth are not separate activities, they are complementary, simultaneously generating subscription revenue and expanding the data asset that makes our platform more valuable over time.

Our Commercial Model

We sell access to the Firefly Platform through a tiered subscription model.

Clinics pay a monthly subscription fee that provides access to the Evoke System, a defined volume of assessments per month, and access to our analytics and reporting platform.

Assessments performed in excess of the monthly allotment are billed at a per-scan overage rate, ensuring that our revenue scales proportionally with clinical utilization.

Multiple subscription tiers are available to accommodate the diverse utilization profiles of our clinical customers;

from individual practitioners performing a modest number of monthly assessments to larger multi-provider clinics or health systems with significantly higher throughput.

This structure allows us to serve a broad range of clinical settings while ensuring pricing is calibrated to the value delivered.

As a clinic's utilization grows, the subscription structure encourages migration to higher tiers, providing natural revenue expansion within our existing customer base.

Clinical Applications

Supporting Clinical Decision-Making

The Evoke System's primary clinical application is providing an objective electrophysiological layer to complement the assessment tools clinicians already use.

Standardized instruments such as the MoCA, MMSE, PHQ-9, and GAD-7 are well-established components of neuropsychiatric evaluation, capturing how a patient performs on cognitive tasks and how they report experiencing mood, anxiety, and daily functioning.

The Evoke System adds a direct measurement of the brain's electrical activity;

capturing the speed, amplitude, and pattern of neural responses during rest and cognitive tasks, contextualized against a reference group.

By returning structured reports that map a patient's electrophysiological profile against our reference group, we give clinicians an additional dimension of biological evidence to inform diagnostic and treatment planning decisions.

The database includes over 12 disorder categories, including depression, anxiety, ADHD, PTSD, MCI, dementia, Parkinson's disease, bipolar disorder, schizophrenia, schizoaffective disorder, ASD, and traumatic brain injury.

Early Detection of Cognitive Decline

We believe a clinically significant application of our platform is the early identification of cognitive impairment.

Our database includes electrophysiological records spanning the spectrum from clinically normal cognition through Mild Cognitive Impairment (MCI) to confirmed dementia and early Alzheimer's disease.

Research utilizing our platform and database;

including a peer-reviewed study examining the differential electrophysiological signatures of MCI versus depression;

which has demonstrated that EEG and ERP biomarkers can differentiate between stages of cognitive impairment with meaningful clinical utility.

The ability to distinguish between conditions with overlapping clinical presentations;

such as cognitive decline due to early neurodegeneration versus cognitive symptoms secondary to depression;

we believe is a valuable application of our technology.

Clinicians already use standardized cognitive assessments such as the MoCA and MMSE to evaluate cognitive performance, and mood instruments such as the PHQ-9 and GAD-7 to assess depressive and anxiety symptoms.

These tools are clinically important, but they assess how a patient performs and feels;

not what is measurably occurring in the patient's brain.

Our platform adds a direct electrophysiological dimension to this clinical picture:

identifying the specific frequency bands, neural regions, and response latencies that deviate from norms, and contextualizing those deviations against the electrophysiological signatures of previously assessed patients across both diagnostic categories.

This combination of behavioral assessment and direct neural measurement is designed to give clinicians a richer, more complete basis for clinical judgment.

Early detection of MCI and related conditions is particularly impactful because the range of available interventions;

lifestyle, pharmacological, and enrollment in clinical trials studying disease-modifying therapies;

we believe is broadest in the earliest stages of disease.

We believe the Evoke System may enable clinicians to identify electrophysiological changes consistent with early cognitive decline through a non-invasive, cost-effective assessment that can be administered in a standard clinical setting, without the expense or logistical complexity of PET imaging or other advanced neuroimaging modalities.

Treatment Selection and Longitudinal Monitoring

As our database scales, we may focus on treatment selection support.

Research utilizing our electrophysiological data has begun to identify signatures associated with differential responses to specific therapeutic interventions.

For example, EEG-based endophenotyping in ADHD has demonstrated that patients with excess theta activity in specific frequency bands tend to respond differently to stimulant medications than patients with excess beta activity;

an electrophysiological signal that may guide initial treatment selection before a trial-and-error prescribing process begins.

This capability may continue to evolve as our database expands.

We are actively investing in research to develop and validate electrophysiological biomarkers of treatment response across additional conditions in our clinical footprint, and we believe as our database scales, it may provide a statistical foundation for this research that is not replicable from smaller, less standardized datasets.

The Evoke System also supports longitudinal monitoring.

Repeated assessments of the same patient over time that allow clinicians to track how electrophysiological profiles change in response to treatment.

This capability transforms the electrophysiological assessment from a one-time diagnostic event into an ongoing clinical monitoring tool, increasing the frequency with which clinicians engage with our platform and correspondingly increasing both revenue and database contribution per patient.

Research & Development

Scientific validation is central to our commercial strategy.

We believe that clinician adoption of electrophysiological assessment as a standard component of neuropsychiatric care depends not only on the clinical utility of our platform, but on the depth and quality of the scientific evidence supporting it.

Accordingly, we invest in research collaborations, clinical studies, and academic partnerships designed to generate peer-reviewed evidence for the applications of our technology.

Combined across Firefly Neuroscience and the former Evoke Neuroscience, our technology and dataset have been the subject of more than 20 peer-reviewed publications in indexed scientific journals.

These publications span a range of conditions and applications, including early-stage Parkinson's disease detection, ADHD endophenotyping and treatment response prediction, major depressive disorder and cognitive biomarkers, traumatic brain injury assessment, drug pharmacodynamics in neuropharmacology trials, and genetic conditions affecting cognitive development.

Select highlights from our published research include:

Early Parkinson's Detection:

A machine learning approach utilizing ERP-derived features from our database identified a neuromarker discriminating early-stage Parkinson's disease patients from healthy controls with an AUC of 0.79, sensitivity of 0.74, and specificity of 0.73;

demonstrating the capacity of our electrophysiological dataset to support early detection of neurodegenerative disease (PLOS ONE, 2022).

MDD Treatment Monitoring:

A pilot study published in the Journal of Affective Disorders Reports (2024) demonstrated that EEG-based assessments using our platform could objectively measure cognitive changes in outpatients with major depressive disorder during treatment with vortioxetine;

with baseline brain activation latencies normalizing toward healthy control levels following treatment, independent of antidepressant effect.

Neuropharmacology Biomarkers:

Collaborative research with Novartis evaluated the pharmacodynamic effects of MIJ821 (onfasprodil) using our EEG analytics as an objective CNS biomarker in a Phase I first-in-human study, published in Clinical and Translational Science (2023).

ADHD Endophenotyping:

Published research demonstrated that electrophysiological activity flow patterns analyzed through our platform can differentiate ADHD subtypes with implications for treatment selection, including differential prediction of stimulant medication response (Psychological Medicine, 2017).

Concussion and TBI:

Multiple publications, including work conducted in collaboration with university athletic programs and the Concussion Assessment, Research and Education (CARE) consortium, have demonstrated the utility of ERP-based assessments for objective evaluation of sport-related concussion and tracking of post-concussion recovery.

Reches, A., Kutcher, J., Elbin, R.J., Or-Ly, H., Sadeh, B., Greer, J., McAllister, D.J., Geva, A.B., & Kontos, A.P.

Differential Diagnosis — MCI vs.

Published research utilizing the Evoke platform has examined the differential electrophysiological signatures of MCI, early-stage Alzheimer's disease, and dementia — demonstrating the potential of EEG/ERP biomarkers to support differential diagnosis in conditions that are clinically challenging to distinguish.

Ganapathi et al.

Journal of Alzheimer's Disease, 91(1), 293–305.

We also conduct academic research collaborations, including a collaboration with the Institute of Human Genetics at Heidelberg University Hospital on EEG biomarker research in genetic neurodevelopmental conditions, and with the Pacific Neuroscience Institute Brain Center on a clinical study examining the electrophysiological signatures of Alzheimer's disease.

We view these collaborations as complementary to our commercial network, generating peer-reviewed scientific evidence that supports clinician adoption of our platform while simultaneously contributing high-quality, protocol-driven records to our database.

Pharmaceutical and Research Partnerships

In addition to our clinical subscription business, we engage with pharmaceutical companies and academic research institutions that seek access to our electrophysiological database and/or analytical capabilities in support of neuroscience drug development.

These engagements typically involve the use of our EEG and ERP analytics as biomarker endpoints in clinical trials, providing pharmaceutical sponsors with an objective electrophysiological measure of drug effect on the central nervous system.

The use of EEG and ERP as pharmacodynamic biomarkers in CNS drug development is a well-established scientific approach, and the availability of a large, standardized normative and disorder-specific reference dataset we believe significantly enhances the interpretability of electrophysiological biomarker data in drug trials.

We believe our database scale and the quality of our analytics engine position us as a preferred partner for pharmaceutical sponsors seeking to incorporate electrophysiological biomarkers into neuropsychiatric drug development programs.

Regulatory Matters

The Evoke System has received FDA clearance under the 510(k) pathway as a Class II medical device for the acquisition, display, and storage of EEG and ERP data, and for associated analytical and reporting functions.

This clearance permits commercial marketing and sale of the Evoke System for its cleared indications in the United States and is a prerequisite for our clinical subscription deployment model.

Our analytics platform generates reports for clinician review and is designed to operate as a decision-support tool.

We intend to engage proactively with the FDA as our analytical capabilities evolve to ensure our regulatory posture remains appropriate to the clinical applications of our platform.

The market for brain health diagnostics and clinical decision-support tools includes traditional EEG hardware manufacturers, digital health companies offering neurology-focused software, and academic medical centers with research-grade electrophysiological assessment capabilities.

We believe, however, that the most significant long-term competitive determinant in this market will be the depth and quality of the proprietary electrophysiological dataset underlying AI-driven analytics;

and on this dimension we believe we hold a substantial and growing advantage.

Structural neuroimaging modalities;

including computed tomography (CT), magnetic resonance imaging (MRI), and functional MRI (fMRI);

are well-established and clinically important tools for evaluating brain structure and, in the case of fMRI, patterns of metabolic activity.

CT imaging involves exposure to ionizing radiation and provides excellent resolution of structural abnormalities, but limited visibility into functional neural dynamics.

MRI offers superior soft-tissue contrast and structural detail without radiation, and fMRI can approximate regional brain activity through blood-oxygen-level-dependent (BOLD) signals.

These are valuable tools, and we view them as complementary to, rather than competitive with, electrophysiological assessment.

EEG and ERP capture the brain's direct electrical activity at millisecond-level temporal resolution;

a dimension of brain function that structural and hemodynamic imaging modalities are not designed to measure.

MRI reveals the brain’s structure, while EEG measures its real-time electrical activity and the speed at which it processes information.

We believe different test modalities answer different clinical questions and are most powerful when considered together.

From a practical standpoint, the Evoke System also occupies a distinct access tier relative to neuroimaging equipment.

MRI and CT scanners require significant capital investment, specialized facility infrastructure, and dedicated radiology or imaging staff, making them primarily available in hospital and large outpatient settings.

The Evoke System is designed to operate in standard clinical environments;

psychiatric practices, neurology offices, and behavioral health clinics;

at a cost per assessment that is generally lower than most structural imaging studies.

This accessibility profile means the Evoke System may be able to reach patient populations and clinical settings where advanced neuroimaging is not routinely available, rather than competing directly for the same clinical indication.

We believe our data advantage, combined with our FDA-cleared hardware platform deployed across more than 85 clinical sites, our intellectual property portfolio, and our growing body of more than 20 peer-reviewed publications, leads us to believe we occupy an increasingly valuable position in the brain health diagnostics market.

Human Capital

Our team spans neuroscience, biomedical engineering, signal processing, artificial intelligence, clinical operations, and healthcare commercialization.

We believe our ability to attract and retain talent with deep expertise across these complementary disciplines is essential to the continued development and commercialization of the Firefly Platform.

Intellectual Property

Firefly’s commercial success depends in part on its ability to obtain and maintain intellectual property protection for the BNA Platform and any future products, to prevent others from infringing, misappropriating, or otherwise violating its intellectual property rights, to defend and enforce its intellectual property rights, and to operate without infringing, misappropriating, or otherwise violating valid and enforceable intellectual property rights of others.

Firefly actively seeks to protect intellectual property that it believes is important to its business, which includes patents covering the components of the BNA Platform and the methods used for optimizing the therapy that the BNA Platform delivers.

Firefly’s commercial success depends in part on its ability to obtain and maintain intellectual property protection for Firefly’s products and any future products, to prevent others from infringing, misappropriating, or otherwise violating its intellectual property rights, to defend and enforce its intellectual property rights, and to operate without infringing, misappropriating, or otherwise violating valid and enforceable intellectual property rights of others.

Firefly actively seeks to protect intellectual property that it believes is important to its business, which includes patents covering the components of its software and the methods used for optimizing the assessments its products perform.

Firefly also seeks patent protection for other processes and inventions that are commercially or strategically important to developing and maximizing the value of its enterprise.

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Firefly relies on a strategy that combines the use of patents, trademarks, trade secrets, know-how, and license agreements, as well as other intellectual property laws, employment, confidentiality and invention assignment agreements, and contractual protections, to establish and protect its intellectual property rights.

Our patents and patent applications assert claims generally related methods and systems.

Specifically, there are multiple patent families relating to (i) ERP processing algorithms and the comparison to a reference group and estimation of brain electrophysiology based on the comparison;

(ii) prediction of TMS treatment outcome;

(iii) method and system for estimating brain concussion;

(iv) method and system for managing pain;

(v) method for brain stimulation tool configuration.

As of December 31, 2023, we owned eight issued U.S.

As of December 31, 2025, we owned 23 issued U.S.

patents, which have expiration dates ranging from November 2028 to November 2037.

We own one issued patent in Japan and there are currently patent applications pending in each of Australia, Canada, China, European Union and Israel, which, if issued, are expected to expire in 2037.

The anticipated expiration dates are without taking into account all possible patent term adjustments, extensions, or abandonments, and assuming payment of all appropriate maintenance, renewal, annuity, and other governmental fees.

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Our breach of any license agreements or failure to obtain a license necessary to our business may have a material adverse impact on us.

Our trademark portfolio is designed to protect the brands of our BNA Platform and any future products.

Our trademark portfolio is designed to protect the brands of our current and any future products.

As of December 31, 2025, we own one trademark registration for “BNA” in the United States and other countries, including Israel, Switzerland, European Union, Canada, and India.

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Manufacturing

Our BNA Platform is hardware-agnostic and we do not manufacture any compatible hardware.

As of March 31, 2025, we have thirteen full-time employees and one contractor.

Our Evoke system is manufactured by a third party contract manufacturer based in the United States.

As of the date of this report, we have 17 full-time employees.

None of Firefly’s employees are represented by a labor union or covered by collective bargaining agreements, and Firefly considers its relationship with its employees to be good.

Government Regulation

Our products (including our BNA Platform) are considered medical devices, and, accordingly, are subject to rigorous regulation by government agencies in the United States and other countries in which we intend to sell our products.

Our products are considered medical devices, and, accordingly, are subject to rigorous regulation by government agencies in the United States and other countries in which we intend to sell our products.

These regulations vary from country to country but cover, among other things, the following activities with respect to medical devices:

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Approved PMAs can include post-approval conditions and post-market surveillance requirements, analogous to some of the special controls that may be imposed on Class II devices.

Our BNA Platform is a Class II medical device, which was cleared by FDA for commercialization in the U.S.

pursuant to the 510(k) notification process for the post-hoc statistical analysis of the human electroencephalogram, including ERP in December 2020.

The marketing and distribution of the BNA Platform, is subject to continuing regulation and enforcement by FDA and other government authorities, which includes product listing requirements, medical device reporting regulations.

Our BNA Platform and Evoke System are Class II medical devices, which were cleared by FDA for commercialization in the U.S.

pursuant to the 510(k) notification process.

The marketing and distribution of Firefly’s products are subject to continuing regulation and enforcement by FDA and other government authorities, which includes product listing requirements, medical device reporting regulations.

If FDA finds that we have failed to comply with any legal or regulatory requirements, it or other government agencies may institute a wide variety of enforcement actions against us, ranging from Warning Letters to more severe sanctions, including but not limited to financial penalties, withdrawal of 510(k) clearances already granted, and criminal prosecution.

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In September 2014, the company received the Conformity European approval for the BNA Platform allowing use in European Economic Area.

In December 2020, Firefly received Class II medical device 510(k) clearance from the FDA for the BNA Platform, with indication for use in individuals 12 to 85 years of age.

On April 13, 2022, the name of Elminda Inc.

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and Elminda Ltd, respectively, to “Firefly Neuroscience, Inc.” and “Firefly Neuroscience Ltd.”, respectively.

On the August 12, 2024, pursuant to the Merger Agreement, FFN merged with and into Firefly Neuroscience, Inc., with Firefly Neuroscience, Inc.

On August 12, 2024, pursuant to the Merger Agreement, FFN merged with and into Firefly Neuroscience, Inc., with Firefly Neuroscience, Inc.

surviving the merger as a wholly owned subsidiary of WaveDancer, Inc.

On the Closing Date (i) pursuant to the Amended and Restated Certificate of Incorporation of WaveDancer, we changed our name to Firefly Neuroscience, Inc.

On the Merger Closing Date (i) pursuant to the Amended and Restated Certificate of Incorporation of WaveDancer, we changed our name to Firefly Neuroscience, Inc.

and (ii) pursuant to an amendment to its Certificate of Incorporation, Firefly changed its name to Firefly Neuroscience 2023, Inc.

and (iii) Firefly and FFN filed the Certificate of Merger with the State of Delaware.

The Amended and Restated Certificate of Incorporation and the Amended and Restated Bylaws contain certain provisions relating to limitations of liability and indemnification of directors and certain officers, provide advance notice procedures for stockholder proposals at stockholder meetings, and other matters.

On April 30, 2025, Firefly completed the acquisition of Evoke Neuroscience Inc.

(“Evoke”), which resulted in the acquisition of the Evoke business and a significant expansion of business operations and headcount.

This acquisition included the Evoke System which was Evoke's primary commercial product.

The Charter and the Bylaws contain certain provisions relating to limitations of liability and indemnification of directors and certain officers, provide advance notice procedures for stockholder proposals at stockholder meetings, and other matters.

See “ Description of Capital Stock – Anti-Takeover Provisions ” in Exhibit 4.1 to this Annual Report on Form 10-K and Item 10.

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Compared sentence by sentence after normalising whitespace, quotation marks, case and digits, so re-formatting and restated figures do not read as changed language. Wording changes appear as one removal and one addition. The current filing and the prior one are authoritative.

What changed 10-K

Item 1. Business