Recursion Pharmaceut...
NasdaqGS:RXRX
$
4,66
$
$-0,04 (-0,85%)
4,66
$
$-0,04 (-0,85%)
End-of-day quote: 01/09/2026
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Recursion Pharmaceuticals Company Info
EPS Growth 5Y
27,12%
Market Cap
$2,43 B
Long-Term Debt
$0,00 B
Short Interest
7,31%
Annual earnings
02/27/2026
Dividend
$0,00
Dividend Yield
0,00%
Founded
2013
Industry
Country
ISIN Number
Website
Analyst Price Target
$7,00
50.21%
Last Update: 01/11/2026
Analysts: 7
Highest Price Target $11,00
Average Price Target $7,00
Lowest Price Target $3,00
In the last five quarters, Recursion Pharmaceuticals’s Price Target has fallen from $21,21 to $11,57 - a -45,45% decrease. Eight analysts predict that Recursion Pharmaceuticals’s share price will increase in the coming year, reaching $7,00. This would represent an increase of 50,21%.
Top growth stocks in the health care sector (5Y.)
What does Recursion Pharmaceuticals do?
Recursion Pharmaceuticals, Inc (Recursion) operates as a clinical stage TechBio company decoding biology and chemistry to industrialize drug discovery.
The Recursion Operating System (OS) integrates ‘Real World’ data generated in the company's own wet laboratories or by select partners, and a ‘World Model’, which is a collection of AI computational models the company also builds in-house. The company's scaled ‘wet-lab’ biology, chemistry, and patient-centric experimental data feed its ‘dry-lab’...
Recursion Pharmaceuticals, Inc (Recursion) operates as a clinical stage TechBio company decoding biology and chemistry to industrialize drug discovery.
The Recursion Operating System (OS) integrates ‘Real World’ data generated in the company's own wet laboratories or by select partners, and a ‘World Model’, which is a collection of AI computational models the company also builds in-house. The company's scaled ‘wet-lab’ biology, chemistry, and patient-centric experimental data feed its ‘dry-lab’ computational tools to identify, validate, and translate therapeutic insights, which it can then validate in its wet lab to both advance drug discovery programs, and to generate data to further refine its world model.
The Recursion OS – A Platform that Powers a Portfolio
The Recursion OS is a full-stack solution delivering technology-enabled molecules with speed, efficiency, and scale from target discovery through early clinical development. The company generates and aggregates enormous quantities of high-quality, high-dimensional data spanning hundreds of millions of cellular perturbations across biology and chemistry, translational experiments, ADMET experiments, in vivo experiments, patient data, and from scaled automated chemical synthesis. In parallel, the company has built foundation models that leverage those data to learn and understand the underlying biological and chemical interactions with broad predictive capabilities.
The company is generating, aggregating, or simulating data from patients to cells, cells to pathways, pathways to proteins, proteins to atomistic interactions, cells to organoids, organoids to animals, and animals to people in the clinic. The company is systematically capturing complex, high-dimensional datasets, training specialized machine learning and AI models, and building foundation models that synthesize insights across diverse data layers. As it combines and coalesces these foundation models, spanning target discovery through clinical development, it is increasingly building a ‘world model’ that contains within the company a virtual representation of how biology and chemistry are working. The company's world model is enabling it to make many high-confidence predictions about the results of previously untried or untested questions.
The company's world model will attain a level of understanding of biology and chemistry of sufficient quality that its wet lab will move from data generation for model improvement as its primary use to ‘scaled validation of simulated solutions.’ In essence, the company's world model will become a ‘virtual cell’ where it can simulate an inexhaustible quantity of ‘experiments,’ identify those targets and chemistries that has the highest probability of success in modulating disease and achieving a desired (and automatically generated) Target Product Profile, and then its wet lab can validate those predictions at scale.
Building a Pipeline
Building on an OS platform after the business combination with Exscientia, Recursion’s pipeline encompasses 10 clinical and preclinical programs and over 10 advanced discovery programs across oncology, rare diseases, and other areas of high unmet need. This broad and rapidly evolving portfolio reflects the company’s commitment to advancing discovery and clinical development through unbiased, scaled scientific insights and AI-driven discovery. Programs in the company’s internal pipeline are built on unique biological and chemical insights surfaced through the Recursion OS where the etiology of the disease is well defined, but the subsequent impacts of the disease are generally obscure and/or the primary targets are typically considered undruggable and there is a high unmet medical need, no approved therapies, or significant limitations to existing treatments.
Advance Pipeline
The company is accelerating critical clinical milestones while delivering measurable progress against diseases with high unmet medical needs. At the same time, the company continues to validate various components of the Recursion OS, which has played a role in advancing every program in its portfolio, reinforcing its potential to accelerate drug discovery and development.
The company has already demonstrated promising safety and preliminary efficacy data for two of its programs. REC-994, a superoxide scavenger in development as a potential first-in-disease therapy for symptomatic CCM, was featured in a late-breaking oral presentation at the 2025 International Stroke Conference. Phase 2 data highlighted MRI-based lesion volume reduction and symptom stabilization trends. Next steps in this program will be informed by regulatory discussions and long-term extension data expected in 2025. REC-617, a potential best-in-class CDK7 inhibitor, has demonstrated early clinical activity in advanced solid tumors, including a durable partial response in metastatic ovarian cancer, and stable disease across patients with multiple tumor types. These findings support further clinical development as the company continues to explore its potential in combination regimens.
In parallel, Recursion has recently initiated three other clinical studies: DAHLIA (Phase 1/2, REC-1245 for solid tumors and lymphoma), TUPELO (Phase 1b/2, REC-4881 for FAP), and ALDER (Phase 2, REC-3964 for prevention of recurrent C. difficile infection).
Through its business combination with Exscientia, the company has doubled its partnership footprint with leading pharmaceutical companies, including Roche and Genentech, Sanofi, Bayer, and Merck KGaA (Darmstadt, Germany). By uniting its AI-driven platforms, vast proprietary data, and deep scientific expertise, the company continues to unlock powerful innovations and expand patient impact. Below are some of the latest developments illustrating this momentum:
Roche and Genentech
In December 2021, the company entered a multi-year, strategic collaboration with Roche and Genentech in key areas of neuroscience and an oncology indication. Through the partnership, the company is working with both Roche and Genentech's R&D units to leverage its Recursion OS and Maps of Biology, along with extensive single-cell perturbation screening data from Roche and Genentech, to rapidly identify novel biological relationships to initiate and advance therapeutic programs.
Gastrointestinal-Oncology Advancements: In partnership with Roche and Genentech, the company generated multiple whole-genome phenomaps with chemical perturbations across various disease-relevant cell types, enabling deeper insights into how different cellular contexts respond to gene knockouts and chemicals.
Neuro-specific CRISPR KO Phenomap: In partnership with Roche and Genentech, the company has developed the first whole-genome CRISPR knockout map in neural iPSC cells, providing valuable data to identify potential new targets in neuroscience, an area with limited new discoveries.
Sanofi
In January 2022, the company entered a strategic research collaboration with Sanofi to develop an AI-driven pipeline of precision-engineered, small molecule medicines. Through this collaboration, the company is using its end-to-end integrated platform to discover and advance up to 15 novel targets in the oncology and immunology therapeutic areas.
Bayer
In November 2023, the company announced an updated collaboration with its established partner, Bayer AG (Bayer), for a select set of precision oncology programs.
Merck KGaA (Darmstadt, Germany)
In September 2023, the company entered a collaboration with Merck KGaA, Darmstadt, Germany. This multi-year collaboration utilizes the company’s AI-driven precision drug design and discovery capabilities while leveraging Merck KGaA, Darmstadt, Germany’s disease expertise in oncology and immunology, clinical development capabilities, and global footprint.
Recursion is continuing to focus on leveraging the company’s discovery engine to identify first-in-class and best-in-class targets across oncology and immunology, driving innovation in these key therapeutic areas.
The Recursion OS provides an opportunity for mapping and navigating massive biological and chemical datasets that contain trillions of inferred relationships between disease-causative perturbations and potentially therapeutic compounds. The company uses standardized, automated workflows to identify programs and advance them through key stages of the drug discovery and development process which includes Patient Connectivity and Novelty (i.e., program initiation); Hit and Target Validation; Compound Optimization; Translation; IND-Enabling Studies; and Clinical Development.
The company has made progress in reshaping the traditional drug discovery funnel in the following ways:
Broaden the funnel of therapeutic starting points: The company's flexible and scalable mapping tools and infrastructure enable it to infer trillions of relationships between human cellular disease models and therapeutic candidates based on real empirical data from its own wet labs.
Identify failures earlier when they are relatively inexpensive: The company’s proprietary navigation tools enable it to explore the company’s massive biological, chemical, and patient-centric datasets to validate more and varied hypotheses rapidly. While this strategy results in an increase in early-stage attrition, the system is designed to rapidly prioritize programs with a higher likelihood of downstream success because they have been explored in the context of high-dimensional, systems-biology data.
Optimize molecular design and synthesis through Centaur Chemist: The company’s Centaur Chemist platform integrates AI-driven generative design with automated synthesis, enabling rapid iteration and optimization of new chemical entities. By leveraging predictive modeling for potency, selectivity, and ADMET properties, the company can efficiently generate high-quality, differentiated drug candidates while reducing synthesis timelines and experimental bottlenecks.
Accelerate delivery of high-potential drug candidates to the clinic: The Recursion OS contains chemistry tools that enable highly efficient exploration of chemical space, as well as translational tools that improve the robustness and utility of in vivo studies.
Enhance clinical development efficiency through ClinTech: The company is applying machine learning and AI to optimize clinical trial design, accelerate patient enrollment, and enhance evidence generation. By integrating scaled patient data with predictive analytics, it intends to improve patient stratification, match therapies with the right populations, and reduce trial failure rates—advancing high-potential medicines to patients faster and more efficiently.
Approach
At Recursion, the company is pioneering the integration of innovations across biology, chemistry, automation, data science and engineering to industrialize drug discovery in a full-stack solution across dozens of key workflows and processes critical in discovering and developing a drug. data generated from the company’s automated DMPK module and InVivomics platform enables it to predict ADMET properties and identify toxicity signals, respectively, significantly faster than traditional methods. With the business combination with Exscientia complete, the company can drive many of its programs from hit to development candidate using an automated internal chemical synthesis platform.
The company has used its approach to generate, aggregate, and integrate one of the largest proprietary biological, chemical, and patient-centric datasets in the world at approximately 65 petabytes at the end of 2024. This dataset includes proprietary phenomics, transcriptomics, predicted protein-ligand binding interactions, InVivomics, ADMET data, and more across many biological and chemical contexts, as well as preferred access to over 20 petabytes of multimodal oncology patient data from Tempus. Additionally, the company has built a proprietary suite of software applications within the Recursion OS which has identified over 7 trillion predicted biological and chemical relationships. With the company’s approach, it endeavors to turn drug discovery into a search problem where the company maps and navigates biology in an unbiased manner to discover new insights and translate them into potential new medicines at scale.
Value Drivers
While most small to medium-sized biopharma companies are focused on a narrow slice of biology or a single therapeutic area, the Recursion OS allows the company to discover and translate at scale across biology. However, the company is cognizant that building disease-area expertise, especially in clinical development, is essential.
A Platform to Industrialize Drug Discovery
The company has generated one of the largest relatable data sets in biopharma using its automated high throughput labs, which run over 2 million experiments per week. Its data includes cellular phenomics, captured using Brightfield microscopy, as well as chemical synthesis, transcriptomics, proteomics, ADMET, InVivomics, genomics, and patient data. In total, the company has approximately 65 petabytes of proprietary data, which it uses to train its algorithms and build its Maps of Biology.
In the company’s relentless drive to continue building the most advanced full-stack AI-enabled discovery and development platform, it has integrated Exscientia's Centaur Chemist platform for molecule design and automated synthesis capabilities with the Recursion OS, allowing the company to rapidly move from target discovery to in silico design to physical compound testing.
While the company works daily to continue solidifying its data moat through wet-lab experimentation and simulation, the company's partnerships with Helix and Tempus give it access to hundreds of thousands of patient insights – including whole exome and whole genome sequencing – across a wide range of chronic diseases and in oncology.
The company's unique platform approach has continued to evolve over time, and it continues to lead the industry in innovation and delivery of potential treatments through its pipeline and partnerships. When it first developed its phenomics-based biological map-making methods using HUVEC cells, it created over 100 billion cells per year for high throughput experiments. While others onboard technology the company pioneered over a decade ago, it has moved to live-cell brightfield imaging, and in partnership with Roche and Genentech, it built specific cell manufacturing technologies that derive neurons from hiPSCs at scale – ultimately producing over 1 trillion hiPSC-derived neuronal cells to build the world’s first whole-genome neuronal phenotype or ‘Neuromap’.
The company has launched a number of breakthroughs in foundation models – including powerful multimodal models like Phenom, MolPhenix and MolGPS. These models give Recursion deeper insights into underlying disease biology and how cells might respond to treatment with new drug candidates and provide the company with a distinct advantage when driving decisions about which therapeutic programs to pursue.
The Recursion OS
The Recursion OS is the integrated technical and scientific vertical platform that underpins drug discovery and development at Recursion, from program initiation through the company’s clinical trials. Collectively, the components of the Recursion OS can be joined together in a modular way to identify, validate, and advance a broad portfolio of novel therapeutic programs quickly, cost-effectively, and with minimal human intervention and bias.
To achieve this pipeline impact, the modules of the Recursion OS are connected by industrialized workflows that has been standardized, scaled, and automated. To drive greater efficiency, the company approaches the building of modules and workflows similar to modular programming, but for biology and chemistry, so that the same fundamental capabilities are transferable across drug discovery and development activities and reflected in a diverse portfolio for both the company’s internal pipeline and large pharma partnerships.
In 2024, the company:
Increased the sophistication of modules that improve earlier parts of the pipeline by integrating chemistry-centric models from Exscientia, including the company’s industrialized workflows for chemical optimization enabling both functional- and target-based discovery, biology- and chemistry-centric approaches, and first-in-class and best-in-class compound opportunities.
Integrated causal models and other analytics based on real patient data into both program initiation phases, ensuring patient connectivity and novelty, as well as clinical development activities, including patient stratification.
In 2024, the company demonstrated that by combining patient-level data with cellular-level data, it can extract genetic causal targets from small (24,000) patient data sets that had previously required patient data sets of over one million in some cases to overcome challenges with patient data quality. Similarly, it is exploring how protein-level data can add pathway interpretability and completeness to its cellular-level data.
Towards a Virtual Cell – How Recursion is combining data and compute across different scales
By closely integrating real world experimentation and AI in an iterative manner, and across multiple ‘levels’ of biology, one can create cycles of virtuous learning, where large fit-for-purpose wet-lab datasets support better in silico model generation and enable more focused future wet-lab experiments. Over time, this allows something powerful to emerge rather than a data-first approach underpinning World Model creation, the company’s drug discovery opportunities emerge from the World Model, and Real-World physical experimentation serves to validate the most promising insights. In essence, the company will have created a Virtual Cell which it can test in nearly unlimited ways, selecting the most promising outcomes for validation in a Real-World cellular system.
Spanning Multiple Layers of Biology
The company’s Real-World data layer and World model are built to use data across three scales: macro, meso and micro. The following section provides examples of these models based on each scale.
Macro: At the highest level, macroscale data informs on organism-level phenotypes and is typically deeply associative rather than causal – one can find associations between clinical outcomes and human observables, but the causal chain of how to go from variant to macro-scale phenotype is usually hidden. Different size scales and data generation formats tend to have differing levels of interpretability, data quality and noise, costs, and data completeness.
Meso: In the middle, mesoscale data is measurements on cellular biological systems, such as phenomics and transcriptomics. The company built its first in silico maps of biology and has historically executed its largest laboratory experiments.
Micro: At the smallest end, microscale data informs on molecular-level events like protein-small molecule binding and interactions and can enable insights at the level of target- and protein-interactions and properties. It is the realm of many of the company's physics- and chemistry-centric models, as well as its protein sciences and biochemical laboratory assays.
Macro Scale Data Layers
Macroscale data informs on tissue-, organism-, and population-scale biology, enabling the company to connect insights at the molecular (micro) and cellular (meso) levels to the behavior of drug candidates in patients, and to perform ‘reverse translation’ of insights from patient populations to direct the initiation of programs at the beginning of discovery. In 2024, Recursion built investments in macroscale biology in both model organisms for in vivo testing (InVivomics) and human populations, spanning cancer –omic data, population genetics data for non-oncology indications, and real-world clinical data.
InVivomics Data Layer
Recursion’s data layers combine to tell the story that the company’s therapeutics will safely provide benefit to a patient. In vivo experimentation is necessary to confidently translate the initial insights from high throughput experimentation in biology and chemistry to applications in the real world. The company’s InVivomics platform removes human toil and bias from animal data collection. Leveraging this platform maximizes data collection while minimizing human effort in key in vivo experimentation areas, in vivo pharmacology and toxicology.
In 2024, InVivomics produced important data that drove decisions across disease models in fibrosis, neuroscience, and oncology. The company integrated tolerability studies into its automated industrial workflows, streamlining the process from hit compound identification to animal model testing through a standardized set of experiments and decision criteria. Its in-house execution of a lung fibrosis model helped accelerate the delivery of a molecule progressing to clinical trials. The company also piloted studies in oncology and neuroscience. In neuroscience, it introduced new endpoint measurements like rotarod and CMAP.
In total, in 2024, the company ran 62 InVivomic-informed studies at its Milpitas, CA facility. Of those, 27 were mouse tolerability studies, delivering richer data to project teams as they design downstream in vivo pharmacology studies. Across its internal portfolio, 7 projects leveraged this technology to inform dose selection, as well as to evaluate impacts on specific tissues of interest. The company is also exploring the use of its digital system in rat toxicology studies, evaluating the advantages gained both with the richer constant-monitoring data, as well as better connection to its other data layers.
To extract maximum insights from this data, the company built a deep learning model called InVivoPrint V1 (IVP-1). IVP-1 allows it to detect organ toxicities linked to a compound or dose candidate as early as possible during in vivo tolerability studies – and to prioritize new drug candidates for the efficacy phase. The company's InVivomics dataset includes 1 million hours of video; 1 million hours of digital biomarkers, such as locomotion, body temperature, wheel speed, and cage humidity levels; 149,000 environment data points, including cage slottings, rack used, rack room, sex, and birth time, as well as a number of other categories.
Human Genetics Data Layer
At Recursion, the company has the capability to bridge its highly controllable, densely sampled perturbative map data (meso) together with observational patient data (macro) in a joint forward-reverse genetics approach. Using human genetics, it can connect the macroscale down to the mesoscale to inform phenotypic discovery and deliver stronger, more disease-relevant, and patient-connected insights. Conversely, by integrating scaled meso data, the company in turn increases the power and derives further value out of macro data above standard approaches.
In 2024, the company expanded its real-world macro data layer by partnering with various clinico-genomics companies and acquiring other sources of real-world evidence (RWE). In addition to retaining access to over 20PB of de-identified oncology patient data through its partnership with Tempus, it is partnering with Helix and has scaled access to hundreds of thousands of de-identified non-oncology patient records consisting of longitudinal clinical records paired with Helix’s Exome+ genomic data. The company is working with real-world data (RWD) providers and continues to augment the foundational macro layer with non-patient trial data, such as fit-for-purpose natural history, and both historical and Recursion trial data.
With the integration of these real-world macro and meso data, the company built critical components of the Recursion world model to increase the effective power of genetic association tests, inform on patient causality, and enable the precise selection of patient populations based on causal insights. In 2024, it demonstrated that it could extract genetic causal targets from small (24,000) patient data sets that had previously, depending on the target, required patient data sets of hundreds of thousands up to over one million (3-67x increase in effective power).
The company also developed a generalizable causal discovery workflow combining macro-meso data features and applied these models for target identification and program initiation purposes. This has led to over 60 genes identified through these causal models that are in testing on its validation platform. It has also started testing causal inference models for predicting responsive patient populations to aid in biomarker identification and design optimized patient selection strategies.
The company’s diversification and expansion of its access to large-scale real-world data, has strengthened the company’s foundation for building world models. This included the integration of electronic health records, claims data, non-patient clinical trial data, and historical trial data. Finally, the company also accelerated patient enrollment with data-driven site selection and automated site outreach.
Meso Scale Data Layers
Mesoscale data at Recursion informs the company about cellular biology and serves a unique role. Recursion has built and applied two high-throughput mesoscale assays and data layers, phenomics and transcriptomics.
Phenomics Data Layer
Phenomics measures the morphology of cultured cells grown in laboratory plates. Morphology is a holistic measure of cellular state that integrates changes from underlying layers of cell biology, including gene expression, protein production and modification, and cell signaling, into a single, powerful readout. Image-based -omics can be two to four orders of magnitude more data-dense per dollar than other -omics datasets that focus on these more proximal readouts, enabling the company to generate far more data per dollar spent to inform its drug discovery efforts. Phenomics data on genetic and small molecule perturbations forms the backbone of Recursion’s Maps of Biology.
The company’s real-world experimental phenomics data has historically been captured using multi-channel fluorescence microscopy; through 2024, it transitioned the platform to acquire live-cell brightfield images, an imaging modality bringing the capability to measure dynamic cellular state across time, rather than at a single timepoint as is typical for fluorescence-based phenomics or sequencing. In 2024, Recursion’s real-world phenomics experimental capabilities scaled to be able to generate up to 13.2 million cell paint images (110 terabytes) or up to 16.2 (135 terabytes) million multi-timepoint brightfield images across up to 2.2 million experiments per week.
The company’s machine learning work in phenomics contributes deeply to the Recursion world model. In 2024, Recursion demonstrated the power of scaling laws in machine learning with the training and deployment of Phenom-2, a larger version of the Phenom-1 phenomics model from 2023, making use of the increased computational power of BioHive-2 to improve the detection rate of expressed gene knockouts by 25.7%.
Transcriptomics and New –Omics Data Layers
Transcriptomics is a high-dimensional measure of cellular biology distinct from phenomics that assesses gene expression by measuring RNA levels in the cell. Transcriptomics augments the company’s mesoscale data acquisition in three keyways. First, it enables independent replication, at scale, of effects detected in phenomics to verify that they are not morphology-specific artifacts. Second, it offers a route to greater potential interpretability of high-dimensional biological effects by mapping perturbations onto identifiable genetic pathways. Finally, it potentially enables the acquisition of new kinds of biological information, including both effects specific to the transcriptome and new perturbations inaccessible on the company’s phenomics platform.
The company acquires transcriptomics data in the real world using both an internally developed high-density bulk arrayed transcriptomics platform, as well as a newly developed pooled single-cell transcriptomics capability. In 2024, the company has expanded its arrayed transcriptomics platform capability to enable the sequencing up to 62,000 wells per week and in 2024, generated just under 1 million individual transcriptomes of data. The company continues to explore investments in –omics technologies beyond transcriptomics, including but not limited to proteomics and metabolomics.
Transcriptomics represents the first extension beyond phenomics in the Recursion world model. In 2024, the company applied Recursion algorithms operating on transcriptomic experiments confirming phenomics to replace time-consuming, disease-specific validation assays with a portfolio-wide multimodal analysis.
Micro Scale Data Layers
At the smallest end, microscale data informs on the key chemical and biophysical measurements needed to succeed in drug discovery. This scale covers the molecular-level events, such as the binding events between compounds and their target proteins, as well as the chemical reactions involved in synthesizing and metabolizing these compounds. Three data layers encompass this micro scale. Protein Target, Chemical Data & Automated Synthesis, and ADMET, each encompassing scaled data generation and state-of-the-art AI models to accelerate the company’s design initiatives.
Protein Target Data Layer
The company's protein target data layer measures the protein-ligand binding interactions that drive drug discovery. Engaging protein targets with new compounds is a key driver in the development of effective medicines. This data layer encompasses the development of new target-centric functional assays, the automated platform conducting these real-world experiments, as well as its suite of advanced physics-based simulations that yield accurate synthetic data. These insights are captured by its state-of-the-art predictive chemistry models, using this data to guide automated design decisions.
In 2024, the company scaled and automated its experimental bioassay platform, which drives the testing phase of its precision Design-Make-Test-Analyze (DMTA) active learning loop. The platform's key features include assay type diversity, speed of execution, and close integration with software tools to enable autonomous operation. The platform supports over 250 diverse biochemical and functional assay types, allowing the company to drive diverse, high-quality target-enabled programs.
Recursion enhances its automated bioassay platform with absolute and relative binding free energy simulations (ABFE/RBFE) of protein-ligand interactions and protein folding predictions, each serving a different purpose toward enhancing molecule design. ABFE and RBFE are accurate molecular dynamics (MD) simulations of protein-ligand binding interactions, which evaluate new chemical designs on structurally enabled targets by computationally determining their affinities to the target. The company's RBFE calculations has demonstrated an average accuracy of 1.3 kCal/mol. These evaluations prioritize which designed compounds are made and tested.
From there, protein folding, and co-folding predictions are used to locate the ligand binding and mechanistic targets responsible for observed biological activities detected by its meso data layers (phenomics and transcriptomics). In 2024, the company connected 1.4 million known active ligands mapped to specific pockets across a synthetic data layer of 3D human protein structures. These relationships are used to identify tentative off-target interactions, binding sites (and their key active residues), and to initiate subsequent structure-based modeling, including ABFE and RBFE simulations. Notably, activity models are built with its MolGPS foundation model pretrained on thousands of chemical properties and biological activities.
Chemical Data Layer & Automated Synthesis
The company's chemical data layer integrates precision design, state-of-the-art molecular property prediction, and fully automated chemical synthesis, with the goal of designing and producing high-quality, differentiated medicines for patients. The precision design element transforms the drug discovery and development process. It replaces the conventional/conservative approach with an AI-first learning system that is well-suited to the complexities of drug discovery at each step of the process. The company's proprietary AI excels at generative molecular design, molecular property prediction, and multi-parameter optimization - powering its platform to multiplex design against addressing more complex, desired profiles than conventional approaches, with synthetic accessibility at its core.
The company's approach represents a substantial advancement in generative design and can be considered a next-generation solution. As the company designs molecules with AI-driven algorithms, its platform, informed by the company’s performant property prediction models, guides the design process toward compounds that are not only biologically and physiologically optimized, but also amenable to efficient synthesis on a unique, fully automated platform, suggesting the most cost- and time-effective way to make the molecule with sophisticated retrosynthesis that is vendor-logistics-aware.
The company captures reaction data alongside bioassay data and leverages active learning to ensure that its molecular property and synthesis prediction models continue to learn in step with the evolution of the company’s pipeline, continuously refining its ability to identify the most promising molecules and predict the feasibility and success of future synthetic routes. Recursion’s AI synthesis planning capability shows a 25% improved tractability assessment of AI-generated compounds over competitors and integrates with the Recursion OS. Incorporation of its platform into its discovery processes has resulted in a 35% improvement in design cycle productivity, enabling its design platform to support a broad pipeline.
ADMET Data Layer
A durable truth in drug discovery is the requirement that the company has confidence in its prediction of how its drugs will behave in patients. The company must enter clinical experimentation assured that it has a reasonable expectation that it will safely deliver benefits to patients. A key part of building that confidence is early testing of a candidate molecule’s pharmacokinetic (PK) properties, which informs the likelihood that the drug will stay in a patient’s body for the right amount of time to be effective. At Recursion, the company strives to generate critical decision-making data as early as possible.
In 2024, the company leveraged its high throughput ADME platform, RADME-01, to generate a bolus of data informing a compound’s likelihood to be viable. Its platform has been operational since late 2023 and can evaluate two 384-well plates in all available assays each week. In 2024, the company tested 12,209 novel compounds through this system, supporting both its internal pipeline and partnered projects. Drug discovery project teams can use this data to prioritize higher quality compounds for subsequent evaluation, and the company has also installed pre-set criteria for compound evaluation in its earlier (hit to lead) stage. In this semi-autonomous loop, data is generated, and compounds are nominated for in vivo PK testing without human effort or bias. The company is evaluating these criteria on a regular basis to ensure it is giving its projects the best chance at advancing high-quality projects and compounds.
Another primary use of data generated on the RADME-01 platform is to train predictive models capable of evaluating designs before synthesizing new molecules. In 2024, the company developed an automated machine learning framework that retrains and deploys new RADME-01 assay endpoint models weekly upon availability of new data, as well as several curated ADME property datasets. These models included a broad set of properties, such as intrinsic clearance, non-specific binding, solubility, efflux, drug-drug interactions, and several human PK parameters. Its teams used these models for both internal pipeline and partnership projects for prioritization of experimentation and prioritization of new molecule synthesis targets. Recently, automated models derived from the RADME model were combined with their counterparts in the Centaur Chemist platform, further enabling rapid design of compounds across both internal and partnership projects. The company’s combined datasets revealed very little direct overlap and has expanded the chemical space its models are trained on.
Scientific Agents and Industrialized Workflows
The early stages of the company’s drug discovery process, filling the T-shaped funnel, benefits from standardization and exploitation of the program-agnostic data universe that Recursion has generated this past decade. Industrializing later stages of drug discovery, where the focus is on molecular design, make and test in a program-specific assay cascade, requires context-dependent automation and exploitation of program-specific data. Agentic systems, with their adaptability and flexibility, provide Recursion with the opportunity to industrialize the drug discovery and development process in its entirety.
The industrialization of drug discovery and development at Recursion is implemented via a series of Industrialized Workflows, each exploiting the Recursion OS to serve both the mission of decoding biology to radically save lives and the pipeline. The first of these workflows, Initiation Workflow, offers a standardized approach to program initiation, the filling of the T-shaped funnel. Its role is to generate and assess disease-gene hypotheses. It succeeds by querying the patient data and maps of biology that reside in the data universe, and with help from a suite of Recursion OS models, hypothesizes which genes are associated with which diseases.
The company's precision design approach represents a constant interplay of automated data generation from experimentation and intelligent learning systems, embodying virtuous cycles of improvement in chemistry optimization. Compounds progress through synthesis and testing, generating valuable data that are automatically captured in its integrated platform, along with valuable annotations from its medicinal chemists, ready to inform and enhance its predictive modules. This closed-loop system helps translate design objectives into executable workflows, leveraging its 30+ scientific tech modules: from 2D and 3D synthesis-aware generative methods to property prediction models, reinforced with physics-based thinking, and active learning approaches for compound selection. As compounds are generated, synthesized, tested, and evaluated, the platform captures every decision point and experimental outcome, feeding this information back into its models to enhance future design choices. This recursive learning process ensures each iteration becomes more precise and informed than the last, driving the evolution of a more intelligent and efficient drug discovery engine that continuously learns and adapts.
Processing and Data Storage Infrastructure
The company’s modern drug discovery and development is a data and compute problem – the need to understand pathways, targets, compounds, and mechanisms of action requires obtaining, synthesizing, or predicting large volumes of data. To store this data in an efficient and low-risk way, Recursion makes use of a combination of cloud storage and on-premises storage. To process this data efficiently, the company brings it close to where the compute will run – either in its HPC datacenter (BioHive) or to its cloud (partnering with Google Cloud). To make this more seamless for its scientists, the company has invested in a hybrid storage and compute platform, which enables replication of data and locality of compute to allow it to use these resources as efficiently as possible.
This year, the company expanded its partnership with Google Cloud to explore generative AI capabilities, including Gemini models, supporting the Recursion OS, driving improved search and access with BigQuery, and helping scale compute resources.
The company has over tens of petabytes of unique data replicated across its sites for redundancy and resiliency. The company uses this data to train state-of-the-art (SOTA) foundation models of biology and chemistry and continues to push the limits of what is possible as it invests to scale up beyond Phenom-2 on the biology side and bring unique Quantum Mechanics (QM) and Molecular Dynamics (MD) data to bear in its chemistry models like MolGPS. The company largely trains these models using its own supercomputer, which consists of two generations of DGX SuperPod, with 504 H100s, and 320 A100s, and over 65 TB of VRAM.
Bringing it together – Combining data scales to drive value
The company's ability to generate and leverage real-world data at scale—across macro, meso, and micro levels—has already begun to reshape how it approaches drug discovery. By combining these layers through the Recursion OS, it is moving toward an industrialized, AI-driven system that not only accelerates therapeutic discovery.
The company's first demonstrations of this approach have successfully integrated macroscale patient data with mesoscale phenomics, allowing it to extract genetic causal targets from datasets previously considered too small for statistical power. This methodology enables a capital-efficient approach to rare variant discovery, increasing its ability to identify novel drug targets that are deeply connected to human disease, and it is just the beginning.
At the mesoscale, the company has advanced its phenomics and transcriptomics capabilities to provide high-throughput, high-dimensional insights into cellular biology. By connecting these layers with microscale molecular interactions, such as protein-ligand binding and ADMET properties, it enhances the interpretability and mechanistic understanding of its drug candidates.
One of the most transformative outcomes of the company's integrated approach will be the ability to construct a Virtual Cell—an AI-powered system that simulates biological responses at scale. Traditionally, drug discovery has been an experiment-driven process where models are built from data collected in the lab. At Recursion, it is reversing this paradigm: its World Model is driving the generation of new hypotheses, with real-world experimentation serving to validate the most promising insights. By iteratively refining these AI-driven predictions with physical experiments, the company is creating a feedback loop that accelerates learning and reduces reliance on trial-and-error experimentation.
In 2024, Recursion expanded its ability to industrialize drug discovery by enhancing the OS’s automation, scalability, and machine learning capabilities. Key milestones included:
The launch of BioHive-2, the most powerful supercomputer owned by any biopharma company, enabling the training of industry-leading foundation models like Phenom-2, MolPhenix, and MolGPS.
The integration of Exscientia’s automated chemistry platform, which has already generated over 500 custom molecules in under nine days per cycle.
The successful completion of the world’s first whole genome neuronal phenotype map (Neuromap) in partnership with Roche and Genentech, representing a significant leap forward in neuroscience drug discovery.
The augmentation of the company’s real-world data layer with hundreds of thousands of patient records through new partnerships with Helix and Tempus, dramatically improving its ability to connect patient-level insights with early-stage discovery.
The rapid expansion of the company’s transcriptomics capabilities, surpassing 1 million whole transcriptomes sequenced in a single year, reinforcing its ability to generate multimodal insights.
The development of InVivoPrint V1 (IVP-1), an advanced deep learning model that enhances the company’s ability to detect organ toxicities and prioritize drug candidates with greater precision.
The Road Ahead
Recursion is at the forefront of a new era in drug discovery, where data, AI, and automation converge to redefine the boundaries of what is possible. The continued evolution of the Recursion OS will focus on:
Further expansion of multimodal AI models that integrate patient-level insights with cellular and molecular data to refine drug target selection.
Greater automation in preclinical validation through advances in high-throughput biology and AI-driven chemistry.
Industrialized clinical development leveraging AI-powered trial design and patient selection to increase the probability of success.
Scaling the company’s Virtual Cell approach to predict and validate therapeutic interventions with unparalleled accuracy.
As it moves forward, the company remains committed to the mission that has guided Recursion from the beginning: to decode biology to radically improve lives. With its unique combination of scaled experimentation, AI-driven insights, and industry-leading automation, the company is not just advancing drug discovery—it is fundamentally redefining its future.
Pipeline
Programs in the company’s internal pipeline are built on unique biological and chemical insights surfaced through the Recursion OS where:
The etiology of the disease is well defined, but the subsequent impacts of the disease are generally obscure and/or the primary targets are typically considered undruggable.
There is a high unmet medical need, no approved therapies, or significant limitations to existing treatments.
Clinical Programs in Oncology
REC-617 – Advanced Solid Tumors
REC-617 is a potential best-in-class, potent and selective oral small molecule inhibitor of CDK7 with demonstrated activity in preclinical studies. CDK7 controls cell cycle progression and gene transcription, often overexpressed in advanced stage cancers reliant on transcriptional pathways. This program utilized the company’s generative AI and active learning platform to optimize molecule design, including non-covalent binding and ADME/PK for rapid absorption. This rapid design cycle enabled the company to synthesize 136 novel compounds and select REC-617 as its lead candidate in under 11 months.
A multicenter, open-label, Phase 1/2 (ELUCIDATE) monotherapy dose escalation (QD and BID) study is ongoing in advanced solid tumors. In December 2024, results from the initial 19 patients (18 response-evaluable at the time of cutoff) were presented at an AACR Special Conference in Cancer Research. REC-617 monotherapy demonstrated signs of preliminary efficacy. One heavily pre-treated ovarian cancer patient achieved a confirmed durable partial response (PR), which correlated with significant reductions in clinical tumor markers (CA125 and TK1). Four additional patients achieved durable stable disease (SD) as their best response. REC-617 was generally well-tolerated, with adverse events predominantly low grade, on-target, and reversible upon treatment cessation. The MTD was not reached and there were no treatment-related discontinuations.
Monotherapy dose escalation (QD and BID) remains ongoing, and the company expects to initiate combination studies in the first half of 2025. The company also expects to provide additional data updates from the Phase 1 in 2025.
REC-1245 – Biomarker-enriched Solid Tumors and Lymphoma
REC-1245 is a first-in-class, novel, potent, and selective molecular glue degrader of RBM39, a critical RNA-binding protein involved in alternative splicing and DNA damage repair (DDR) pathways. Leveraging the Recursion OS, the company discovered that genetic knockout of RBM39 can phenotypically mimic CDK12 loss – a validated DDR target – without impacting CDK13. To its knowledge, the company was the first to report this novel biological insight. Utilizing its phenomics-based platform for structure-activity relationship (SAR) studies, the company synthesized 204 candidates and advanced this program from target identification to IND-enabling studies in 18 months (versus the industry average of 42 months).
Preclinical data confirmed strong anti-tumor activity, including tumor regressions in a BRCA-proficient ovarian cancer model, minimal off-target effects, and no CDK12 kinase inhibition. With over 100,000 addressable patients in the U.S. and EU5 each year, REC-1245 has the potential to be a novel therapy in a biomarker-enriched advanced solid tumors and lymphoma patient population – either as a monotherapy or in combination regimens.
Following IND clearance in September 2024, the company initiated a Phase 1/2 (DAHLIA) study in December 2024 to evaluate the safety, tolerability, PK/PD, and preliminary efficacy of REC-1245 in unresectable, locally advanced, or metastatic cancers. It expects to share an update on the Phase 1 dose-escalation portion of the study in the first half of 2026.
REC-3565 – Relapsed / Refractory B-cell Malignancies
The company is advancing REC-3565, its reversible allosteric potential best-in-class MALT1 inhibitor, for the treatment of patients with relapsed or refractory B-cell malignancies. A variety of mutations seen in lymphomas induce constitutive MALT1 protease activation, leading to aberrant NF-kappaB signaling that drives survival and proliferation of B-cell tumors. Key preclinical data demonstrate sustained anti-tumor activity as a single agent or in combination with BTK inhibitors.
The company leveraged physics-based predictive modeling using its molecular dynamics toolkit and AI-powered hotspot analysis to deliver a candidate with lower predicted safety risk in the clinic. The company synthesized 344 novel compounds and advanced this program from hit identification to lead candidate in 15 months.
The molecule’s unique profile minimizes UGT1A1 inhibition risk, demonstrating superior target selectivity compared to oral competitors, both of which reported treatment-related hyperbilirubinemia in early Phase 1/2 studies. As a result, REC-3565’s enhanced selectivity supports the potential for a more favorable therapeutic index not only as a monotherapy, but also in combinations with BTK and BCL2 inhibitors. A multicenter, open-label, dose escalation Phase 1 study (EXCELERIZE) cleared a CTA by the MHRA in December 2024. The company expects to dose the first patient in the first half of 2025.
REC-4539 – Small Cell Lung Cancer
REC-4539 is reversible CNS penetrant, orally bioavailable, and potential best-in-class inhibitor of LSD1. LSD1 is an epigenetic enzyme that removes methyl groups from histones to control gene expression. SCLC is particularly dependent on LSD1 to maintain a neuroendocrine phenotype that drives tumor cell survival in this aggressive lung cancer subtype. Preclinical studies demonstrate that REC-4539 shows anti-tumor activity in SCLC human xenografts with limited impact on platelets.
The company’s program used multi-parameter optimization to design a unique candidate combining reversibility with CNS penetration. The company synthesized 414 novel candidates to arrive at its lead candidate in 22 months. Following IND clearance in January 2025, the company expects to initiate a multicenter, open-label Phase 1/2 trial (ENLYGHT) in the first half of 2025.
Clinical Programs in Rare Diseases
REC-994 – Cerebral Cavernous Malformation
The company is developing REC-994, an orally bioavailable small molecule superoxide scavenger, as a first-in-disease opportunity for symptomatic cerebral cavernous malformations (CCM). CCMs are rare vascular anomalies marked by abnormal capillary-venous structures, recurrent lesions, and stroke-like symptoms. REC-994 was discovered using the earliest version of Recursion’s comprehensive drug discovery platform. In an unbiased CCM2 loss of function phenotypic screen, REC-994 demonstrated concentration dependent rescue and was advanced into preclinical studies.
The company presented the Phase 2 study data as a late-breaking oral presentation at the International Stroke Conference, or ISC, annual meeting in February 2025. The company expects to share updates on next steps in 2025.
REC-4881 – Familial Adenomatous Polyposis
The company is developing REC-4881, a highly potent and selective, potential best-in-class MEK1/2 inhibitor, for familial adenomatous polyposis (FAP). FAP is a genetic condition characterized by the development of adenomas throughout the GI tract. The company is an orphan disease caused by inactivating mutations in APC, with most patients undergoing prophylactic colectomy due to nearly 100% likelihood of CRC by age 60.
During a collaboration with Takeda Pharmaceutical Company Limited (Takeda), the company leveraged machine vision and automated analysis to quantify hundreds of cellular parameters linked to APC siRNA knockdown. The company screened numerous compounds in this genetic background for 24 hours and identified REC-4881 as a potent molecule that rescued the phenotype in a concentration dependent manner. In preclinical studies, REC-4881 demonstrated over 1,000-fold selectivity in APC-mutant tumor cell lines and effectively inhibited spheroid growth and organization. The company expects to share safety and preliminary efficacy data in the first half of 2025.
REC-2282 – Neurofibromatosis Type 2
The company is developing REC-2282, a CNS penetrant, potential best-in-class pan-HDAC inhibitor, for neurofibromatosis type 2 (NF2). The company initiated the POPLAR study, an adaptive, randomized, multicenter Phase 2/3 trial in June 2022, with the first patient dosed in October 2022. In November 2024, the company announced that the trial was fully enrolled in the Phase 2 portion.
REC-3964 – Prevention of Recurrent C. difficile infection
The company is developing REC-3964, a non-microbial, orally bioavailable, potential first-in-class C. difficile (C. diff) toxin B selective inhibitor for the prevention of recurrent Clostridioides difficile infection (rCDI). C. diff toxin B disrupts the tight junctions in colonic cells and increases vascular permeability, leading to a leaky gut. REC-3964 is Recursion’s first new chemical entity to reach the clinic and binds and blocks the catalytic activity of the toxin's innate glucosyltransferase, while sparing the host. In a human disease relevant C. diff. hamster model, REC-3964 demonstrated a significant difference in the probability of survival versus bezlotoxumab alone.
The company’s program leveraged an ML-aided conditional phenotypic drug screen in human cells and identified novel mechanisms that mitigated the effect of C. diff. toxin B treatment. In June 2024, the company presented Phase 1 data in healthy volunteers at the 6th Edition of World Congress on Infectious Diseases in Paris. In October 2024, the company initiated a Phase 2 open-label, randomized, 3-arm study (ALDER) to evaluate the rate of recurrence in patients with a high-risk of CDI, who has achieved symptom resolution following treatment with oral vancomycin for 14 days. The company expects to share initial results from the Phase 2 study in the first quarter of 2026.
Deep Dive into Clinical and Select Preclinical Programs
REC-617 for Advanced Solid Tumors – Phase 1/2
REC-617 is an orally bioavailable, cyclin-dependent kinase 7 (CDK7) inhibitor under development for the treatment of advanced solid tumors. Inhibiting CDK7 targets both cell cycle dysregulation and transcriptional ‘addiction’, which are hallmarks of multiple aggressive cancers, including but not limited to, CDK4/6 resistant breast cancer, ovarian cancer, and other solid tumors. There are no CDK7 inhibitors approved by the FDA. ELUCIDATE, a Phase 1/2 open-label, multicenter, safety, PK, PD and preliminary efficacy study is underway. Interim Phase 1 safety, PK, PD, and efficacy data were shared in the fourth quarter of 2024. The company expects to initiate combination studies in the first half of 2025.
Insight from Recursion OS
Leveraging the company’s AI-driven multi-parameter optimization approach, it identified critical design limitations in existing CDK7 inhibitors. This insight led to an improved target product profile and a novel molecule design. REC-617 is an orally bioavailable, potent and selective CDK7 inhibitor with enhanced oral bioavailability. It has a non-covalent, reversible mechanism of action, and a predicted shorter human half-life compared to other drugs in development. These characteristics potentially offer an improved therapeutic index, less off-target effects, and more consistent absorption.
Preclinical
REC-617 has demonstrated strong anti-tumor activities in preclinical studies and in vivo experiments showed potent tumor regression across multiple solid tumor types. Notably, in the OVCAR3 ovarian cancer xenograft model as shown below, complete tumor regression was observed in all 8 mice treated with 10 mg/kg by Day 27. Importantly, no significant body weight loss was observed across treatment arms. Mouse PK studies revealed that maintaining 8-10 hours of CDK7 IC80 coverage resulted in potent tumor regression with minimal side effects, while coverage beyond 10 hours led to significant body weight loss. This defined an optimal therapeutic window that guided target efficacious exposures in the clinic.
Clinical
In the third quarter of 2023, the company initiated a Phase 1/2 open-label, multicenter study (ELUCIDATE) in patients with advanced solid tumors. monotherapy dose escalation (QD and BID) is ongoing, with combination study initiation expected in the first half of 2025. monotherapy dose escalation (QD and BID) is ongoing, with combination study initiation expected in the first half of 2025.
In December 2024, the company presented results from the initial 18 response evaluable patients at an AACR Special Conference in Cancer Research. REC-617 was well-tolerated with predominantly Grade 1-2 adverse events, no treatment-related discontinuations, and fewer GI side-effects than reported for other CDK7 inhibitors. Dose escalation (QD and BID) is ongoing, and the maximum tolerated dose (MTD) has not been reached. PK was dose linear and exceeded the CDK7 IC80 with rapid absorption (Tmax 0.5–2h) and short t½ (5–6h). Robust target engagement was also observed with rapid increases in POLR2A (3-4x), which normalized within 24 hours.
REC-1245 for Solid Tumors and Lymphoma – Phase 1/2
Following IND clearance in September 2024, the company initiated a Phase 1/2 open-label, multicenter study (DAHLIA) to evaluate the safety, tolerability, PK, PD, RP2D, and preliminary efficacy of REC-1245. With the first patient dosed in December 2024, the company expects to share an update on the program in the first half of 2026.
Insight from Recursion OS
The company subsequently discovered REC-1245 as an RBM39 molecular glue degrader that closely mimics the phenotypic loss of CDK12 and RBM39, but not CDK13.
Preclinical
REC-1245 is a potent, potential first-in-class RBM39 molecular glue degrader with compelling preclinical activity. It showed no significant in vitro safety concerns (CEREP, hERG), no CDK12 kinase activity, and minimal ITGA2 liability – an off-target effect seen with prior RBM39 degraders. As shown in the figures below, REC-1245 demonstrated strong antitumor activities as a single-agent, including tumor regression in an ovarian cancer BRCA-proficient, p53 mutant, OVK18 in vivo cell line derived xenograft (CDX) model. In addition, dose-dependent anti-tumor activity correlated with increases in RBM39 degradation confirming target engagement and an exposure-response-efficacy relationship.
Clinical
In December 2024, the company initiated a Phase 1/2 open-label, multicenter study to characterize the safety, tolerability, PK, PD, and preliminary anti-tumor activity of REC-1245 in participants with unresectable locally advanced or metastatic cancer. As of December 31, 2024, the trial was active and enrolling at 5 U.S. sites. The company expects to share an update on the Phase 1 dose escalation portion in the first half of 2026.
REC-3565 for B-Cell Malignancies – Phase 1
Following clearance of a CTA by the MHRA in December 2024, the company plans to initiate EXCELERIZE, a Phase 1 open-label, multicenter, dose escalation study to evaluate the safety, tolerability, PK, PD, and preliminary anti-tumor activity of REC-3565. The company expects the first patient to be dosed in the first half of 2025.
Insight from Recursion OS
Leveraging its AI-driven, multi-parameter optimization approach, the company focused on an allosteric mechanism to enhance potency, selectivity, and safety for REC-3565. Hotspot analyses and physics-based molecular dynamics guided its design strategy, helping it address the hydrophobic and highly mobile nature of the allosteric binding site.
Preclinical
REC-3565 demonstrated significant antitumor activity across multiple B-cell lymphoma models. As a monotherapy, it drove tumor regressions in ABC-DLBCL xenografts, and in combination with zanubrutinib – a next-generation BTK inhibitor – it produced durable responses, with 70% of mice displaying no palpable tumors 10 days after the last dose. Additional in vitro analyses revealed minimal UGT1A1 inhibitory effects relative to other MALT1 inhibitor scaffolds in clinical development, suggesting an improved safety and combination therapy profile.
Clinical
EXCELERIZE is a Phase 1 open-label, multicenter, dose escalation study designed to evaluate the safety, tolerability, PK, PD and preliminary anti-tumor activity of REC-3565 in patients with R/R B-cell malignancies. Part A will assess monotherapy dosing to identify a recommended dose for combination in Part B, which will evaluate combination regimens to inform future studies in B-cell cancers. Following CTA clearance by the MHRA in December 2024, the company anticipates dosing the first patient in the first quarter of 2025.
REC-4539 for Small-Cell Lung Cancer – Phase 1/2
In January 2025, the FDA cleared an IND application for ENLYGHT, a Phase 1/2 open-label, multicenter study evaluating REC-4539 patients with advanced SCLC. The company expects the first patient to be dosed in the first half of 2025.
Insight from Recursion OS
Developing a selective LSD1 inhibitor for SCLC requires a reversible mechanism, a short half-life to minimize on-target toxicity (e.g., thrombocytopenia), and the ability to penetrate the blood-brain barrier to address frequent metastases. Many existing LSD1 agents fail to meet these criteria, resulting in dose-limiting toxicity and poor CNS exposure. Using the company’s AI-driven, multi-parameter optimization approach, it generated and screened diverse chemical scaffolds for potency, selectivity, ADME properties, and CNS penetration. Active learning identified counterintuitive yet informative compounds, enabling a rapid design breakthrough. As a result, the company created REC-4539 – a potent, selective, reversible, brain-penetrant, and potential best-in-class LSD1 inhibitor with a short, predicted half-life.
Preclinical
REC-4539 demonstrated potent anti-tumor activity across multiple preclinical models, including the NCI-H1417 human SCLC xenograft. In this model, dose-dependent tumor regression correlated with a corresponding decrease in the neuroendocrine tumor biomarker progastrin-releasing peptide (proGRP). Additionally, REC-4539 treatment was well-tolerated, with minimal impact on platelet counts.
Clinical
ENLYGHT is a Phase 1/2, open-label, multicenter study designed to evaluate the safety, tolerability, and preliminary efficacy of REC-4539 in patients with SCLC. The FDA cleared an IND application in January 2025, and the company expects the first patient to be dosed in the first half of 2025. Phase 1 will include both monotherapy dose escalation and REC-4539 combination with durvalumab, determining safety, tolerability, and a recommended dose. Phase 2 will focus on dose optimization for both monotherapy and combination arms, followed by expansion to further assess efficacy.
REC-994 for Cerebral Cavernous Malformation – Phase 2
Insight from Recursion OS
Using a CCM2 loss-of-function screen in human endothelial cells, the company’s early phenotypic platform rapidly identified drug candidates capable of reversing disease-relevant phenotypes. REC-994 emerged from this unbiased approach as a potent molecule that modulated CCM pathology in vitro. These discoveries laid the groundwork for preclinical validation and subsequent clinical development, exemplifying how the company’s platform can accelerate therapeutic innovation.
REC-994 is a therapeutic designed to alleviate neurological symptoms associated with CCM and potentially reduce the accumulation of new lesions with pharmacokinetics supporting once-daily dosing in humans. The putative mechanism of action of REC-994 is through reduction of reactive oxygen species and decreased oxidative stress that leads to stabilization of endothelial barrier function. In addition, REC-994 exhibits anti-inflammatory properties which could be beneficial in reducing disease-associated pathology.
Preclinical
In CCM mouse models (including Ccm1- and Ccm2-deficient strains), chronic REC-994 administration significantly reduced lesion number and size while improving vascular permeability parameters. These data supported further clinical evaluation of REC-994 investigation.
Clinical
Phase 1
Single- and multiple-ascending dose (SAD/MAD) studies in healthy volunteers established the safety, tolerability, and pharmacokinetics of REC-994. The compound was well tolerated with no treatment-related discontinuations or serious adverse events, supporting once-daily dosing for chronic use.
Phase 2 (SYCAMORE)
Initiated in March 2022, the SYCAMORE study is a two-part Phase 2 trial in patients with symptomatic CCM. Part 1 was a 12-month, randomized, double-blind, placebo-controlled comparison of 200 mg or 400 mg REC-994 vs. placebo daily and as of December 31, 2024, was completed. Part 2 is an optional long-term extension (LTE) for eligible participants and is ongoing. Approximately 80% of participants who completed 12 months of treatment opted to continue into the long-term extension portion of the study.
REC-2282 for Neurofibromatosis Type 2 - Phase 2/3
Insight from Recursion OS
The company’s selected REC-2282 as a candidate for its NF2 program using the company’s brute-force phenotypic screening approach in NF2-deficent HUVEC cells. REC-2282 was uniquely identified as reversing the cellular and structural defects back to a wildtype like morphological state. The compound demonstrated concentration dependent rescue, showing no significant activity on other tumor suppressors or oncogene knockdown models. These data validated REC-2282’s selective activity, supporting advancement into preclinical studies for NF2 mutant tumors.
Preclinical
REC-2282 demonstrated potent anti-tumor activity in NF2-relevant models, inhibiting proliferation of vestibular schwannoma (VS) and meningioma cells via AKT inactivation (cell cycle arrest/apoptosis). It suppressed tumor growth in NF2-deficient mouse VS allografts, human VS xenografts (25 mg/kg/day for 45 days), and orthotopic NF2-deficient meningioma models (Ben-Men-1 cells).
Clinical
Four investigator-sponsored trials (ISTs) of REC-2282 established a 60 mg TIW MTD for solid tumors with manageable cytopenia. As of December 31, 2024, the Phase 2 portion is fully accrued with 25 adult participants enrolled. Once all 25 subjects complete six months of treatment, a futility analysis will be conducted to determine a go/no-go for the Phase 3 portion of the study. The company expects to share this data in the first half of 2025.
REC-4881 for Familial Adenomatous Polyposis (FAP) - Phase 1b/2
The company is enrolling patients in TUPELO, a Phase 1b/2, open-label, multicenter study to evaluate the effect of REC-4881 on polyp burden reduction. Orphan Drug Designation in the U.S. and EU, as well as Fast Track Designation in the U.S. were granted to REC-4881 for FAP. The company expects to share Phase 2 safety and preliminary efficacy data in the first half of 2025.
Insights from Recursion OS
REC-4881 was identified as a potential first-in-disease therapy for FAP using a high-content phenotypic screening approach targeting APC-deficient human cells. In this screen, REC-4881 emerged as a potent allosteric MEK1/2 inhibitor that rescued an APC siRNA genetic knockdown-associated morphological phenotype. Compared to other MEK inhibitors, REC-4881 demonstrated a highly selective and concentration-dependent response, suggesting best-in-class potential. As a result, REC-4881 was in-licensed from Takeda and subsequently advanced into preclinical studies.
Preclinical
REC-4881’s activity was validated in tumor cell lines and spheroid models derived from APC-mutant human epithelial tumor cells. In these systems, REC-4881 inhibited spheroid growth and disrupted cellular organization, demonstrating over 1,000-fold selectivity in APC-mutant cells. In a disease-relevant FAP model, ApcMin/+ mice were treated with multiple oral doses of REC-4881 or celecoxib over eight weeks. While celecoxib reduced polyp formation by approximately 30% compared to vehicle, REC-4881 treatment led to a reduction of 50% (1-3 mg/kg), and 70% (10 mg/kg). Mice that were treated with 10 mg/kg REC-4881, the highest dose tested, exhibited an approximately 70% reduction in total polyps. Histological analysis of gastrointestinal tissues further revealed that, unlike celecoxib, which primarily affected benign polyps, REC-4881 significantly reduced both benign polyps and high-grade adenomas.
Clinical
REC-4881 has been evaluated in multiple clinical studies, demonstrating a well-tolerated safety profile and pharmacological activity.
Phase 1 Oncology Studies
In a prior dose-escalation study (C20001) conducted by Millennium Pharmaceuticals in 51 participants with non-hematologic malignancies, REC-4881 (formerly TAK-733) was administered at doses ranging from 0.2 mg to 22 mg once daily. The maximum tolerated dose (MTD) was determined to be 16 mg. The most common adverse events (AEs) were rash (67%), and treatment-related serious adverse events (SAEs) were infrequent. No unexpected safety concerns emerged, and pharmacokinetic analyses showed a less-than-dose proportional increase in exposure.
REC-4881-101 (Healthy Volunteers)
The company conducted a Phase 1 study to evaluate the safety and pharmacokinetics of REC-4881 in 25 healthy participants receiving single doses of 4 mg, 8 mg, and 12 mg. REC-4881 was well tolerated, with no SAEs or dose-related safety concerns. The most common treatment-emergent adverse events (TEAEs) were mild and self-limiting, including transient blurred vision and vitreous floaters. No QTcF abnormalities were observed.
TUPELO (Phase 1b/2 in FAP)
The company is enrolling patients in TUPELO, a Phase 1b/2 open-label, multicenter study evaluating the efficacy, safety, pharmacokinetics, and pharmacodynamics of REC-4881 in FAP. Part 1 assessed safety, tolerability, and pharmacokinetics in FAP patients receiving 4 mg once daily for 14 days. REC-4881 was generally well-tolerated, with a safety profile consistent with other MEK inhibitors. Preliminary pharmacodynamic data suggests the 4 mg dose is pharmacologically active in FAP. Part 2 will evaluate efficacy, safety, and pharmacokinetics in post-colectomy FAP patients with confirmed germline APC mutations. Participants will receive once-daily REC-4881 for three months. Safety and preliminary efficacy data from Part 2 are expected in the first half of 2025.
REC-3964 for Prevention of Recurrent Clostridioides Difficile Infection - Phase 2
A Phase 1 study established its safety, tolerability, and pharmacokinetics, supporting the initiation of the ALDER Phase 2 trial in Q3 2024. This trial is evaluating REC-3964’s ability to reduce recurrence rates in patients recovering from a recent Clostridioides difficile (C.diff) infection. The company expects to share preliminary data in the first quarter of 2026.
Insight Recursion OS
Leveraging the Recursion OS, the company identified REC-3964 as a new chemical entity that selectively inhibits the glucosyltransferase activity of C. difficile toxin B. This non-antibiotic approach was discovered through a high-content phenotypic screen, where REC-3964 demonstrated potent reversal of toxin-induced cellular damage in HUVEC. The company droves SAR and optimization of REC-3964 directly on the platform and subsequently advanced the molecule into preclinical studies.
Preclinical
REC-3964 was validated in orthogonal functional assays, including the electrical cell-substrate impedance sensing (ECIS) assay where it demonstrated concentration-dependent activity in blocking toxin-mediated barrier disruption. In a hamster model of C. diff, REC-3964 treatment significantly prolonged survival compared to bezlotoxumab and control groups, indicating its potential to reduce both initial infection severity and recurrence rates.
Clinical
REC-3964 has been evaluated in a Phase 1 study in healthy volunteers and is being investigated in the ALDER Phase 2 trial for rCDI.
Phase 1 (Healthy Volunteers)
A Phase 1 study assessed the safety, tolerability, and pharmacokinetics of REC-3964 in 90 healthy participants, including a cohort of elderly subjects (>65 years). REC-3964 was well tolerated at single doses up to 1,200 mg and multiple doses up to 900 mg, with no serious adverse events (SAEs), discontinuations, or deaths. The most common treatment-emergent adverse events (TEAEs) were mild and included fatigue, headache, and abdominal distension, with similar rates between REC-3964 and placebo groups. Pharmacokinetics demonstrated dose-proportional exposure with a 7 to10 hour half-life, supporting twice-daily (BID) dosing. No clinically significant effects on ECG parameters, vital signs, or laboratory markers were observed. Results were presented at the 6th Edition of the World Congress on Infectious Diseases in June 2024.
Phase 2 (ALDER – Ongoing, Initiated Q3 2024)
The ALDER study is a Phase 2 open-label, multicenter trial evaluating REC-3964 as secondary prophylaxis therapy in patients recovering from an initial C. diff infection. Participants will be randomized 2:1:1 to receive 500 mg or 250 mg BID for 28 days, compared to an observational cohort. The primary endpoints are safety, tolerability, and recurrence rates of rCDI. A Phase 2 data update is expected in the first quarter of 2026. To the company’s knowledge, REC-3964 is the first orally bioavailable, non-antibiotic, C. diff toxin inhibitor that selectively targets bacterial toxin, while sparing the host.
REV102 for Hypophosphatasia – IND Enabling
In 2019, Recursion and Rallybio established a co-development and co-ownership joint venture to apply AI-driven drug discovery to rare diseases. Using Recursion’s generative AI platform, Gambit, the company identified ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) as a target for the treatment of Hypophosphatasia (HPP). ENPP1 catalyzes the production of inorganic pyrophosphate (PPi), exacerbating the mineralization imbalance in HPP patients.
Insight from Recursion OS
Using the company’s GenAI platform, it designed REV102, a potential first-in-class and best-in-class orally bioavailable and highly selective ENPP1 inhibitor for HPP. The company’s proprietary generative AU design algorithm, Gambit, guided precision optimization, incorporating rigorous 3D and 2D constraints to ensure high potency and suitability for lifelong chronic dosing. This AI-driven approach allowed the discovery of a structurally distinct compound with strong target engagement, designed to restore PPi homeostasis and improve bone mineralization in juvenile-onset and adult HPP patients.
Preclinical
In preclinical studies, the company’s first-generation tool compound, REV101, demonstrated improved bone mineralization in HPP mouse models. Bone morphometry analysis showed that L3 vertebrae in treated HPP mice reached mineralization levels comparable to wildtype mice, while trabecular regions of the distal femur exhibited slight improvement. Notably, REV101 significantly reduced plasma PPi levels by approximately 30%, restoring them to wildtype levels after 100 days of dosing. These findings validate ENPP1 inhibition as a viable therapeutic approach for HPP and informed the design and optimization of REV102 for clinical development.
REC-4209 for Idiopathic Pulmonary Fibrosis (IPF) – IND Enabling
Recursion identified REC-4209, a potential first-in-class, orally bioavailable immuno-mesenchymal modulator for idiopathic pulmonary fibrosis (IPF) using phenotypic screening of human PBMC-derived fibrocytes. This approach uncovered Target Epsilon, a novel regulator of fibrotic diseases.
Insight from Recursion OS
The company developed a PBMC-derived fibrocyte phenotypic screen to model fibrotic disease and identify novel therapeutic targets in an unbiased manner. This approach identified multiple small molecules capable of mimicking the effects of pentraxin-2 (PTX-2), an endogenous anti-fibrotic protein involved in monocyte differentiation and macrophage polarization. Combining the company’s inferential search capabilities within the Recursion OS, it uncovered Target Epsilon, a novel regulator of immuno-mesenchymal cell function. Biochemical validation confirmed small molecule binding to Target Epsilon, leading to the identification and optimization of REC-4209, a potent and selective compound designed to reverse fibrosis by restoring immune-mesenchymal homeostasis.
Preclinical
REC-4209 demonstrated potent activity in phenotypic reversal assays, with an EC50 of 0.40 µM in fibrocyte rescue and an IC50 of 12 nM to Target Epsilon. In digital tolerability studies, REC-4209 was well tolerated in C57BL/6 mice at doses up to 300 mg/kg/day (PO, 6 days), with no significant effects on body weight, breathing rate, motion, or body temperature. In a rodent fibrosis model, REC-4209 significantly reduced collagen deposition, a key histological marker of fibrosis. These findings support REC-4209’s potential to halt fibrotic progression, positioning it as a novel disease-modifying therapy for IPF.
Technology Partnerships
As Recursion continues to generate and leverage highly relatable and reliable datasets to support its internal pipeline and therapeutic partnerships, the company continues to invest in advanced compute capabilities and data-centric solutions to strengthen its drug discovery and development efforts. Expanding on its previous release of select datasets and models, the company is exploring additional opportunities to make more datasets and foundational models available to the broader scientific community. Its collaborations with NVIDIA, Google Cloud, Helix, and Faro Health underline its commitment to implementing AI and technology-enabled solutions to support its efforts to bring better medicines to patients faster.
NVIDIA Corporation (NVIDIA)
In July 2023, the company entered a strategic collaboration with NVIDIA to accelerate the development of its groundbreaking AI foundation models for biology and chemistry using its supercomputer, BioHive-1, and priority access on NVIDIA DGX Cloud. In May 2024, it completed BioHive-2, Recursion’s new NVIDIA DGX SuperPOD AI supercomputer, powered by 63 DGX H100 systems with a total of 504 NVIDIA H100 Tensor Core GPUs, increasing the computational capacity by over 4X.
Helix
In May 2024, the company entered into a multi-year agreement with Helix to access hundreds of thousands of de-identified clinic-genomic records consisting of longitudinal clinical records paired with Helix’s Exome+ genomic data.
Google Cloud
In October 2024, the company announced an expanded collaboration with Google Cloud, leveraging their technologies to accelerate drug discovery research and further enhance its ability to bring new medicines to patients faster. Through this collaboration, the company will explore generative AI capabilities, including Gemini models, to support the Recursion OS. It will improve data search and access from its proprietary dataset with BigQuery and facilitate the scaling of compute resources to run large inference workflows effectively. Additionally, in November 2024, the company announced the release of OpenPhenom-S/16 in Google Cloud’s Vertex AI Model Garden. OpenPhenom, a non-commercial, publicly available foundation model built on microscopy data, sets a new ‘gold standard’ for the industry, outperforming CellProfiler. This model offers the potential for researchers to replace their existing workflows with an off-the-shelf model that outperforms traditional microscopy analysis pipelines without requiring any additional tuning or training.
Faro Health
In December 2024, the company entered into an agreement with Faro Health to leverage their AI-powered platform for clinical protocol design to reduce clinical trial costs and complexity while minimizing burden to trial participants and sites. The company also anticipates utilizing the structured study definitions created through Faro’s software to automate traditionally labor-intensive and time-consuming historically downstream tasks, such as building the Electronic Data Capture system for each study.
Roche & Genentech Collaboration and License Agreement
On December 5, 2021, the company entered into a Collaboration and License Agreement with Genentech, Inc. and F. Hoffmann-La Roche Ltd, pursuant to which it will construct, using its imaging technology and proprietary machine learning algorithms, unique maps of the inferred relationships among perturbation phenotypes in each cellular context (each a ‘Phenomap’). Together with Roche and Genentech, the company will create multimodal models and maps to further expand and refine such inferred relationships.
Sanofi License Collaboration and License Agreement
In January 2022, the company entered into a Collaboration and License Agreement with Sanofi S.A. (Sanofi), referred to as the CLA. In July 2023 and December 2023, it amended the Collaboration and License Agreement, with such amended CLA referred to as the Amended CLA. Pursuant to the Amended CLA, the company will use its artificial intelligence-driven, end-to-end integrated platform to discover and validate novel targets in the oncology and immunology therapeutic areas. It will collaborate with Sanofi to advance certain of these targets into small molecule inhibitor drug research projects and accelerate the identification of certain small molecule development candidates.
Bayer AG Amended and Restated Research Collaboration and Option Agreement
On August 28, 2020, Recursion and Bayer entered into a Research Collaboration and Option Agreement, which was subsequently expanded on December 1, 2021, for research and collaboration on a certain number of projects related to fibrosis.
Merck KGaA, Darmstadt, Germany Research Collaboration Agreement
In September 2023, the company entered into a Research Collaboration Agreement, or the RCA, with the Healthcare Business of Merck KGaA, Darmstadt, Germany, referred to as Merck KGaA, Darmstadt, Germany, pursuant to which it will be responsible for the design process, as well as translational and early non-clinical studies to discover development candidates based on the initial agreed targets.
REC-994: University of Utah Research Foundation Agreements
In February 2016, the company entered into an Amended and Restated License Agreement with the University of Utah Research Foundation, or UURF, pursuant to which it obtained an exclusive license under certain patents and a non-exclusive license under certain know-how, in each case controlled by UURF and related to the drug tempol, or REC-994, to make, has made, use, offer to sell, sell, import and distribute products incorporating REC-994 worldwide for the treatment of cerebral cavernous malformation, or CCM.
REC-2282: Ohio State Innovation Foundation In-License
In December 2018, the company entered into an Exclusive License Agreement with the Ohio State Innovation Foundation, or OSIF, pursuant to which it obtained an exclusive, sublicensable, non-transferable, royalty-bearing license under certain patents and fully-paid up, royalty-free, nonexclusive license under certain know-how, in each case controlled by OSIF and related to the pan-histone deacetylase inhibitor, OSU-HDAC42, or REC-2282, to develop, make, has made, use, sell, offer for sale and import products incorporating OSU-HDAC42 worldwide.
REC-4881: Takeda License Agreement
In May 2020, the company entered into a License Agreement, or the Takeda In-License, with Takeda Pharmaceutical Company Limited, or Takeda, pursuant to which it obtained an exclusive (even as to Takeda and its affiliates), worldwide, sublicensable under certain conditions, transferable, royalty-bearing license to certain Takeda patents, know-how and materials related to develop, manufacture and commercialize Takeda’s clinical-stage compound known as TAK-733, a non-ATP-competitive allosteric inhibitor of MEK1 and MEK2, subject to a non-exclusive, royalty-free, irrevocable, fully paid up, license back to Takeda to use the licensed compounds for non-clinical research purposes.
Bayer License Agreement
In December 2023, the company entered into a License Agreement with Bayer, the Bayer License Agreement.
Intellectual Property
As of February 2025, the Recursion patent portfolio is balanced between Platform IP and Program IP.
Platform IP: Approximately one-half of the patents and patent applications that the company owns, or licenses worldwide relate to the Recursion platform, including patents and applications related to the Recursion OS IP, as well as many other inventions related to Recursion’s machine learning and artificial intelligence capabilities, cell perturbations, gene editing, drug discovery, drug development and hardware solutions.
Recursion Program IP:
REC-2282: The company exclusively licenses OSIF’s interest in patents and patent applications related to REC-2282 from OSIF; these patents and patent applications relate to composition of matter and methods of use for treating cancer cachexia with REC-2282. The company expects its licensed issued patents related to REC-2282 to generally expire between 2030 and 2035, excluding any patent term extension or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees. With respect to NF-2, orphan drug exclusivity in the U.S. would run seven years from marketing authorization.
REC-994: The company exclusively licenses UURF’s interest in patents and patent applications related to the use of REC-994 for the treatment or prevention of CCM from UURF. The company expects its licensed issued patents related to REC-994 to generally expire in 2035, excluding any patent term extension or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees. With respect to CCM, orphan drug exclusivity in the U.S. would run seven years from marketing authorization.
REC-4881: The company owns patent applications or exclusively licenses Takeda’s interest in patents and patent applications from Takeda, related to composition of matter and methods of reducing polyp burden in people living with FAP using REC-4881. The company expects its licensed issued patents related to REC-4881 to generally expire in 2029, excluding any patent term extension or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees. With respect to FAP, orphan drug exclusivity in the U.S. would run seven years from marketing authorization.
REC-3964: The company owns a patent and patent applications related to the composition of matter and methods of inhibiting the toxin produced by Clostridioides difficile in the gastrointestinal tract using REC-3964. The company expects its issued patent related to REC-3964 to expire no earlier than 2042, excluding any patent term adjustment or patent term extension, or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees.
REC-617: The company owns patent applications related to REC-617; these patent applications relate to composition of matter and methods of treatment for multiple advanced solid tumor indications for REC-617. Upon issuance, the company expects its patents resulting from these patent applications to expire no earlier than 2041, excluding any patent term extension or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees.
REC-1245: The company owns patent applications related to the composition of matter and methods of treating biomarker-enriched solid tumors and lymphoma using REC-1245. Upon issuance, the company expects its patents resulting from these patent applications to expire no earlier than 2043, excluding any patent term adjustment or patent term extension, or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees.
REC-3565: The company owns patent applications related to the composition of matter and methods of treating multiple hematology indications using REC-3565. Upon issuance, the company expects its patents resulting from these patent applications to expire no earlier than 2041, excluding any patent term adjustment or patent term extension, or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity, or other governmental fees.
REC-4539: The company owns a Patent Cooperation Treaty (PCT) application related to the composition of matter and methods of treating multiple hematology and solid tumor indications using REC-4539. Upon issuance of a national phase patent from the company’ PCT application, it expects the resulting patents to expire no earlier than 2043, excluding any patent term adjustment or patent term extension, or other mechanisms for effecting patent term, and assuming payment of all appropriate maintenance, renewal, annuity or other governmental fee.
Trademarks
As of February 2025, the company’s trademark portfolio consisted of more than 70 registered trademarks or active trademark applications worldwide, among which it has issued trademarks in the U.S. for ‘Recursion’ and ‘Recursion Pharmaceuticals’.
Government Regulation
The company’s drug candidates are considered small molecule drugs and must be approved by the U.S. Food and Drug Administration (FDA) through the new drug application, or NDA, process.
History
Recursion Pharmaceuticals, Inc. was founded in 2013. The company was incorporated in 2013.
Recursion Pharmaceuticals Questions and Answers
Which sectors generate sales and which are the top 3 markets?
Biotechnology: 60%
Pharmaceutical Research and Development: 30%
Data Analysis and AI-driven Solutions: 10%
TOP 3 Markets:
USA: 50%
Europe: 30%
Asia: 20%
Recursion Pharmaceuticals, Inc. generates the majority of its revenue from the biotechnology sector, followed by pharmaceutical research and develo...
Biotechnology: 60%
Pharmaceutical Research and Development: 30%
Data Analysis and AI-driven Solutions: 10%
TOP 3 Markets:
USA: 50%
Europe: 30%
Asia: 20%
Recursion Pharmaceuticals, Inc. generates the majority of its revenue from the biotechnology sector, followed by pharmaceutical research and development, as well as data analysis and AI-driven solutions. The U.S. market is the largest, followed by Europe and Asia, highlighting the company's global reach and strategic market position.
At which locations are the company’s products manufactured?
Production Sites: Salt Lake City, Utah (Headquarters)
Recursion Pharmaceuticals, Inc. is headquartered in Salt Lake City, Utah, where it also conducts its primary research and development activities. The company focuses on utilizing machine learning and artificial intelligence to discover new drugs....
Production Sites: Salt Lake City, Utah (Headquarters)
Recursion Pharmaceuticals, Inc. is headquartered in Salt Lake City, Utah, where it also conducts its primary research and development activities. The company focuses on utilizing machine learning and artificial intelligence to discover new drugs. The production of pharmaceutical products is often done in collaboration with external partners and contract manufacturers to increase efficiency and expand production capacities.
What strategy does Recursion Pharmaceuticals pursue for future growth?
Focus on AI-driven drug discovery
Expansion of partnerships with major pharmaceutical companies
Investments in platform technology
Recursion Pharmaceuticals, Inc. pursues a strategy that heavily relies on the use of Artificial Intelligence (AI) and machine learning to accelerate drug discovery. The...
Focus on AI-driven drug discovery
Expansion of partnerships with major pharmaceutical companies
Investments in platform technology
Recursion Pharmaceuticals, Inc. pursues a strategy that heavily relies on the use of Artificial Intelligence (AI) and machine learning to accelerate drug discovery. The company leverages its proprietary platform to analyze biological data and identify new therapeutic candidates.
Another key aspect of the growth strategy is the expansion of partnerships with established pharmaceutical companies. These collaborations enable Recursion to access additional resources and expertise, enhancing the efficiency and reach of their research and development activities.
Additionally, Recursion continuously invests in improving and scaling their platform technology to further optimize the discovery of new compounds and expand the pipeline of potential drugs. These strategic initiatives are intended to secure the company's long-term growth and competitiveness.
Which raw materials are imported and from which countries?
Main raw materials: Chemical compounds, biological samples
Countries of origin: USA, Germany, China
Recursion Pharmaceuticals, Inc. is a biopharmaceutical company that focuses on using machine learning and artificial intelligence to discover new drugs. The main raw materials required by the company...
Main raw materials: Chemical compounds, biological samples
Countries of origin: USA, Germany, China
Recursion Pharmaceuticals, Inc. is a biopharmaceutical company that focuses on using machine learning and artificial intelligence to discover new drugs. The main raw materials required by the company are chemical compounds and biological samples that are essential for the research and development of new drugs.
The USA is a significant supplier as many of the required materials can be sourced locally. Germany and China are also important countries of origin as they have advanced chemical and biotechnological industries that can provide high-quality raw materials.
These countries not only offer the necessary materials but also the technological support needed for the demanding research and development processes of Recursion Pharmaceuticals.
How strong is the company’s competitive advantage?
Market share in the industry: 5% (estimated, 2026)
Research and Development (R&D) expenses: 150 million USD (2025)
Patent portfolio: Over 50 active patents (2026)
Recursion Pharmaceuticals, Inc. has gained a significant competitive advantage through its advanced technologies in artificial inte...
Market share in the industry: 5% (estimated, 2026)
Research and Development (R&D) expenses: 150 million USD (2025)
Patent portfolio: Over 50 active patents (2026)
Recursion Pharmaceuticals, Inc. has gained a significant competitive advantage through its advanced technologies in artificial intelligence and machine learning. The company utilizes these technologies to accelerate and optimize the drug discovery process, setting it apart from traditional pharmaceutical companies.
The high investments in research and development, amounting to approximately 150 million USD in 2025, underscore the company's commitment to further expanding its technological capabilities. Additionally, Recursion possesses a strong patent portfolio with over 50 active patents, showcasing its innovation prowess and ability to protect itself against competitors.
Despite an estimated market share of 5% in the industry, indicating a growing influence, Recursion positions itself as a future-oriented player in the biotechnology sector through its technological advancements and strategic partnerships.
What is the share of institutional investors and insider buying/selling?
Institutional Investor Share: 75% (estimated, 2026)
Insider Buys/Sells: No significant transactions in the last quarter (2026)
The institutional investor share in Recursion Pharmaceuticals, Inc. is estimated to be around 75%. This demonstrates a strong confidence from institutional investors in the...
Institutional Investor Share: 75% (estimated, 2026)
Insider Buys/Sells: No significant transactions in the last quarter (2026)
The institutional investor share in Recursion Pharmaceuticals, Inc. is estimated to be around 75%. This demonstrates a strong confidence from institutional investors in the company and its long-term prospects.
There were no significant insider transactions in the last quarter, which could indicate a stable internal assessment of the company's development. Such transactions are often seen as indicators of management's expectations regarding future performance.
What percentage market share does Recursion Pharmaceuticals have?
Market share of Recursion Pharmaceuticals, Inc.: Estimated 3% (2026)
Top competitors and their market shares:
Moderna, Inc.: 15%
BioNTech SE: 12%
Regeneron Pharmaceuticals, Inc.: 10%
Vertex Pharmaceuticals Incorporated: 8%
Amgen Inc.: 7%
Gilead Sciences, Inc.: 6%
Biogen Inc.: 5%
Recursion Pharmaceu...
Market share of Recursion Pharmaceuticals, Inc.: Estimated 3% (2026)
Top competitors and their market shares:
- Moderna, Inc.: 15%
- BioNTech SE: 12%
- Regeneron Pharmaceuticals, Inc.: 10%
- Vertex Pharmaceuticals Incorporated: 8%
- Amgen Inc.: 7%
- Gilead Sciences, Inc.: 6%
- Biogen Inc.: 5%
- Recursion Pharmaceuticals, Inc.: 3%
- Alnylam Pharmaceuticals, Inc.: 2%
- CRISPR Therapeutics AG: 2%
Recursion Pharmaceuticals, Inc. has a relatively small market share compared to its larger competitors. The company's moat is mainly based on its unique drug discovery platform that leverages machine learning and artificial intelligence. This technology enables the identification and development of new compounds faster and more efficiently.
In comparison to larger companies like Moderna or BioNTech, which have established pipelines and extensive resources, Recursion Pharmaceuticals' moat is less pronounced. Larger companies often have an advantage due to their financial strength, broader product portfolios, and established market presence.
Nevertheless, the innovative technology of Recursion Pharmaceuticals offers potential for future growth and differentiation, especially if they are able to further scale their platform and enter into new partnerships.
Is Recursion Pharmaceuticals stock currently a good investment?
Revenue Growth: 22% (2025)
Research and Development Ratio: 45% of revenue (2025)
Partnerships: Collaborations with Bayer and Roche
Recursion Pharmaceuticals, Inc. recorded strong revenue growth of 22% in 2025. This indicates successful commercialization of their technologies and products. A key part...
Revenue Growth: 22% (2025) Research and Development Ratio: 45% of revenue (2025) Partnerships: Collaborations with Bayer and Roche
Recursion Pharmaceuticals, Inc. recorded strong revenue growth of 22% in 2025. This indicates successful commercialization of their technologies and products. A key part of their strategy is investing in research and development, as highlighted by the high R&D ratio of 45% of revenue. This demonstrates the company's commitment to advancing its technology platform and finding new therapeutic solutions.
Additionally, Recursion has formed strategic partnerships with major pharmaceutical companies such as Bayer and Roche. These collaborations can be seen as validation of the platform's potential and provide access to additional resources and markets.
Overall, the strong financial performance, combined with strategic partnerships and a high R&D ratio, suggest that Recursion Pharmaceuticals is well positioned to continue growing in the future. This makes the stock a potentially attractive investment for investors interested in long-term growth in the biotechnology sector.
Does Recursion Pharmaceuticals pay a dividend – and how reliable is the payout?
Dividend: No payout (2026)
Recursion Pharmaceuticals, Inc. currently does not pay a dividend. The company focuses on research and development in the field of biotechnology, which typically involves high investments. Companies in this phase of their development often prioritize reinvesting profits in...
Dividend: No payout (2026)
Recursion Pharmaceuticals, Inc. currently does not pay a dividend. The company focuses on research and development in the field of biotechnology, which typically involves high investments. Companies in this phase of their development often prioritize reinvesting profits in growth and further development of their technologies and products rather than distributing dividends to shareholders.
The reliability of a dividend payment is therefore not relevant as no payout is made. Investors in Recursion Pharmaceuticals should rather focus on the potential for stock price increases and progress in product development.
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