RXRX Stock: Insider Activity, Filings & Research
Recursion Pharmaceuticals, Inc. (RXRX) — Drillr’s hub for RXRX insider activity, SEC filings, earnings signals and AI research. Over the trailing 3 months, RXRX insiders filed 0 open-market buys and 11 sales (SEC Form 4).
RXRX insider trading activity (SEC Form 4)
| Date | Insider | Type | Shares | Price |
|---|---|---|---|---|
| Jun 4, 2026 | Bumpus Namandjedirector | Sell | 4,386 | $3.54 |
| Jun 4, 2026 | Borgeson Blakedirector | Sell | 30,000 | $3.68 |
| May 27, 2026 | Gibson Christopherdirector | Sell | 40,000 | $3.08 |
| May 19, 2026 | Gibson Christopherdirector | Tax | 22,821 | $3.04 |
| May 19, 2026 | Khan Najatdirector, officer: CEO and President | Tax | 62,701 | $3.04 |
| May 19, 2026 | Taylor Ben Rofficer: Chief Financial Officer | Tax | 25,018 | $3.04 |
| May 19, 2026 | Hallett Davidofficer: Chief Scientific Officer | Tax | 26,657 | $3.04 |
| May 8, 2026 | Gibson Christopherdirector | Sell | 40,000 | $3.37 |
| May 7, 2026 | Borgeson Blakedirector | Sell | 30,000 | $3.52 |
| Apr 24, 2026 | Gibson Christopherdirector | Sell | 40,000 | $3.61 |
| Apr 8, 2026 | Taylor Ben Rofficer: Chief Financial Officer | Tax | 48,028 | $3.11 |
| Apr 8, 2026 | Borgeson Blakedirector | Sell | 30,000 | $3.10 |
| Apr 8, 2026 | Gibson Christopherdirector | Sell | 40,000 | $3.10 |
| Apr 2, 2026 | Dar Zavaindirector | Grant | 4,902 | — |
| Apr 2, 2026 | Li Dean Ydirector | Grant | 3,268 | — |
Source: RXRX SEC Form 4 filings, latest Jun 4, 2026. For informational purposes only — not investment advice.
Recursion Pharmaceuticals, Inc. company profile
Overview
Recursion Pharmaceuticals, Inc. (NASDAQ:RXRX) is a clinical-stage biotechnology company founded in 2013 and headquartered in Salt Lake City, Utah. The company went public in April 2021 and represents a pioneering approach to drug discovery that combines artificial intelligence, automation, and massive biological data generation. Recursion has positioned itself at the forefront of the "TechBio" revolution, seeking to industrialize and accelerate the traditionally slow and expensive process of pharmaceutical development. In 2024, the company completed a strategic merger with Exscientia, another AI-driven drug discovery company, creating a combined entity with enhanced computational capabilities and an extended cash runway through 2027.
Business
Recursion operates in the biotechnology sector, specifically focusing on AI-driven drug discovery and development. The company has built what it calls an integrated platform that combines biology, chemistry, automation, data science, and engineering to systematically decode biological systems and identify potential therapeutic compounds. The core technology revolves around phenomics - the large-scale study of biological phenotypes (observable characteristics) at the cellular level. Recursion's automated laboratories can generate millions of microscopic images of cells under different experimental conditions, creating what the company calls "phenomaps." These phenomaps capture how cells respond to various genetic perturbations, chemical compounds, or disease states. The company processes over 6.2 million multi-timepoint brightfield images weekly and has generated nearly 1 million transcriptomes (complete sets of RNA transcripts). The company's business model centers on two main revenue streams. First, Recursion develops its own proprietary drug candidates across multiple therapeutic areas including oncology, rare diseases, infectious diseases, and immunology. The company currently has over five internally developed programs in clinical or near-clinical stages, with programs like REC-617 (a CDK7 inhibitor for cancer), REC-994 (for cerebral cavernous malformation), and REC-4881 (for familial adenomatous polyposis) showing promising early results. Second, Recursion partners with major pharmaceutical companies to apply its platform to their drug discovery needs. The company has established collaborations with industry giants including Roche/Genentech, Sanofi, Bayer, and others. These partnerships typically involve upfront payments, milestone payments as programs advance, and potential royalties on successful drugs. To date, Recursion has earned approximately $450 million through four major collaborations. The 2024 merger with Exscientia significantly expanded Recursion's capabilities by adding advanced generative AI for molecular design and automated synthesis platforms. This combination created what the company calls "Recursion 2.0," integrating biological exploration capabilities with precision chemistry and AI-driven molecular design.
Revenue model
Recursion generates revenue through two primary business models. The partnership model provides the most immediate revenue, with the company earning milestone payments, upfront fees, and potential future royalties from pharmaceutical collaborations. Major partners include Roche/Genentech, Sanofi, and Bayer, with the company having earned $450 million to date across four collaborations. These partnerships can potentially generate over $20 billion in milestone payments before royalties, with approximately $200 million in potential milestones expected over the next two years. The proprietary drug development model represents the longer-term, higher-value opportunity. Recursion develops its own drug candidates through clinical trials, with the potential for either licensing deals with larger pharmaceutical companies or eventual commercialization. The company currently has over five internally developed programs with first-or-best-in-class potential advancing through clinical development. Several factors influence Recursion's margins and profitability prospects. Positive factors include the scalability of its AI platform, which can theoretically reduce the time and cost of drug discovery compared to traditional methods. The company's automated systems can run millions of experiments efficiently, and successful AI models can be applied across multiple drug programs. Strategic partnerships provide non-dilutive funding and validation of the platform's capabilities. However, margin pressures come from the inherent risks and costs of drug development. Clinical trials remain expensive and time-consuming, with high failure rates industry-wide. The company currently burns approximately $450 million annually in cash, primarily on research and development activities. Competition in the AI-driven drug discovery space is intensifying, with both established pharmaceutical companies and other biotech startups developing similar capabilities. Additionally, regulatory approval processes remain lengthy and uncertain, regardless of the discovery method used. The company's ability to achieve profitability will largely depend on successful clinical trial outcomes, the ability to secure additional high-value partnerships, and the potential for platform licensing or acquisition by larger pharmaceutical companies seeking AI capabilities.
Competitive moat
Recursion's competitive moat centers on its massive proprietary biological dataset and the network effects created by its integrated platform. The company has generated over 50 petabytes of biological and chemical data, representing one of the world's largest collections of cellular phenotypic data. This dataset becomes more valuable as it grows, creating a reinforcing cycle where more data improves AI model performance, which in turn generates better drug candidates and attracts more partnerships, funding additional data generation. The technical moat includes several components. Recursion's automated laboratory systems can generate 2.2 million experiments per week, a scale that would be difficult and expensive for competitors to replicate. The company's BioHive-2 supercomputer, developed in partnership with NVIDIA, provides 23.32 petaflops of computing power specifically optimized for biological data analysis. The integration of multiple data types - phenomics, transcriptomics, genomics, and chemical data - creates a comprehensive biological understanding that individual datasets cannot provide. However, this moat faces several challenges. Large pharmaceutical companies are increasingly developing internal AI capabilities and may not need to rely on external platforms long-term. Technology giants like Google, Microsoft, and Amazon are applying their AI expertise to drug discovery, potentially offering superior computational resources. The core technologies - machine learning, automated microscopy, and robotics - are not proprietary to Recursion and can be replicated by well-funded competitors. The regulatory environment also limits the moat's strength. Regardless of discovery method, all drug candidates must undergo the same clinical trial and approval processes, where Recursion competes on equal footing with traditionally discovered drugs. The company's ultimate success depends on clinical trial outcomes, which remain inherently unpredictable despite AI optimization. The moat appears moderately strong in the near term due to data network effects and technical scale, but faces significant long-term challenges from well-resourced competitors and the fundamental uncertainties of drug development.
Risks & safety
Recursion maintains a reasonable margin of safety despite operating losses, primarily due to strong cash reserves and extended runway. **Cash Position and Solvency:** - Cash and short-term investments: $500.5 million as of Q1 2025 - Current ratio: 4.11, indicating strong short-term liquidity - Debt-to-equity ratio: 0.10, representing minimal debt burden - Cash runway extended to mid-2027 based on current burn rate - Annual cash burn targeted at ≤$450 million **Valuation Metrics:** - Trading at 2.3x book value, reasonable for a growth biotech - Negative earnings multiples due to R&D-heavy business model - Enterprise value reflects significant cash position - Graham net-net ratio of 0.41 indicates trading below liquidation value **Other Considerations:** - Strong partnership validation with $450 million earned from collaborations - Multiple clinical programs reducing single-point-of-failure risk - Post-merger operational synergies expected to save >$100 million annually - Potential milestone payments of ~$200 million over next two years provide upside optionality
Recent development
Recursion has undergone significant strategic evolution over the past few years, marked by three major developments. The most transformative was the 2024 merger with Exscientia, creating "Recursion 2.0" with combined capabilities in biological exploration and precision chemistry. This merger brought together complementary AI platforms, with Recursion's phenomics expertise combining with Exscientia's generative AI for molecular design and automated synthesis capabilities. The company has strategically focused its clinical pipeline, recently announcing the deprioritization of three programs (neurofibromatosis type 2, cerebral cavernous malformation, and C. difficile colitis) while placing its LSD1 program on strategic pause. This portfolio rationalization allows Recursion to concentrate resources on its most promising oncology and rare disease programs, including the CDK7 inhibitor REC-617, which has shown encouraging early monotherapy activity. Platform development has accelerated significantly with the launch of BioHive-2, a 23.32 petaflop supercomputer developed in partnership with NVIDIA, potentially making it the fastest in the biopharmaceutical industry. The company has also introduced foundation models like Phenom-1 and developed LOWE (Large Language Model-Orchestrated Workflow Engine) for scientific workflow automation. These technological advances support the company's vision of moving toward autonomous drug discovery. Partnership strategy has evolved from simple collaboration agreements to more strategic, long-term relationships. Beyond the existing partnerships with Roche/Genentech, Sanofi, and Bayer, Recursion has expanded into data partnerships, including a collaboration with Tempus for genomic data integration. The company has also opened a London office to attract computational biology talent and established advisory relationships with leading AI researchers like Michael Bronstein. The company's approach to drug development has shifted toward precision medicine, leveraging AI for patient population selection, biomarker identification, and study design optimization. This represents a move beyond traditional drug discovery toward what the company calls "precision patient selection" and the development of companion diagnostics alongside therapeutic compounds.
RXRX company profile · for informational purposes only — not investment advice.
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