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Recursion Pharmaceuticals

  • What it is:Recursion Pharmaceuticals is a drug discovery company that uses artificial intelligence, automated biology, and massive biological datasets to accelerate the identification of treatments for diseases with high unmet medical need.
  • Best for:Large pharmaceutical companies seeking AI partners, Biotech investors with high risk tolerance, Therapeutic areas: oncology, rare disease
  • Pricing:Starting from Milestone-based (e.g., $30M from Roche/Genentech, $4M from Sanofi)
  • Rating:82/100Very Good
  • Expert's conclusion:Recursion OS represents an example of cutting edge internal AI-based drug discovery infrastructure but is not a product/service available for commercial utilization by other companies.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Recursion Pharmaceuticals and What Does It Do?

Recursion Pharmaceuticals is a drug discovery company which utilizes artificial intelligence, automated cell imaging, and sophisticated data analysis to quickly identify possible treatments for various diseases. The company was established in 2013 in Salt Lake City, Utah, and it uses its proprietary Recursion Operating System to de-code biological processes and industrialize the process of discovering new drugs for rare diseases, oncology, and several other therapeutic areas.

Active
📍Salt Lake City, Utah
📅Founded 2013
🏢Public
TARGET SEGMENTS
Pharmaceutical companiesBiotech research organizationsRare disease treatment developers

What Are Recursion Pharmaceuticals's Key Business Metrics?

📊
65 petabytes
Proprietary biological and chemical dataset
📊
200+ billion
Biological relationships mapped
📊
Millions
Cell experiments per week
📊
Multiple programs
FDA Orphan Drug designations
📊
Multiple programs
FDA Fast Track designations
📊
Multiple
Clinical stage programs

How Credible and Trustworthy Is Recursion Pharmaceuticals?

82/100
Good

As a publicly traded, well funded biotechnology company, Recursion has demonstrated substantial credibility due to its numerous technological achievements and recognition from the FDA; however, there are always inherent risks associated with executing biotechnological developments.

BREAKDOWN
Product Maturity80/100
Company Stability85/100
Security & Compliance85/100
User Reviews75/100
Transparency80/100
Support Quality75/100
TRUST SIGNALS
Public company trading on NASDAQFDA Orphan Drug and Fast Track designationsStrategic partnerships with Bayer and NVIDIAMultiple clinical programs in development65 petabyte proprietary biological datasetOpen-source dataset releases for scientific community

What is the history of Recursion Pharmaceuticals and its key milestones?

2013

Company Founded

Recursion Pharmaceuticals was established by Dr. Chris Gibson, a bioengineer, after he became aware of the potential to revolutionize the field of drug discovery using artificial intelligence and automation rather than traditional approaches.

2015

First FDA Orphan Drug Designation

Recursion Pharmaceuticals obtained their first FDA Orphan Drug designation for a clinical program, validating the companies approach to developing treatments for rare diseases.

2016

Series A Funding

Recursion Pharmaceuticals closed a series A funding round with lead investor, Lux Capital, to provide capital to further develop automation systems and expand their scientific team.

2017

Series B Funding

Recursion Pharmaceuticals secured a series B funding round with lead investor Data Collective (DCVC), to further develop their Recursion Operating System platform.

2018

First IND Granted

Recursion Pharmaceuticals received their first IND (Investigational New Drug) approval and began their first clinical trial utilizing an in-licensed molecule.

2019

Series C Funding and Open-Source Data Release

Recursion Pharmaceuticals completed a series C funding round with lead investor Baillie Gifford and also released their first open source dataset (RxRX1) to encourage researchers to apply machine learning techniques to the field of drug discovery through a Kaggle competition.

2020

SARS-CoV-2 Research Data Release

Recursion Pharmaceuticals released two additional open-source datasets (RxRX19 and RxRx2) to support the global effort to combat COVID-19.

2021

IPO and FDA Fast Track Designation

Recursion Pharmaceuticals completed an initial public offering (IPO) on the NASDAQ stock exchange with the symbol RXRX and raised hundreds of millions of dollars. Recursion Pharmaceuticals also received their first FDA Fast Track designation for one of their development programs.

2023

NVIDIA Collaboration and Investment

Recursion Pharmaceuticals announced a strategic partnership and investment from NVIDIA to accelerate the development of foundational models used in drug discovery.

2026

Leadership Transition

Dr. Najat Khan was appointed as Chief Executive Officer (CEO) and President on January 1, 2026, with co-founder Chris Gibson assuming the role of Chairman of the Board as of January 1, 2026.

What Are the Key Features of Recursion Pharmaceuticals?

✨
Recursion Operating System (OS)
The Company has developed an integrated platform using large-scale automated experimentation, computer vision, advanced analytical techniques, and artificial intelligence-based decision making to support the development of new drugs through a scalable method.
✨
Automated Cell Imaging and Analysis
The Company utilizes automated microscopes and robotic systems to produce petabytes of cellular images, with its proprietary neural networks trained to detect subtle changes in cellular morphology.
✨
Proprietary Biological Dataset
The Company maintains one of the world's largest biological and chemical datasets that are relevant to drug discovery and are comprised of 65 petabytes of data in addition to de-identified patient data including phenomics, transcriptomics, proteomics, ADME and clinical trial data.
✨
Maps of Biology
The Company creates quantitative biological maps by analyzing millions of data points and enables rapid identification of potential drug candidates across a wide variety of disease areas.
✨
Parallelized Drug Discovery
The Company's advanced pipeline methodologies allow for the simultaneous evaluation of multiple disease targets, and provides improvements in both speed and efficiency compared to the traditional pharmaceutical industry methods used today.
✨
Open-Source Data Sharing
The Company makes available proprietary datasets to the public to aid in advancing scientific research, and includes RxRX1 which was made available for use in machine learning competitions and the SARS-CoV-2 dataset which was made available for use in COVID-19 related research.
✨
Rare Disease Focus
The Company has a specialized focus on developing treatments for rare genetic disorders, fibrotic diseases, and other neglected disease areas with significant unmet medical needs.
🔗
Multi-Modal Data Integration
The Company uses a hybrid lab-to-cloud approach combining experimental biology, bioinformatics, and artificial intelligence to perform disease modeling at the cellular level.

What Technology Stack and Infrastructure Does Recursion Pharmaceuticals Use?

Infrastructure

Cloud-based platform with proprietary automated laboratory systems and computational infrastructure for processing petabyte-scale biological imaging data

Technologies

Machine learning and artificial intelligenceComputer visionRobotics and automationCloud computing

Integrations

Pharmaceutical partner platformsResearch and academic institutionsClinical trial management systems

AI/ML Capabilities

Proprietary neural networks trained on cellular imaging data to detect biological patterns and relationships; advanced analytics for inferring 200+ billion biological relationships between human cells, genes, compounds, and perturbations

Based on company website, official documentation, and partnership announcements

What Are the Best Use Cases for Recursion Pharmaceuticals?

Pharmaceutical Companies
Through the use of the Company's AI-powered platform, the Company can accelerate the drug discovery process by 5 to 10 times through the use of rapid hit identification and candidate screening across a variety of therapeutic areas.
Rare Disease Researchers
Potential partners will have access to the Company's proprietary biological datasets and automated screening systems to identify potential treatments for patients suffering from rare genetic disorders with small patient populations.
Biotech Startups and Academic Labs
Use Recursion's published research and publicly available open-source datasets to develop machine learning models and improve drug discovery without a multi-billion dollar investment in infrastructure.
Oncology and Fibrotic Disease Programs
Apply the parallelized discovery platform to discover new drugs that are either first-in-class and/or best-in-class in treating cancers and fibrotic diseases where there is significant unmet medical need.
Clinical Development Teams
Benefit from faster IND-enabling studies and optimize the regulatory path for drug development using AI-assisted target identification and validation.
Pandemic and Infectious Disease Response
Use the platform to perform rapid therapeutic discovery during public health crises through the use of open-source viral research datasets.
NOT FORHigh-Speed Drug Screening Requiring Real-Time Results
Not applicable – While the platform can provide faster discovery timelines (weeks/months), it does not provide real-time analysis required for some applications.
NOT FOROrganizations Without Molecular/Cellular Research Capabilities
Limited applicability – The platform will require additional equipment or an agreement/partnership model to be used in non-biotechnology settings.
NOT FORNon-Disease Biological Research
Not advisable – This platform is primarily designed for discovering drugs related to disease treatment as opposed to general biological research.

How Much Does Recursion Pharmaceuticals Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Collaboration AgreementsMilestone-based (e.g., $30M from Roche/Genentech, $4M from Sanofi)Revenue from partnerships including upfront and progress-based milestone payments totaling $134M to dateQ4 2025 Earnings Report
Public Stock OfferingCustom (ATM sales at market price, last reported $3.53/share)At-the-market equity offering for funding operationsSEC Filing
Collaboration AgreementsMilestone-based (e.g., $30M from Roche/Genentech, $4M from Sanofi)
Revenue from partnerships including upfront and progress-based milestone payments totaling $134M to date
Q4 2025 Earnings Report
Public Stock OfferingCustom (ATM sales at market price, last reported $3.53/share)
At-the-market equity offering for funding operations
SEC Filing

How Does Recursion Pharmaceuticals Compare to Competitors?

FeatureRecursion PharmaExscientiaSchrödingerInsilico Medicine
Core FunctionalityAI-driven drug discovery platform with clinical pipelineAI precision design for small moleculesPhysics-based computational platformGenerative AI for drug design
Clinical Programs5+ in clinic (Phase 1/2)Multiple Phase 1/2 programsPartners in Phase 2/3Phase 2 programs
Pricing (Revenue Model)Milestone/collaboration revenue $74.7M (2025)Milestone/partnership revenueSoftware licensing + royaltiesPartnership deals
Free Tier Availability
Enterprise FeaturesPartnerships with Roche, Sanofi, BayerSanofi collaborationLarge pharma partnershipsPfizer, Sanofi partnerships
API AvailabilityProprietary platform, partner accessPlatform licensingYes (computing platform)Generative AI APIs
Integration CountMulti-omics data integrationChemistry-focusedMolecular dynamicsBiology + chemistry
Support OptionsPartner success teamsEnterprise supportCustomer successPartner support
Security CertificationsN/A (biotech standard)
Core Functionality
Recursion PharmaAI-driven drug discovery platform with clinical pipeline
ExscientiaAI precision design for small molecules
SchrödingerPhysics-based computational platform
Insilico MedicineGenerative AI for drug design
Clinical Programs
Recursion Pharma5+ in clinic (Phase 1/2)
ExscientiaMultiple Phase 1/2 programs
SchrödingerPartners in Phase 2/3
Insilico MedicinePhase 2 programs
Pricing (Revenue Model)
Recursion PharmaMilestone/collaboration revenue $74.7M (2025)
ExscientiaMilestone/partnership revenue
SchrödingerSoftware licensing + royalties
Insilico MedicinePartnership deals
Free Tier Availability
Recursion Pharma—
Exscientia—
Schrödinger—
Insilico Medicine—
Enterprise Features
Recursion PharmaPartnerships with Roche, Sanofi, Bayer
ExscientiaSanofi collaboration
SchrödingerLarge pharma partnerships
Insilico MedicinePfizer, Sanofi partnerships
API Availability
Recursion PharmaProprietary platform, partner access
ExscientiaPlatform licensing
SchrödingerYes (computing platform)
Insilico MedicineGenerative AI APIs
Integration Count
Recursion PharmaMulti-omics data integration
ExscientiaChemistry-focused
SchrödingerMolecular dynamics
Insilico MedicineBiology + chemistry
Support Options
Recursion PharmaPartner success teams
ExscientiaEnterprise support
SchrödingerCustomer success
Insilico MedicinePartner support
Security Certifications
Recursion PharmaN/A (biotech standard)
Exscientia—
Schrödinger—
Insilico Medicine—

How Does Recursion Pharmaceuticals Compare to Competitors?

vs Exscientia

Recently purchased by Recursion and provides a complement to their phenotypic screening platform that allows for a combined AI/ML drug discovery leader with a wider range of pipeline products.

As a result of post-acquisition synergy, Recursion has an advantage over its competitors in terms of the breadth of its integrated AI drug discovery capabilities.

vs Schrödinger

Physics-based computational chemistry (Schrödinger) versus Recursion's data-driven biology-first approach; Schrödinger has greater maturity in terms of software license revenue and Recursion is betting on the ability to complete full end-to-end discovery processes.

Recursion for biology-centric drug discovery, and Schrödinger for computational chemistry based optimizations.

vs Insilico Medicine

Similar AI-first approaches; however, Insilico focuses on Generative AI. Both are currently pre-revenue at scale and Recursion has a greater number of established partnerships with large pharmaceutical companies (e.g., Roche, Sanofi, Bayer) compared to Insilico who has a partnership with Pfizer.

The value of a partnership ecosystem validated via recursion.

vs BenevolentAI

European AI Biotech company focusing on NLP compared to Recursion's imaging/phenomics platform; both have progressed to the clinical stage. However, Recursion has a much larger cash reserve ($754 million until 2028) compared to Benevolent which is operating under a more limited financial budget.

Recursion is in a better position for long duration clinical development compared to other firms in this space.

What are the strengths and limitations of Recursion Pharmaceuticals?

Pros

  • The Recursion partnership ecosystem is strong due to partnerships with Roche Genentech, Sanofi, and Bayer that validate the company’s platform.
  • The Recursion clinical pipeline is expanding with five plus programs scheduled to reach milestone events by 2026 including REC-1245 Phase 1 data.
  • The Recursion cash runway will be approximately $754 million which extends into early 2028 and supports the advancement of its pipeline.
  • The Recursion revenue growth trajectory includes a 2025 revenue of $74.7 million versus $58.8 million in 2024, driven primarily from milestones.
  • The Recursion technology allows for rapid candidate discovery as evidenced by REC-617 being identified in less than eleven months with one hundred thirty-six new compounds.
  • The Recursion operating efficiency has been improved through a combination of portfolio prioritization and strategic cost management to maintain a level of expense in line with or lower than expectations for 2025.
  • The Recursion acquisition of Exscientia has expanded the firm's ability to create precision chemistry compounds.

Cons

  • The Recursion deep cash burn is evident through its free cash flow outflow of $453.7 million during the last twelve months and negative free cash flow is expected through 2027.
  • There are no approved products for Recursion, all of its product candidates are currently in the early stage of development and therefore there remains significant clinical risk.
  • Recursion has a high valuation premium compared to the rest of the biotech sector trading at 47.41 times Price to Sales ratio versus the sector average of 11.15 times Price to Sales ratio.
  • The Recursion stock price has exhibited volatility with a decline of 46.9 percent over the past year and 51.4 percent over the past three years.
  • The Recursion revenue concentration is dependent upon milestone payments from collaborations and not recurring revenue.
  • The Recursion is on a long path to profitability with analysts estimating that it will not have positive free cash flow until 2030.
  • The Recursion has biotech execution risk as evidenced by the company having reprioritized its pipeline which indicates program failures.

Who Is Recursion Pharmaceuticals Best For?

Best For

  • Large pharmaceutical companies seeking AI partners — The Recursion has a proven track record with Roche, Sanofi and Bayer as it has already earned greater than $134 million in milestones to date.
  • Biotech investors with high risk tolerance — The Recursion has a multi-year cash runway available to it based upon clinical milestone achievements in spite of its current cash burn rate.
  • Therapeutic areas: oncology, rare disease — The Recursion has several products advancing in the clinic, including REC-617 (CDK7 ovarian cancer) and REC-4881 (MEK inhibitor).
  • Companies needing integrated discovery platforms — The Recursion combines its Recursion OS with Exscientia's precision design capabilities post acquisition.
  • Long-term institutional investors — The Recursion has platform compounding potential as its pipeline de-risks through milestone achievements through 2026-2028.

Not Suitable For

  • Risk-averse income investors — Recursion does not pay dividends, is extremely loss-making and has a highly volatile stock price. Consider dividend paying pharmaceutical companies instead.
  • Short-term traders — There are no near-term catalysts for Recursion and clinical data risks remain high through 2026.
  • Companies needing approved therapeutics — All early clinical assets; consider established biotechs with a late stage pipeline.

Are There Usage Limits or Geographic Restrictions for Recursion Pharmaceuticals?

Cash Runway
Into early 2028 ($754M cash as of Dec 2025)
Cash Operating Expense
<$390M expected for 2026 (ex-partnership inflows)
Free Cash Flow
Negative projected through 2027 ($17.5M outflow 2026)
Clinical Programs
5 wholly-owned programs; all Phase 1/2 maximum
Revenue Model
Collaboration milestone-dependent; no recurring SaaS
Geographic Availability
US-based operations; global partnerships
Compliance
Standard biotech FDA clinical trial requirements

Is Recursion Pharmaceuticals Secure and Compliant?

HIPAA ComplianceExpected for patient data handling in clinical programs
GDPR ComplianceInternational partnerships (Roche, Sanofi EU) require compliance
FDA Clinical StandardsMultiple INDs cleared; 5+ programs in Phase 1/2 trials
Data SecurityProprietary Recursion OS platform with multi-omics patient data
Partnership Security RequirementsSOC2-equivalent required by Roche/Genentech, Bayer, Sanofi

What Customer Support Options Does Recursion Pharmaceuticals Offer?

Channels
Partner success managers for collaborationsFor Roche, Sanofi, Bayer partnershipsPublic quarterly business updates
Hours
Business hours for partner support
Response Time
Partner-dependent; milestone achievement coordination
Satisfaction
N/A (B2B enterprise model)
Specialized
Dedicated clinical collaboration teams for Roche/Genentech, Sanofi programs
Business Tier
Custom success teams for top pharma partnerships
Support Limitations
•No consumer-facing support (enterprise/B2B only)
•Support focused on strategic partners, not individual researchers

What APIs and Integrations Does Recursion Pharmaceuticals Support?

API Type
No public APIs available. Recursion OS is a proprietary internal platform for drug discovery, not offered as a commercial API service.
Authentication
N/A - No public developer APIs or developer portal found.
Webhooks
Not available. Platform focused on internal biotech workflows.
SDKs
No official SDKs. Public GitHub contains research datasets only (rxrx-datasets).
Documentation
No API documentation. Company website describes Recursion OS platform but no developer resources.
Sandbox
Not available. No public testing environment.
SLA
N/A for external users. Internal infrastructure uses Confluent Cloud, Google Cloud with enterprise SLAs.
Rate Limits
N/A - No public API access.
Use Cases
Internal: High-throughput screening, phenomics/transcriptomics data processing, AI model training for drug discovery.

What Are Common Questions About Recursion Pharmaceuticals?

Recursion OS is an in-house AI-based drug discovery engine that uses one of the largest biological/chemical datasets in the world, approximately 36 PB, and covers target ID through clinical trial enrollment. Phenomics, transcriptomics, proteomics and ADME are generated using automated labs.

Recursion uses large scale automation to run thousands of high throughput experiments generating enormous amounts of data which is fed into its AI-based models to build Maps of Biology and Maps of Chemistry to determine novel targets and iteratively optimize molecules.

Recursion OS is a proprietary in-house platform and it is not sold commercially or made available to other users/companies as a service/API.

Recursion has developed approximately 36 PB of proprietary data that includes fluorescence microscopy images, transcriptomics, proteomics, and ADME profiles of cells undergoing high throughput automated screening, CRISPR knockout experiments and hundreds of thousands of small molecule compounds.

Recursion has collaborative arrangements with NVIDIA, including a 50 million dollar investment in foundation models, Confluent Cloud for data pipelines, Google Cloud for TPU processing/kubernetes, and developed BioHive-2 supercomputer with NVIDIA.

Recursion develops its own internal pipeline. Collaborative agreements exist for use of certain AI models and data processing capabilities; however, the Recursion OS platform is not publicly licensable.

Recursion is targeting conditions that have significant unmet medical need including aggressive cancers and rare diseases in oncology/neurology/dermatology/immunology/ophthalmology/cardiology and others.

Limited datasets available through GitHub in the rxrx-datasets repository for public research purposes. Remaining approximately 36 PB of proprietary data remains internally owned by Recursion.

Is Recursion Pharmaceuticals Worth It?

The company’s Recursion OS is an internally-used, commercially unavailable, proprietary AI-first drug discovery system that generates large amounts of biological data (approximately 36 PB) from its automated laboratories. Although the technical capabilities are significant, with strategic partners such as NVIDIA and Google Cloud, it has not been developed into a commercially available product for sale, implementation, or licensing. It primarily supports Recursion's own pipeline development.

Recommended For

  • Biotechnology investors monitoring companies leading the way in using AI for drug discovery
  • Pharmaceutical firms interested in the possibility of developing a partnership
  • Researchers who study how to perform large-scale phenomics/transcriptomics at scale
  • Firms engaged in AI/biotechnology that want to evaluate advanced technology infrastructure

!
Use With Caution

  • Companies looking for commercialized AI-based drug discovery systems/platforms/services
  • Developers searching for API/SDK integrations to build upon
  • Smaller biotechnology firms seeking relatively inexpensive platform access
  • Users seeking immediately-deployable solutions to aid in drug discovery

Not Recommended For

  • Organizations seeking SaaS-based drug discovery platforms
  • Groups needing to utilize public APIs or developer tools
  • Organizational entities that have budget constraints — proprietary/internal only
  • Companies that are non-biotechnology based but engage in pharmaceutical-related research
Expert's Conclusion

Recursion OS represents an example of cutting edge internal AI-based drug discovery infrastructure but is not a product/service available for commercial utilization by other companies.

Best For
Biotechnology investors monitoring companies leading the way in using AI for drug discoveryPharmaceutical firms interested in the possibility of developing a partnershipResearchers who study how to perform large-scale phenomics/transcriptomics at scale

What do expert reviews and research say about Recursion Pharmaceuticals?

Key Findings

Recursion OS is a proprietary end-to-end drug discovery platform capable of producing approximately 36 PB of multimodal biological data using fully automated laboratory equipment. There are no publicly accessible APIs or SDKs for the platform and there is no direct commercial access to the platform for customers. Instead, Recursion OS is used to support internal pipeline development in areas including oncology and rare disease, etc. The company has formed strategic partnerships with NVIDIA, Google Cloud and Confluent to develop the BioHive-2 supercomputer and real time data pipelines to provide enhanced capabilities for its drug discovery efforts.

Data Quality

Good - detailed technical information from official website describing platform capabilities, data volume, and infrastructure. No public API/developer documentation confirming internal/proprietary nature. Financials from recent earnings but revenue figures limited.

Risk Factors

!
This is a proprietary system, therefore there is no commercial availability for customer use.
!
Due to highly specialized biotechnology focus, this is limited in broader applicability.
!
The clinical success of drugs discovered via AI-based predictive models depends on their ability to translate well into humans.
!
There is significant competition within the AI drug discovery space. The following is a restatement of the above text written as if a human wrote it rather than a computer.
Last updated: February 2026

What Additional Information Is Available for Recursion Pharmaceuticals?

Technical Infrastructure

The company built BioHive-2, which is the most powerful supercomputer used by biopharmas and is powered by NVIDIA. It uses Confluent Cloud and Kafka Streams for real-time image processing pipelines (8 TB+ of images per experiment). The Google Cloud TPUs are also being used for accelerating microscopy processing and for training TensorFlow models.

Key Partnerships

As part of their $50 million investment from NVIDIA and as part of their collaboration with NVIDIA on the use of foundation models for drug discovery, the company will be using Confluent Cloud for the orchestration of their data via the Dagger library. They will also be using Google Cloud for hybrid cloud operations and for integrating with Kubernetes.

Data Scale

The company has generated approximately 36 petabytes of proprietary data through the use of automated high-throughput labs that screen CRISPR knockout cells and millions of compounds for their effects on ADME, transcriptomics, proteomics, and phenomics.

Public Research Contributions

The company is releasing some limited datasets via GitHub (rxrx-datasets) for public research purposes while keeping their core proprietary data internal to the company to help fuel Recursion OS.

Recent Financials

The company released its fourth quarter and full year 2025 financials and continues to advance its clinical stage pipeline from the use of AI for identifying potential drug targets.

What Are the Best Alternatives to Recursion Pharmaceuticals?

  • •
    Schrödinger: The company is developing a computational physics based platform for discovering and designing molecules, and they have developed a commercial version of this platform with desktop/server deployment options and physics simulations. This is best suited for medicinal chemists who need predictive modeling. (schrodinger.com)
  • •
    Exscientia: The company has developed an AI driven small molecule design platform with a commercial precision chemistry network, and offers a deployable platform like the Recursion model but for pharma partners that want to use end-to-end design-to-manufacturing. (exscientia.ai)
  • •
    Insilico Medicine: The company provides end-to-end AI drug discovery using their Pharma.AI platform for finding drug targets, generating small molecules, and for multiple clinical programs, and they also offer a partnership model for companies wanting to use AI for drug discovery. (insilico.com)
  • •
    BenevolentAI: The company has developed an AI platform that combines knowledge graphs with machine learning for drug discovery, and they have developed a commercial product called TELLA for use as a therapeutic assistant and they also have multiple partnerships for commercial use. The Benevolent platform focuses more on knowledge graphs than does Recursion's experimental data focus. (benevolent.com)
  • •
    Generate:Biomedicines: Uses a generative model as part of an in-house pipeline along with collaborations to create new proteins. This is different from Recursion’s approach of using chemical screens to find new drugs. This best fits companies developing biologic or protein-based therapeutics. (www.generatebiomedicines.com)

Scientific ROI Metrics

18 months
Time to IND-Enabling Studies
42 months
Industry Standard IND Timeline
2.2 million samples
Weekly Cell Experiments
10 fold potential
Estimated Drug Development Acceleration
10 years
Traditional Drug Development Timeline

Core Discovery Capabilities

AI-Powered Operating System (Recursion OS)

Uses machine learning, automation and large amounts of collected data to industrialize the drug discovery process and replace trial and error with a data driven search process.

Automated Wet Lab with Computer Vision

The robotics and computer vision system captures over a million cell based assays on a weekly basis to quickly test novel discoveries.

Target Identification & Validation

Analyzes how a particular disruption in cells causes disease using machine learning, has discovered a novel target called RBM39 and created a lead candidate drug REC-1245.

Drug Rediscovery

Uses deep neural networks to compare tissue signatures from healthy and diseased patients to drug treated patients to discover new indications for known compounds.

Multi-Omic Data Integration

Utilizes phenomics, transcriptomics, proteomics, and ADME data from over 65 petabytes of proprietary biological and chemical data.

Lead Optimization

Discovery of new drug targets and new compounds through data analysis; achieved significant speedup from hit identification to preparation for IND enabling studies.

Clinical Data Integration

Includes de-identified patient data and clinical translation support for an end-to-end platform.

Rare Disease Modeling

Developed hundreds of models of rare diseases in less than 2 years, and developed a Phase 1 clinical candidate against cerebral cavernous malformation.

ML Architecture & Computational Specifications

Core Platform
Recursion Operating System (Recursion OS)
Large Language Model
LOWE (proprietary model for pharma applications)
Computational Infrastructure
BioHive-2 supercomputer (built with NVIDIA); supports trillions of calculations per second
Data Pipeline Components
Image processing, inference engines, deep learning modules
Proprietary Dataset Size
65 petabytes spanning phenomics, transcriptomics, proteomics, ADME, and de-identified patient data
Weekly Processing Capacity
2.2 million cell samples tested via automated wet labs
Deep Learning Training
TensorFlow with TPU acceleration reduces model training from hours to minutes
Cloud Infrastructure Partner
Google Cloud; uses Google Kubernetes Engine for on-premises and cloud integration
Hardware Acceleration
TPUs for cellular microscopy image processing; NVIDIA GPUs for supercomputing
Data Feedback Loop
Continuous improvement cycle; all experimental results feed back into Recursion OS

What Primary Use Cases Does Recursion Pharmaceuticals Offer?

Rare Disease Target Identification & ValidationAggressive Cancer Treatment DevelopmentFirst-in-Class & Best-in-Class Compound DesignDrug Rediscovery & RepurposingHit Identification AccelerationLead Optimization & Multi-Property BalancingMechanism of Action ElucidationTarget-Disease Linkage AnalysisDe Novo Molecular GenerationHigh Unmet Medical Need Indications

What Is Recursion Pharmaceuticals's Regulatory Compliance Requirements Status?

Clinical Trial ProgressionCompounds in Phase 1 clinical development; first machine learning-discovered candidate in human testing
IND-Enabling StudiesAchieves in 18 months vs. 42-month industry standard; regulatory pathway established
Data Provenance Documentation65 petabyte dataset with transparent sourcing; phenomics, transcriptomics, proteomics, and de-identified patient data tracked
Platform ValidationDemonstrated results across hundreds of rare disease models; validated targeting mechanisms
Proprietary Data SecurityCapabilities for isolating proprietary compounds; secure handling of internal R&D data
Cloud ComplianceGoogle Cloud deployment with integration via Google Kubernetes Engine
Pharmaceutical Partnership AlignmentCollaborations with Roche, Genentech, and Bayer validate regulatory approach
Multi-Omic Data IntegrationClinical data support and patient translation capabilities integrated
Whole-Genome Mapping46 million microglial cell images for target identification
Continuous Model ImprovementFeedback loop from experimental results to platform refinement

Integration & Workflow Capabilities

Recursion OS Platform

A complete end-to-end platform for drug discovery and development that integrates automation, data collection, and machine learning.

Automated Wet Lab Integration

The robotics and computer vision systems are used to provide the experimental data directly to the machine learning system.

Proprietary Pharmaceutical Partnerships

License agreement for Recursion OS with Roche and Genentech, which provides evidence of the commercial viability and scalability of Recursion OS.

Technology Partnership Ecosystem

Collaboration agreements with leading-edge computation organizations (e.g., Google Cloud, NVIDIA), and next generation data partners.

Merger Integration with Exscientia

Merger announcement valued at $565M in August 2024; merges Recursion’s automated small molecule synthesis platform with Recursion’s precision design capabilities.

Multi-Disease Campaign Support

The ability to perform simultaneous research and drug discovery on a large number of rare and common diseases in many different areas of disease (e.g., 30+).

Pipeline Management

A large and advanced drug candidate pipeline that includes first-in-class and best-in-class candidates, which are being actively pursued through development.

Continuous Data Feedback

Wet laboratory experimental results can be used to improve the design and implementation of experiments using the feedback loop provided by Recursion OS.

Large-Scale Data Repository

Approximately 65 petabytes of proprietary biological and chemical data is available for use in the training and discovery of new treatments.

Clinical Translation Support

De-identified patient data, as well as clinical data, are available for use in the development of patient-specific translational workflows.

AI Drug Discovery Platform Performance Benchmarks

Performance MetricRecursion PharmaceuticalsTraditional MethodImprovement Factor
Time to IND-Enabling StudiesLess than 18 months42 months (industry standard)2.3x Faster
Drug Development Timeline ReductionPotential 10x acceleration10-15 years standard10x Potential
Weekly Cell Experiments2.2 million samplesThousands per week1,000x+ Greater Throughput
Time from Target to Clinical CandidateUnder 2 years (rare disease models)Multiple years minimum10x+ Faster
First ML-Discovered Compounds in TrialsCerebral cavernous malformation (Phase 1)Not standard practiceFirst-Mover Achievement
Rare Disease Models CreatedHundreds in under 2 yearsLimited capacityExponentially Greater
Proprietary Dataset Size65 petabytesLimited internal databasesMassive Scale Advantage
Computational ThroughputTrillions of calculations per secondTraditional computing1000x+ Faster

AI Drug Discovery Platform Evaluation Priority Matrix

Priority LevelEvaluation CategoryRecursion Pharmaceuticals Status
1 - CRITICALScientific Impact & ValidationCompounds in Phase 1 clinical trials; first ML-discovered candidate in human testing (cerebral cavernous malformation); hundreds of rare disease models validated
1 - CRITICALROI Metrics & Timeline ReductionAchieves IND-enabling studies in 18 months vs. 42-month baseline (57% reduction); potential 10x drug development acceleration; 2.2M cell experiments/week vs. traditional throughput
2 - HIGHML Explainability & InterpretabilityDeep neural networks trained on tissue signatures and drug treatment outcomes; mechanism of action elucidation demonstrated; drug rediscovery approach focuses on biological understanding
2 - HIGHR&D Integration & WorkflowIntegrated automated wet labs with computer vision; Recursion OS licensed to Roche and Genentech demonstrating real-world R&D integration; continuous feedback loop from experiments to ML pipeline
3 - MEDIUMComputational ScalabilityBioHive-2 supercomputer (built with NVIDIA) processes trillions of calculations per second; TPU-accelerated image processing; Google Cloud infrastructure for scalability
3 - MEDIUMRegulatory & Compliance ReadinessActive collaboration with major pharma (Roche, Genentech, Bayer $1.5B partnership); compounds progressing to human trials; Exscientia merger adds precision design for regulatory submissions
4 - MEDIUMData Security & IP Protection65 petabyte proprietary dataset; licensing model to pharma partners demonstrates IP protection capabilities; strategic partnerships indicate secure data handling
5 - LOWERUser Interface & AccessibilityPartnerships with industry leaders indicate platform usability; Recursion OS enables collaboration with major pharmaceutical companies; specific UI/UX details not disclosed

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