Artificial intelligence is fundamentally rewiring how medicines are discovered, designed, and brought to market. The CEOs leading this transformation are compressing timelines that once took a decade into years, and in some cases, months. From generative protein design to AI-optimized clinical trials, these leaders are building the platforms that the world’s largest pharmaceutical companies now depend on.
Companies are listed in alphabetical order. This list is non-exhaustive.
1. Absci: Sean McClain, Founder & CEO
Headquarters: Vancouver, WA | Total Funding: ~$228M+
Sean McClain founded Absci around a bold premise: that generative AI can design better biologics from scratch. Absci’s Integrated Drug Creation Platform uses AI models trained on proprietary wet-lab data to design novel antibodies against difficult-to-drug targets, combining computational protein design with high-throughput experimental validation in a single integrated loop.
Under McClain’s leadership, Absci has secured partnerships with Merck and Astellas for AI-driven drug development and raised $125M in crossover financing. The company’s acquisition of Denovium’s deep learning platform for protein engineering further strengthened its position at the intersection of generative AI and synthetic biology, a space where McClain has positioned Absci as one of the few companies that can both design and make AI-generated biologics.
2. Atomwise (now Numerion Labs): Abraham Heifets, Co-Founder & Former CEO
Headquarters: San Francisco, CA | Total Funding: ~$219M
Abraham Heifets co-founded Atomwise — now rebranded as Numerion Labs Tracxn — as one of the earliest companies to apply deep learning to structure-based drug discovery. The AtomNet platform uses convolutional neural networks, originally designed for image recognition, to predict how small molecules will bind to protein targets, screening billions of compounds computationally in a fraction of the time traditional high-throughput screening requires.
Heifets filed the foundational patent for applying convolutional networks to spatial molecular data, a technique that has since influenced the entire computational drug discovery field. Atomwise claimed its AI delivered results 100x faster than ultra-high-throughput screening, and the company built a broad portfolio of pharmaceutical partnerships since its founding in 2012, making it one of the longest-running AI drug discovery companies in operation.
Heifets departed the company in May 2024 after more than a dozen years Rssing, with his exit not publicly announced at the time. Steve Worland, Ph.D. was subsequently appointed as CEO in February 2025.
3. BenevolentAI: Kenneth Mulvaney, CEO
Headquarters: London, United Kingdom | Total Funding: ~$200M+ (including $90M from Temasek in 2024)
Kenneth Mulvaney took the CEO role at BenevolentAI in May 2024, bringing operational discipline to one of Europe’s most prominent AI drug discovery companies. BenevolentAI’s platform applies machine learning to extract insights from vast repositories of unstructured biomedical data, including scientific literature, patents, and clinical records, to identify novel drug targets and therapeutic hypotheses that human researchers would miss.
Mulvaney’s appointment came alongside a $90M investment from Singapore’s Temasek and a broader strategic restructuring designed to focus the company’s pipeline and accelerate its path to clinical readouts. BenevolentAI, which is publicly listed, represents one of the highest-profile bets on AI-driven target discovery in the life sciences, and Mulvaney’s mandate is to translate that platform into clinical and commercial results.
4. Chai Discovery: Josh Meier, Co-Founder & CEO
Headquarters: San Francisco, CA | Total Funding: ~$225M+
Josh Meier co-founded Chai Discovery to build frontier AI models that can predict and reprogram interactions between biochemical molecules. The company’s foundation models specialize in molecular design, with a particular focus on AI-designed antibodies and proteins for therapeutic applications, pushing beyond structure prediction into functional protein engineering.
Chai Discovery raised a $130M Series B in December 2025 at a $1.3B valuation, backed by OpenAI among others, and announced its Chai 2 computational model for antibody design. Pfizer’s CSO joined the board, a signal of how seriously big pharma is taking Meier’s approach. At just two years old, Chai Discovery has already achieved unicorn status and positioned itself at the frontier of generative biology.
5. Cradle Bio: Stef van Grieken, Founder & CEO
Headquarters: Amsterdam, Netherlands | Total Funding: ~$102M
Stef van Grieken founded Cradle Bio to make AI-powered protein engineering accessible as a SaaS platform, a fundamentally different business model than most AI drug discovery companies, which typically operate as drug developers themselves. Cradle’s protein language models help biotech and pharma teams design protein sequences with desired properties, accelerating the development of biologics, enzymes, and other protein-based therapeutics.
The approach has resonated: Cradle now counts 4 of the top 10 global pharma companies among its 21 customers, including Johnson & Johnson and Novo Nordisk, with 31 molecules in development on the platform. Van Grieken raised a $73M Series B in November 2024 led by Index Ventures, and the SaaS model, which avoids royalty complications, has made Cradle one of the most capital-efficient companies in the AI life sciences space.
6. Deep Genomics: Brendan Frey, Founder & CEO
Headquarters: Toronto, Canada | Total Funding: ~$400M+
Brendan Frey brings a rare pedigree to AI drug discovery: he is a co-inventor of foundational deep learning systems and a professor at the University of Toronto, the institution where much of modern deep learning was born. He founded Deep Genomics to apply AI to the discovery and development of RNA therapeutics for genetic diseases, building an AI Workbench that combines AI-driven target discovery with therapeutic design optimization.
Deep Genomics raised a $180M Series C led by SoftBank Vision Fund 2 and has developed 10 programs with 4 advancing toward the clinic within two years, a pace that underscores the platform’s ability to compress traditional drug discovery timelines. Frey’s academic credentials and the company’s focus on genetic medicines position Deep Genomics at the intersection of two of biology’s most promising frontiers: AI and RNA therapeutics.
7. Dyno Therapeutics: Eric Kelsic, Founder & CEO
Headquarters: Cambridge, MA | Total Funding: ~$150M+
Eric Kelsic founded Dyno Therapeutics to solve one of gene therapy’s hardest problems: delivery. The company’s AI platform engineers adeno-associated viral (AAV) vectors, the vehicles that carry therapeutic genes into cells, by combining high-throughput in vivo screening with machine learning to optimize capsid design for safe, targeted delivery to specific tissues and organs.
Dyno was the first company to combine ML with in vivo data for AAV optimization, and its $100M Series A from Andreessen Horowitz in 2021 signaled the venture world’s confidence in the approach. Kelsic’s CapsidMap platform has become a foundational tool for next-generation gene therapies, and the company’s partnerships position it as the infrastructure layer for an industry that has long been bottlenecked by delivery challenges.
8. Exscientia (now part of Recursion Pharmaceuticals): Dave Hallett, Chief Scientific Officer
Headquarters: Oxford, United Kingdom | Parent: Recursion Pharmaceuticals (NASDAQ: RXRX)
Dave Hallett is one of the most credentialed scientific leaders in AI-driven drug design — a fact that hasn’t changed regardless of the corporate structure around him. He stepped into the CEO role at Exscientia in an interim capacity following the departure of founder Andrew Hopkins in early 2024, bringing deep scientific authority to a company navigating a pivotal transition. Under his leadership, Exscientia continued advancing multiple clinical-stage programs built on its platform, which integrates machine learning with automated chemistry, biology, and physics to design novel small molecules and biologics.
Exscientia’s defining achievement — advancing the first AI-designed drug candidate into human clinical trials (EXS5004) — remains one of the most significant proof points in the entire field, and that milestone belongs to the scientific team Hallett helped lead. Following Exscientia’s combination with Recursion Pharmaceuticals in late 2024, Hallett assumed the role of Chief Scientific Officer of the combined entity, where he now oversees the scientific direction of one of the most ambitious AI drug discovery platforms in the world. His journey from CSO to interim CEO to CSO of a much larger combined organization reflects both the respect he commands in the field and the premium placed on scientific leadership as AI drug discovery matures from platform-building into clinical delivery.
9. Generate:Biomedicines: Michael Nally, CEO
Headquarters: Cambridge, MA | Total Funding: ~$673M+ (including $400M IPO, September 2024)
Michael Nally leads Generate:Biomedicines, the company that coined the term “Generative Biology” to describe its approach: using machine learning to program proteins for specific therapeutic functions. The platform leverages a training set of 160,000 protein structures and 190 million genetic sequences to design AI-engineered protein therapeutics, essentially treating protein design as a generative AI problem.
Generate closed the largest biotech Series C ($273M) in 2023, then raised $400M in its September 2024 IPO. The company’s $1B+ partnership with Novartis, which included $65M upfront, validated the generative biology approach at scale, and the company now has a Phase 3 TSLP antibody program underway. Nally’s leadership of a publicly traded generative biology company makes him one of the most closely watched CEOs in the AI life sciences space.
10. Genesis Therapeutics: Evan Feinberg, Co-Founder & CEO
Headquarters: San Francisco, CA | Total Funding: ~$327M+
Evan Feinberg co-founded Genesis Therapeutics to build GEMS, a generative and predictive AI platform for small molecule drug design. The platform integrates deep learning models, molecular simulations, and molecular generative AI to discover novel therapeutics, combining computational approaches that are typically siloed across different companies and academic groups.
Feinberg, a Stanford PhD from the lab of pioneering computational biologist Vijay Pande, raised a $200M Series B with NVentures (NVIDIA’s venture arm) increasing its stake, a signal that GPU-native molecular simulation is becoming a strategic priority for the AI infrastructure giants. Genesis has also partnered with Incyte for AI-based small molecule discovery, translating its computational platform into real pharmaceutical pipelines.
11. Iambic Therapeutics: Tom Miller, Co-Founder & CEO
Headquarters: San Diego, CA | Total Funding: ~$306M+
Tom Miller, PhD, co-founded Iambic Therapeutics to build an AI drug discovery platform that operates on weekly design-make-test cycles, a cadence that traditional drug discovery simply can’t match. The platform’s core technologies include Enchant, a multimodal transformer that predicts clinical and preclinical outcomes, and NeuralPLexer, a protein structure predictor that enables rapid computational screening.
Miller raised a $100M+ oversubscribed Series C in November 2025 from investors including Sequoia, Qatar Investment Authority, and Illumina Ventures, and the company was named to CNBC’s Disruptor 50 list in 2025. A partnership with Takeda further validates the platform’s commercial traction. Miller’s background in computational chemistry and the company’s weekly iteration speed position Iambic as one of the fastest-moving AI drug discovery companies in the field.
12. Insilico Medicine: Alex Zhavoronkov, Founder & CEO
Headquarters: Hong Kong / New York, NY | Total Funding: ~$700M+ (including $293M IPO on Hong Kong Stock Exchange, December 2025)
Alex Zhavoronkov, PhD, founded Insilico Medicine to accelerate the entire drug discovery pipeline using generative AI, from target identification through molecule design to clinical development. The company’s platform has produced 10+ programs in its pipeline and attracted partnerships with major pharmaceutical companies, including a deal with Eli Lillyworth up to $2.75 billion.
Zhavoronkov raised a $110M Series E in January 2025, then took Insilico public on the Hong Kong Stock Exchange in December 2025 with a $293M IPO, making it one of the first AI drug discovery companies to list in Asia. The company now operates across 6 countries and continues to expand its pharma partnership portfolio. Zhavoronkov’s prolific publishing record, having authored hundreds of papers on AI in drug discovery and aging, has made him one of the most visible scientific voices in the field.
13. Insitro: Daphne Koller, Founder & CEO
Headquarters: San Francisco, CA | Total Funding: ~$700M+
Daphne Koller is one of the most credentialed founders in all of AI: a Stanford professor, MacArthur Fellow (2004), co-founder of Coursera, and one of the pioneers of probabilistic graphical models. She founded Insitro to combine machine learning with cell-based disease models, creating a “pipeline-through-platform” approach that analyzes genetic, phenotypic, and clinical data to discover new drugs for metabolic diseases and neurological conditions.
Insitro raised a $400M Series C led by Canada Pension Plan Investment Board and Andreessen Horowitz, and has built a partnership portfolio that includes a 5-year collaboration with Bristol Myers Squibb worth $50M upfront and up to $2B if successful, as well as an expanded partnership with Eli Lilly. Koller’s combination of academic prestige, AI expertise, and ability to attract top-tier capital makes Insitro one of the most closely watched companies in the AI life sciences space.
14. Isomorphic Labs: Demis Hassabis, Founder & CEO
Headquarters: London, United Kingdom | Parent: Alphabet/Google
Demis Hassabis needs little introduction: he is the co-founder and CEO of Google DeepMind, the winner of the 2024 Nobel Prize in Chemistry for AlphaFold, and arguably the single most influential figure in the application of AI to biology. He founded Isomorphic Labs as a spinoff from DeepMind to apply AlphaFold’s protein structure prediction capabilities, and its successors, directly to drug discovery.
Isomorphic raised a record $600M Series A in March 2025 and has secured partnerships with Novartis, Eli Lilly, and GSK to co-develop AI-designed therapeutics targeting what the industry calls “undruggable” proteins. Hassabis’s vision is to use AI to unlock the $100B+ AI drug discovery opportunity, and with the Nobel Prize, DeepMind’s research infrastructure, and Alphabet’s resources behind him, Isomorphic Labs starts with advantages that no other company in the space can match.
15. PostEra: Aaron Morris, CEO
Headquarters: Boston, MA | Total Funding: ~$26M+ (plus $1B+ in partnership commitments)
Aaron Morris leads PostEra, the AI-powered medicinal chemistry platform that made its name by co-leading the COVID Moonshot, one of the largest open-science drug discovery collaborations in history, launched in March 2020. PostEra’s Proton platform automates molecular design and synthesis planning, using AI to accelerate the medicinal chemistry workflow that is often the slowest step in drug development.
What PostEra lacks in venture funding it makes up for in pharmaceutical validation: the company has secured over $1B in partnership commitments, including a $610M expansion with Pfizer and collaborations with Amgen and the NIH. Morris has built a company that operates at the intersection of open science and commercial drug discovery, a positioning that has earned both credibility with the research community and commercial traction with big pharma.
16. Recursion Pharmaceuticals: Najat Khan, CEO & President
Headquarters: Salt Lake City, UT | NASDAQ: RXRX | Total Funding: $1B+
Najat Khan became CEO of Recursion Pharmaceuticals on January 1, 2026, taking the reins from founder Chris Gibson (who transitioned to Founder and Chairman) to lead the next phase of growth for one of the most ambitious AI drug discovery companies in the world. Recursion’s platform uses high-resolution microscopy and machine learning to map disease biology at massive scale, integrating computational approaches with biological experimentation across genetic, cellular, and animal models.
Recursion’s pharmaceutical partnership portfolio is staggering: collaborations with Roche/Genentech, Bayer, Sanofi, and Merck KGaA valued at up to $20B collectively. Khan, who previously led R&D strategy at Johnson & Johnson, brings deep pharmaceutical industry experience to a publicly traded company that has built one of the largest proprietary biological datasets in the world. Her appointment signals Recursion’s shift from platform-building to pipeline-delivering.
17. Relay Therapeutics: Sanjiv Patel, CEO
Headquarters: Cambridge, MA | NASDAQ: RLAY
Sanjiv Patel leads Relay Therapeutics, the company that has built its drug discovery platform around a concept most competitors overlook: protein motion. While traditional structure-based drug design works from static snapshots of proteins, Relay’s platform uses AI and computational biophysics to model how proteins move and flex over time, revealing transient “allosteric” pockets that static models miss entirely.
This dynamic approach to drug design has allowed Relay to pursue targets that are considered undruggable by conventional methods. The company is publicly traded on NASDAQ and has multiple programs in clinical development. Patel’s leadership has kept Relay focused on translating its computational advantage into clinical-stage assets, a critical transition that separates platform companies from drug companies in the eyes of investors and pharma partners.
18. Schrödinger: Ramy Farid, CEO
Headquarters: New York, NY | NASDAQ: SDGR
Ramy Farid leads Schrödinger, the company that has spent decades building what is arguably the most sophisticated physics-based computational platform in drug discovery. While many AI drug discovery companies rely primarily on data-driven machine learning, Schrödinger integrates first-principles physics with AI to model molecular behavior, an approach that provides a deeper understanding of why molecules behave as they do, not just predictions of what they’ll do.
Schrödinger’s partnership portfolio includes a $2.3B collaboration with Novartis, a $10M grant from the Gates Foundation for toxicity prediction, and dozens of pharmaceutical collaborations. As a publicly traded company, Schrödinger also advances its own internal drug discovery pipeline. Farid has built a company that serves as essential infrastructure for computational drug discovery across the pharmaceutical industry, a position that gives Schrödinger both recurring software revenue and pipeline optionality.
19. Tempus AI: Eric Lefkofsky, Founder & CEO
Headquarters: Chicago, IL | NASDAQ: TEM (IPO June 2024)
Eric Lefkofsky founded Tempus AI to unlock the diagnostic and therapeutic insights buried in clinical and molecular patient data. The platform aggregates multimodal data, including genomic sequences, clinical records, imaging, and pathology, and applies AI and machine learning to guide treatment decisions, identify biomarkers, and accelerate drug development. It’s used by leading health systems and pharmaceutical companies to connect patient data with precision medicine.
Lefkofsky, a serial entrepreneur who co-founded Groupon, took Tempus public in June 2024, a milestone that validated the company’s data-first approach to AI in life sciences. While Tempus operates across diagnostics and clinical decision support as well as drug discovery, its data assets and AI platform make it an increasingly important infrastructure player for pharmaceutical R&D. The company’s scale of clinical data and its ability to connect that data with AI-driven insights give it a moat that pure-play computational companies can’t easily replicate.
20. Terray Therapeutics: Jacob Berlin, Co-Founder & CEO
Headquarters: Pasadena, CA | Total Funding: ~$226M+
Jacob Berlin, PhD, co-founded Terray Therapeutics to merge nanotechnology with generative AI for small molecule drug discovery. Terray’s tNova platform uses proprietary microarray technology to run millions of chemical experiments simultaneously at the nanoscale, generating massive datasets that feed directly into ML models for drug design. It’s an approach that combines the rigor of experimental chemistry with the speed of computational screening.
Terray raised a $120M Series B in October 2024 led by Bedford Ridge Capital and NVentures (NVIDIA), signaling that the marriage of wet-lab nanotechnology and AI is attracting serious infrastructure capital. Berlin’s approach addresses a fundamental limitation of purely computational drug discovery: the models are only as good as the data they’re trained on, and Terray generates orders of magnitude more experimental data than traditional approaches.
Who Did We Miss?
The AI drug discovery landscape is evolving at a remarkable pace, with new companies and approaches emerging regularly. If there’s a CEO or company you think belongs on this list, we want to hear about it for the next one we publish. Drop your nominations in the comments below or reach out to our editorial team.
