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Recursion Pharmaceuticals: AI for drug discovery

L’essentiel

Based in the United States, Recursion Pharmaceuticals combines experimental biology, automation and artificial intelligence to discover new drugs. Its merger with Exscientia, completed in 2024, brings together complementary approaches to biological exploration and molecular design.

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Based in the United States, Recursion Pharmaceuticals combines experimental biology, automation and artificial intelligence to discover new drugs. Its merger with Exscientia, completed in 2024, brings together complementary approaches to biological exploration and molecular design.


Recursion Pharmaceuticals, Inc. is an American biotechnology company based in Salt Lake City, Utah. It is developing an approach to pharmaceutical research in which laboratory experiments feed computational models, which in turn guide subsequent experiments. With an online presence at recursion.com, the company seeks to identify drug candidates by exploring the relationships between genes, molecules and cellular behaviors.

A biotech company born at the intersection of biology and computing

Founded in 2013 by Chris Gibson, Dean Li and Blake Borgeson, Recursion was built around one idea: using large-scale cellular imaging to identify biological effects that are difficult to detect through conventional methods. Its development thus combines automated laboratories, data science expertise and therapeutic research. The company went public on Nasdaq in 2021 under the ticker symbol RXRX.

In November 2024, it completed its merger with Exscientia, a British company specializing in artificial intelligence-assisted drug design. This transaction combines Recursion’s experimental exploration of biology with the molecular design and optimization tools developed by Exscientia. It also expands the combined company’s expertise and portfolio of programs.

Turning experimental data into therapeutic leads

The core of its platform, called Recursion OS, relies on a loop connecting data generation, computational analysis and experimental validation. Robotic systems conduct experiments on cells subjected to various perturbations, including genetic or chemical ones. The resulting images are analyzed to characterize the observed changes and identify similarities between certain biological profiles. These matches can suggest mechanisms of action or potential treatments to explore.

The aim is therefore not merely to predict a molecule’s properties on a computer. It is also to generate comparable experimental data and then test the hypotheses derived from the models. This approach requires substantial computing and storage capacity. In 2023, NVIDIA invested in Recursion and announced a collaboration intended to support its work in artificial intelligence applied to drug discovery.

Recursion develops its own therapeutic candidates and establishes partnerships with pharmaceutical groups. Agreements have notably been signed with Bayer, as well as with Roche and Genentech. These collaborations allow its tools to be applied to different areas of research while sharing some of the resources and risks involved in development.

What next?

The main challenge remains turning the platform’s findings into demonstrated therapeutic benefits for patients. An AI-generated hypothesis must still pass through biological validation, safety assessment and clinical trials. Integrating Exscientia’s expertise presents another challenge: effectively linking an understanding of diseases with molecular optimization. Recursion’s trajectory will therefore depend as much on the quality of its data and models as on clinical results, control over its spending and the strength of its partnerships.

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