Recursion
AI-driven drug discovery platform decoding biology to radically improve lives
Enterprise·Technical·Powered by Proprietary (Recursion OS)
Key strengths
Largest proprietary biological/chemical dataset (>50 petabytes)Automated wet lab with robotics capturing millions of cell experiments per weekBioHive-2 supercomputer built with NVIDIA for biopharma computeIntegrated Recursion OS platform covering hit ID to IND-enabling studiesActive clinical pipeline across oncology and rare disease indications
Enterprise pricing
Salt Lake City, USA
Founded 2013
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- High-content phenotypic screening – Using computer vision and deep learning on cell imaging data to identify disease-relevant phenotypic signatures at massive scale.
- Multi-omic data integration – Combining phenomics, transcriptomics, proteomics, and ADME datasets into unified ML-ready representations for target and pathway discovery.
- Generative molecule design – Training generative AI models on proprietary chemical datasets to design and optimize small molecules with desired therapeutic properties.
- Target deconvolution – Leveraging large biological maps to identify previously unknown disease targets from cellular perturbation experiments.
- IND-enabling study acceleration – Applying Recursion OS predictions to compress preclinical timelines by reducing experimental iteration cycles in toxicology and efficacy profiling.
- Supercomputer-scale model training – Utilizing BioHive-2 (NVIDIA partnership) to train and fine-tune foundation models on petabyte-scale proprietary biological datasets.