In traditional drug discovery, 90% of drugs fail in clinical trials, after more than a decade in development and ~$2 billion in costs.
We’re changing the paradigm – leading with data, AI, and an industrialized approach to dramatically improve the cost, timeline, and probability of success of developing new medicines — because patients are waiting.
Our advanced preclinical and clinical-stage programs are focused on areas of high unmet need across oncology and rare diseases.
We’ve amassed one of the world’s largest relatable biological and chemical datasets across phenomics, transcriptomics, proteomics, InVivomics, ADME, and de-identified patient data.
Built in partnership with NVIDIA, BioHive-2 ranks as the 54th most powerful supercomputer by the Top 500 list in 2024.
We are leveraging partnerships with Big Pharmas and leading tech companies to expand our therapeutic reach, scale and improve our AI platform, and drive new discoveries.
Unlike traditional drug discovery, which begins with a specific target or hypothesis, we leverage the Recursion OS — our platform of interconnected technical and scientific tools spanning physical experimentation to in silico analysis. This platform, along with 65 petabytes of fit-for-purpose data, allows us to train machine learning models that can help us identify promising new targets and design highly optimized molecules that will become potential first-in-class and best-in-class medicines. Combined with hundreds of thousands of de-identified patient records from our partners Tempus and Helix, all of these data layers are connected in the Recursion OS, which is continuously learning and improving in a “virtuous cycle” feedback loop.
Learn how we generate dataInstead of evaluating a few programs over years to find a “hit,” our system allows us to evaluate hundreds of potential programs, and quickly funnel those into the most promising opportunities. We then use our precision chemistry platform to design the best chemical compounds for synthesis in our automated lab. With this system, we’re able to identify hit candidates in weeks, instead of years, and for thousands of dollars as opposed to millions.
Explore our pipeline