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Anthropic expands Claude drug discovery with six partnerships

AI summary

Anthropic announced research partnerships with six drug-development organizations, began its own drug-discovery work and acquired Mithril Medicine, whose founder used Claude to coordinate 11 external laboratories and two rare-disease programs. In disclosed partner work, Claude helped design molecules, analyze laboratory data and review manufacturing records, including an experiment at BigHat Biosciences that tested about 1,010 variants in roughly 10 weeks. Anthropic said most of the research remains early and preclinical, with little or no human testing yet.

In-depth insight

The disclosures place Claude in experimental workflows spanning molecular design, laboratory analysis, manufacturing review and clinical planning, while Anthropic states that most programs have not reached human testing.

Anthropic’s life sciences team is working to accelerate curing disease. Over the past several months, our scientists have engaged in deep research partnerships with six organizations developing new medicines: BigHat Biosciences, Bristol Myers Squibb, Divergence Labs, Enveda, Generate Biomedicines, and The Column Group. We've also begun drug discovery efforts of our own. In doing so, we've learned a lot about how Claude can support drug development, and how we’ll need to improve Claude further to realize AI's potential in medicine. We plan to scale this work up substantially from here.

There are many opportunities to speed up drug development, even beyond the most commonly discussed applications of AI, like proposing initial designs for new molecules. Developing a drug involves many varied tasks: doing early research to identify a target for a drug and the right type of drug to engage it, designing a molecule with the right properties, optimizing it to be manufactured reliably at scale, drafting the regulatory filings needed to run clinical trials, designing and administering those trials, and much more.

Our strategy to realize AI’s medical benefits is based on having AI increasingly involved in all of these tasks. There is no single problem to solve; the bottlenecks are distributed all throughout the drug development process. The best way to identify and work through these bottlenecks is to get deeply involved in real drug programs, across many different disease areas and stages of development.

#Anthropic#Claude#Claude Code#Mithril Medicine#BigHat Biosciences#Bristol Myers Squibb#Divergence Labs#Enveda#Generate Biomedicines#The Column Group#NVIDIA H100

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