Early progress on accelerating drug development with Claude

Chapter 01: Case studies 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. So, over the past several months, we’ve partnered with six organizations to do so. We’ve also started drug discovery efforts of our own, including programs for rare childhood forms of muscular dystrophy, where Claude handles much of the scientific and operational work. This work serves our goals in three ways. First, it lets us better understand the strengths and limitations of our models in relation to a much wider range of drug development tasks (we’ve already prioritized specific improvements to our models based on what we’ve learned so far). Second, these programs can serve as case studies for the wider life sciences community. If Claude is to significantly increase the rate of new cures, we need to work with many more biotechnology firms and integrate Claude more deeply into their development processes. Third, these projects should, if their positive trajectories continue, have direct impact themselves. We’re optimistic that some may result in effective new medicines for the diseases they target, including food allergies, rare childhood diseases, and several forms of cancer.