A Wall Street research shop just tried its hand at drug discovery. It brought an AI model instead of a lab coat. Citrini Research, working with Anthropic, used the Claude Science model to hunt for potential scorpion antivenom candidates. The experiment produced roughly a year’s worth of early-stage design work in a matter of days. Then it produced something analysts care about even more: an investment thesis. From a 35-page prompt to lab results Citrini’s analysts fed Claude Science a detailed prompt of ~35 pages. Out came approximately 180 candidate molecules aimed at neutralizing scorpion toxins. According to the research findings, work of that scope would normally take a year using traditional methods. Citrini compressed it into a short window. That is where Twist Bioscience came in. The lab synthesized and tested 211 designs. Of those, 17 successfully bound to the target toxins. Seventeen hits might not sound like a blowout. In early-stage drug discovery, where most candidates fail, it was enough to beat Citrini’s own expectations. The bottleneck moves from software to the lab On October 20, 2026, Citrini published a report laying out what it learned. The core argument is less ...
Wall Street researchers used Claude to design drug candidates, and the trade is in the lab
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