BigHat

Anthropic's life sciences team reports that Claude has been used inside real drug programs at six organizations, on tasks reaching from molecule design to manufacturing-document review and regulatory filings. Discussion of AI in drug development has centered on proposing initial molecule designs, while manufacturing paperwork stayed manual, with chemists spending up to 75% of their time on records. In Enveda's test, Claude caught all 11 issues human reviewers had flagged across 1,061 pages of documentation and flagged seven more, cutting human review time by 89%, from over 25 hours to less than three; most of these results remain preclinical.

Anthropic's life sciences team reports that Claude has been used inside real drug programs at six organizations, on tasks reaching from molecule design to manufacturing-document review and regulatory filings. Discussion of AI in drug development has centered on proposing initial molecule designs, while manufacturing paperwork stayed manual, with chemists spending up to 75% of their time on records. In Enveda's test, Claude caught all 11 issues human reviewers had flagged across 1,061 pages of documentation and flagged seven more, cutting human review time by 89%, from over 25 hours to less than three; most of these results remain preclinical.

Turning an antibody into a drug means tuning binding, stability, aggregation and other properties that pull against one another, and lead optimization often takes months to years. Anthropic and BigHat had one researcher and Claude operate BigHat's automated lab via MCP to optimize one VHH and one single-chain Fv antibody across seven design rounds. In 10 weeks they synthesized and comprehensively tested 1,232 antibodies; the most improved variants of both bound their targets up to nine times more tightly, one reaching sub-nanomolar affinity, stayed stable in solution at temperatures up to 18°C higher, and aggregated far more slowly.

Turning an antibody into a drug means tuning binding, stability, aggregation and other properties that pull against one another, and lead optimization often takes months to years. Anthropic and BigHat had one researcher and Claude operate BigHat's automated lab via MCP to optimize one VHH and one single-chain Fv antibody across seven design rounds. In 10 weeks they synthesized and comprehensively tested 1,232 antibodies; the most improved variants of both bound their targets up to nine times more tightly, one reaching sub-nanomolar affinity, stayed stable in solution at temperatures up to 18°C higher, and aggregated far more slowly.