Introducing GPT-Rosalind for life sciences research
OpenAI Blog · 2026-04-16
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Topics: life-sciences-aidrug-discoverybioinformaticsprotein-engineeringscientific-reasoning
Claims
- GPT-Rosalind is a domain-specific frontier reasoning model optimized for biology, drug discovery, and translational medicine workflows.
- On the LABBench2 benchmark, GPT-Rosalind outperforms GPT-5.4 on 6 out of 11 tasks, with the largest gain in CloningQA for molecular cloning protocol design.
- When evaluated by Dyno Therapeutics on an unpublished RNA sequence-to-function task, best-of-ten GPT-Rosalind submissions ranked above the 95th percentile of human experts on the prediction task.
- A freely accessible Life Sciences research plugin for Codex connects models to over 50 scientific tools and databases.
- Access to GPT-Rosalind is restricted to a trusted-access program for qualified U.S. Enterprise customers to mitigate biological misuse risks.
Key quotes
On average, it takes roughly 10 to 15 years to go from target discovery to regulatory approval for a new drug in the United States.
When evaluated directly in the Codex app, best-of-ten model submissions ranked above the 95th percentile of human experts on the prediction task and around the 84th percentile of human experts on the sequence generation task.
Over time, we expect these systems to become increasingly capable partners in discovery—helping scientists move faster from question to evidence, from evidence to insight, and from insight to new treatments for patients.