OpenAI is rolling out a significant model update to the GPT‑Rosalind series, which is purpose-built for life sciences research at enterprise scale. The update combines GPT‑5.5's agentic coding and tool-use capabilities with enhanced model intelligence in core drug-discovery areas such as medicinal chemistry and genomics, while also improving performance across broader life sciences analysis, design, and experimental workflows.
Progress in life sciences depends on synthesizing data and evidence across scales and modalities-molecules, genes, pathways, and living systems. In OpenAI's evaluations, the updated GPT‑Rosalind demonstrates broad performance gains on research tasks from biology experts, complex medicinal chemistry queries, quantitative biology, and wet lab troubleshooting.
GPT‑Rosalind is now available in research preview to eligible organizations globally through OpenAI's trusted-access deployment structure.
Improved Performance on Scientifically Valuable Tasks
To measure and continuously improve the real-world impact of GPT‑Rosalind, OpenAI designed LifeSciBench, an externally expert-judged benchmark centered on foundational aspects of life sciences research. Unlike existing benchmarks that evaluate a single component of model performance or biological domain in isolation, LifeSciBench takes an end-to-end view of scientifically valuable work by drawing tasks from six workflow areas central to life sciences research: evidence handling, analysis, design and optimization, scientific reasoning, validation and operations, and translation and communication. OpenAI uses this benchmark to align progress with the needs and realities of life sciences research.
GPT‑Rosalind leads performance across scientifically valuable tasks as identified by industry and academic experts.
Stronger Scientific Reasoning
Medicinal Chemistry
GPT‑Rosalind achieves industry-leading performance in medicinal chemistry-a field focused on turning molecules into useful drugs. OpenAI designed MedChemBench to reflect realistic medicinal chemistry workflows, evaluating multimodal chemical structure understanding, structure-activity relationships (SAR), prediction of drug potency, toxicity, and ADME properties, multiparameter lead-optimization decision-making, and retrosynthesis. GPT‑Rosalind outperforms GPT‑5.5, scoring 27.5% vs. 25.1% on MedChemBench, while using 7.2% fewer tokens.
Genomics and Quantitative Biology
On GeneBench, OpenAI's agentic evaluation for long-horizon, end-to-end analysis in genomics and quantitative biology, GPT‑Rosalind uses 31% fewer tokens than GPT‑5.5 while achieving higher accuracy (21.6% vs. 20.4%). GeneBench assesses agentic performance on long-horizon quantitative tasks: based on realistic scientific data, can an agent plan valid analysis, QC, modeling, and corrections to arrive at decision-relevant answers? The included problems span functional genomics, spatial transcriptomics, proteomics, epigenomics, and applied genetics.
Assisting Real-World Lab Work
OpenAI introduces a new evaluation called LabWorkBench to test GPT‑Rosalind's ability to help scientists conducting lab work. It tests the model's ability to link perturbations to experimental outcomes in real wet lab protocols, for purposes ranging from troubleshooting to optimization. The data used by LabWorkBench are proprietary and thus uncontaminated. GPT‑Rosalind scores 63.2% compared to GPT‑5.5's 55.8%, while using 5.3% fewer tokens.
From Reasoning to Executed Workflows
OpenAI built the Life Sciences Research and Life Sciences NGS Analysis plugins to extend GPT‑Rosalind's increased intelligence with a practical execution layer for repeatable scientific workflows. Together, these plugins bring sourced evidence retrieval, biological interpretation, and bioinformatics execution into the same workspace, helping researchers connect external evidence with internal omics analyses while preserving artifacts and provenance. All users can access both plugins through Codex, and qualified GPT‑Rosalind enterprise users can additionally use GPT‑Rosalind to power these plugins.
To better leverage Codex as a dynamic workbench for scientists, OpenAI added interactive viewers for biologically native file types. The initial set of sequence, alignment, and structure viewers are designed to keep scientists close to the evidence as GPT‑Rosalind reasons across a workflow and directly answer follow-up questions using the active viewer in-context.
Expanded Access for Trusted Organizations
OpenAI is expanding access to the GPT‑Rosalind series to eligible organizations globally. GPT‑Rosalind will be available in research preview through OpenAI's trusted-access deployment structure for organizations that are conducting legitimate scientific research with clear public benefit, have strong governance and safety oversight, and maintain controlled access with enterprise-grade security.
As part of this global expansion, Novo Nordisk is leveraging GPT‑Rosalind to help scale medical research, enabling researchers to analyze complex datasets, uncover useful patterns, and test hypotheses more quickly. GPT‑Rosalind's stronger biological understanding is expected to help teams connect evidence across literature, genomics, transcriptomics, sequence, structure, and experimental results.
OpenAI is also now offering a managed workspace for qualified organizations without an Enterprise account.
What's Next
The updated GPT‑Rosalind represents the next step in OpenAI's broader commitment to building AI systems that can help accelerate scientific discovery while ensuring that advanced biological capabilities are deployed with appropriate safeguards. OpenAI plans to continue improving the model's biological reasoning, expanding support for tool-heavy and long-horizon research workflows, and working with qualified organizations across regions to evaluate real-world impact.
This also means applying life sciences AI to high-impact public-benefit work-from drug discovery and translational medicine to public health, preparedness, and biodefense. Through Rosalind Biodefense and OpenAI's trusted-access deployment model, the aim is to put frontier biological capabilities in the hands of the researchers, institutions, and defenders working to improve human health and strengthen societal resilience.
OpenAI will continue building GPT‑Rosalind to become a more capable partner across the full life cycle of scientific research, helping scientists move more quickly from the right questions to clearer evidence, better experiments, and ultimately new treatments for patients.