概要
公開日: 2026-06-03
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原文
June 3, 2026 Product Research Release Introducing new capabilities to GPT‑Rosalind Bringing greater intelligence grounded in real scientific workflows for the life sciences industry. Request access Share We’re introducing a new model update to our GPT‑Rosalind series purpose-built for life sciences research at enterprise scale. It combines GPT‑5.5’s agentic coding and tool-use capabilities with stronger model intelligence in core drug-discovery domains such as medicinal chemistry and genomics, while advancing 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 our evaluations, the updated GPT‑Rosalind shows 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 our trusted-access deployment structure. Improving performance on scientifically-valuable tasks In order to measure and continuously improve the real-world impact of GPT‑Rosalind, we designed LifeSciBench, an externally expert-judged benchmark focused on foundational aspects in 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. We use this benchmark to align progress with the needs and realities of life sciences research. GPT‑Rosalind leads performance across scientifically-valuable tasks identified by industry and academic experts. Evidence Handling Analysis Design, Optimization, & Prediction Reasoning Validation & Operations Translation & Scientific Communication Extracting, reconciling, and auditing scientific evidence from papers, figures, tables, and experimental records. Eval Example We’re preparing for a Type B FDA meeting on AAV9-microDys-X, an AAV9-based micro-dystrophin gene therapy for Duchenne muscular dystrophy that expresses a 138 kDa construct from an MCK promoter, and we want a hard-nosed critique of whether our current package really supports accelerated approval on micro-dystrophin expression as a surrogate endpoint reasonably likely to predict clinical benefit. Study context: open-label Phase 1b/2 in 12 ambulatory boys age 4–7 with confirmed DMD and out-of-frame rod-domain deletions. The package is: Pre-treatment vastus lateralis biopsies: 0–3% of healthy-control dystrophin by quantitative Western blot using MANEX1A against the N-terminal actin-binding domain. 12-week post-treatment contralateral vastus lateralis biopsies: mean micro-dystrophin 38% of healthy control (range 18–61%) by the same Western blot, normalized to total protein by Coomassie staining. Post-treatment immunofluorescence: sarcolemmal signal in 75–95% of fibers using a polyclonal anti-dystrophin C-terminal antibody. 48-week function: mean NSAA change +1.4 points from baseline versus −0.6 in an external published natural-history registry cohort (p = 0.03 by unpaired t-test). Safety: transient transaminitis in 8/12 patients managed with steroid taper; one resolved myocarditis; no deaths. Biodistribution/persistence: AAV9 vector genomes detectable in muscle at 12 weeks at a mean of 2.3 vector genomes per nucleus. Eligibility: no baseline anti-AAV9 neutralizing antibodies (titer <1:400) and no exon-44 deletions. Please pressure-test this package item by item: where would FDA or a skeptical reviewer say the evidence, as presented, fails to support our conclusion, and what additional data, analyses, or design changes would be needed to close