OpenAI launches GPT-Rosalind AI model to accelerate drug discovery and life sciences research

OpenAI Takes on Google With New AI Model Aimed at Drug Discovery

OpenAI is rolling out an early version of an artificial intelligence model meant to speed up drug discoveries, joining a field of growing interest for tech companies eager to prove AI can pave the way for more scientific breakthroughs. The ChatGPT maker said Thursday that the model, GPT-Rosalind, is intended for life sciences research, such as helping glean insights from large volumes of data and turning scientific studies into health-care applications for patients. The model will be available initially as a research preview to some of the company's business customers, OpenAI said. The initial users include drugmaker Amgen Inc., vaccine maker Moderna Inc. and the Allen Institute, a bioscience research nonprofit. OpenAI, Anthropic PBC and Alphabet Inc.'s Google have increasingly focused on scientific and health-care applications for AI, ranging from using the technology to help guide research on new drugs to having it review personal medical data. In 2024, two Google DeepMind scientists shared the Nobel Prize in chemistry for AlphaFold, an AI system that predicts protein structures. The technology is generally seen as nascent but promising, and some drugs discovered with the help of AI have been involved in early clinical trials. Get the Tech Newsletter bundle. Get the Tech Newsletter bundle. Get the Tech Newsletter bundle. Bloomberg's subscriber-only tech newsletters, and full access to all the articles they feature. Bloomberg's subscriber-only tech newsletters, and full access to all the articles they feature. Bloomberg's subscriber-only tech newsletters, and full access to all the articles they feature. Plus Signed UpPlus Sign UpPlus Sign Up By continuing, I agree to the Privacy Policy and Terms of Service. Joy Jiao, who leads OpenAI's life science research, said the company hopes the model can act as a research partner for businesses using it, particularly for biology work that is increasingly reliant on computers. Though OpenAI doesn't yet believe AI can be used on its own to come up with new treatments for diseases, "we do think there's a real opportunity to help researchers move faster through some of the most complex and time-intensive parts of the scientific process," she said in a briefing with reporters. Shares of companies involved in drug discovery fell sharply on the news of OpenAI's model. IQVIA Holdings Inc. dropped as much as 3.2% while Charles River Laboratories International Inc. slipped 2.6%. Recursion Pharmaceuticals Inc. and Schrodinger Inc. each fell more than 5%. OpenAI and rival Anthropic have been racing to develop more advanced AI models that can take on a wider range of tasks, including coding, science and cybersecurity, with the hope of convincing more businesses the technology will save time and money. But as their technology has improved in certain areas, most notably software development, there have been renewed concerns about how AI could be misused, including to create biological weapons. Yunyun Wang, OpenAI's life sciences product lead, said that in addition to evaluating whether organizations can safely use its new model, the company includes "high-precision flags" if a user hits certain indicators or thresholds related to bioweapons.

OpenAI launches GPT-Rosalind, an AI model for life sciences research

Named after the crystallographer who helped reveal the structure of DNA, GPT-Rosalind is OpenAI's first domain-specific model series, fine-tuned for biochemistry, genomics, and protein engineering. Access is restricted to a trusted-access programme for vetted enterprise customers including Amgen, Moderna, and Thermo Fisher Scientific. OpenAI has launched GPT-Rosalind, a frontier reasoning model built specifically for life sciences research, the company announced on Thursday. The model is designed to support evidence synthesis, hypothesis generation, experimental planning, and multi-step scientific workflows across biochemistry, genomics, and protein engineering, representing OpenAI's first purpose-built domain-specific model series. It is available as a research preview in ChatGPT, Codex, and the OpenAI API, but access is restricted to a trusted-access programme for qualified enterprise customers in the United States. The model is named after Rosalind Franklin, the British chemist and X-ray crystallographer whose diffraction imaging of DNA was instrumental in revealing the double helix structure, and whose contribution was notably absent from the 1962 Nobel Prize awarded to Watson, Crick, and Wilkins. The naming is a pointed act of recognition: Franklin's work is now widely regarded as foundational to modern molecular biology, and she remains a touchstone in discussions about the erasure of women from scientific history. OpenAI is framing GPT-Rosalind as a tool to compress the timeline from scientific idea to clinical evidence. The company estimates it currently takes roughly 10 to 15 years to move a drug from target discovery to regulatory approval in the United States. GPT-Rosalind is positioned to help at the early stages: it can query specialised databases, parse scientific literature, interact with computational tools, and suggest new experimental pathways within a single interface. Alongside the model itself, OpenAI is also introducing a Life Sciences research plugin for Codex that connects models to more than 50 scientific tools and data sources, giving researchers programmatic access to biological databases and computational pipelines. Launch partners include Amgen, Moderna, Thermo Fisher Scientific, and the Allen Institute. OpenAI is also working with Los Alamos National Laboratory on AI-guided protein and catalyst design. Benchmark performance, as reported by OpenAI, shows GPT-Rosalind achieving a 0.751 pass rate on BixBench, a bioinformatics benchmark developed by Edison Scientific that evaluates models on real-world computational biology tasks. On LABBench2, a broader research task benchmark, the model outperformed GPT-5.4 on six of eleven tasks, with its most significant advantage on CloningQA, a task requiring the end-to-end design of reagents for molecular cloning protocols. The most striking performance signal came from a third-party evaluation conducted with Dyno Therapeutics, a gene therapy company focused on designing AAV capsid proteins. Using unpublished, previously unseen RNA sequences to guard against benchmark contamination, GPT-Rosalind was tested on sequence-to-function prediction and sequence generation tasks. The best-of-ten model submissions ranked above the 95th percentile of human experts on the prediction task and around the 84th percentile on sequence generation, according to OpenAI and confirmed by multiple outlets covering the launch. The launch carries significant dual-use caveats that OpenAI has addressed through its access model. Researchers have warned that AI models trained on biological data could be misused to help design dangerous pathogens.

OpenAI debuts GPT-Rosalind, a new limited access model for life sciences, and broader Codex plugin on Github

The journey from a laboratory hypothesis to a pharmacy shelf is one of the most grueling marathons in modern industry, typically spanning 10 to 15 years and billions of dollars in investment. Progress is often stymied not just by the inherent mysteries of biology, but by the "fragmented and difficult to scale" workflows that force researchers to manually pivot between the actual experimental design equipment, software, and databases. But OpenAI is releasing a new specialized model GPT-Rosalind specifically to speed up this process and make it more efficient, easier, and ideally, more productive. Named after the pioneering chemist Rosalind Franklin, whose work was vital to the discovery of DNA's structure (and was often overlooked for her male colleagues James Watson and Francis Crick), this new frontier reasoning model is purpose-built to act as a specialized intelligence layer for life sciences research. By shifting AI's role from a general-purpose assistant to a domain-specific "reasoning" partner, OpenAI is signaling a long-term commitment to biological and chemical discovery. GPT-Rosalind isn't just about faster text generation; it is designed to synthesize evidence, generate biological hypotheses, and plan experiments -- tasks that have traditionally required years of expert human synthesis. At its core, GPT-Rosalind is the first in a new series of models optimized for scientific workflows. While previous iterations of GPT excelled at general language tasks, this model is fine-tuned for deeper understanding across genomics, protein engineering, and chemistry. To validate its capabilities, OpenAI tested the model against several industry benchmarks. On BixBench, a metric for real-world bioinformatics and data analysis, GPT-Rosalind achieved leading performance among models with published scores. In more granular testing via LABBench2, the model outperformed GPT-5.4 on six out of eleven tasks, with the most significant gains appearing in CloningQA -- a task requiring the end-to-end design of reagents for molecular cloning protocols. The model's most striking performance signal came from a partnership with Dyno Therapeutics. In an evaluation using unpublished, "uncontaminated" RNA sequences, GPT-Rosalind was tasked with sequence-to-function prediction and generation. When evaluated directly in the Codex environment, the model's submissions ranked above the 95th percentile of human experts on prediction tasks and reached the 84th percentile for sequence generation. This level of expertise suggests the model can serve as a high-level collaborator capable of identifying "expert-relevant patterns" that generalist models often overlook. OpenAI is not just releasing a model; it is launching an ecosystem designed to integrate with the tools scientists already use. Central to this is a new Life Sciences research plugin for Codex, available on GitHub. Scientific research is famously siloed. A single project might require a researcher to consult a protein structure database, search through 20 years of clinical literature, and then use a separate tool for sequence manipulation. The new plugin acts as an "orchestration layer," providing a unified starting point for these multi-step questions. Given the potential power of a model capable of redesigning biological structures, OpenAI is eschewing a broad "open-source" or general public release in favor of a Trusted Access program. The model is launching as a research preview specifically for qualified Enterprise customers in the United States. This restricted deployment is built on three core principles: beneficial use, strong governance, and controlled access. Organizations requesting access must undergo a qualification and safety review to ensure they are conducting legitimate research with a clear public benefit. Unlike general-use models, GPT-Rosalind was developed with heightened enterprise-grade security controls. For the end-user, this means: The announcement garnered significant buy-in from OpenAI parnters across the pharmaceutical and technology sectors. Sean Bruich, SVP of AI and Data at Amgen, noted that the collaboration allows the company to apply advanced tools in ways that could "accelerate how we deliver medicines to patients".The impact is also being felt in the specialized tech infrastructure that supports labs: This builds on tangible results OpenAI has already seen in the field, such as its collaboration with Ginkgo Bioworks, where AI models helped achieve a 40% reduction in protein production costs. OpenAI's mission with GPT-Rosalind is to narrow the gap between a "promising scientific idea" and the actual "evidence, experiments, and decisions" required for medical progress. By partnering with institutions like Los Alamos National Laboratory to explore AI-guided catalyst design and biological structure modification, the company is positioning GPT-Rosalind as more than a tool -- it is meant to be a "capable partner in discovery". As the life sciences field becomes increasingly data-dense, the move toward specialized "reasoning" models like Rosalind may become the standard for navigating the "vast search spaces" of biology and chemistry.

OpenAI launches new AI model for life sciences research

Why it matters: Biology research is increasingly computational, but scientists are drowning in data across fields like genomics, protein analysis and biochemistry. By the numbers: Right now it takes roughly 10 to 15 years to go from target discovery to regulatory approval for new drugs in the U.S., according to OpenAI. * Only one in 10 drugs entering clinical trials ultimately gets approved. * More than 30 million Americans and 300 million people globally living with rare diseases are waiting for better treatments. The big picture: OpenAI designed the first Life Sciences model -- GPT-Rosalind -- to be better at fundamental reasoning in fields like biochemistry and genomics, Joy Jiao, OpenAI's life sciences research lead, told a group of reporters on Wednesday. * The company says the models won't replace scientists, but rather help them move faster through some of the most time-intensive and analytically demanding work of the scientific process. * While there's an industry-wide effort to reduce AI hallucinations overall, OpenAI stresses that these new models are designed to synthesize evidence, generate hypotheses, and support analysis -- not replace expert judgment or real-world validation. * Humans, they say, still belong in the loop. Fun fact: OpenAI named the model after British chemist Rosalind Franklin, whose research helped reveal the structure of DNA and laid the foundation for modern molecular biology. Zoom in: The company launched the frontier reasoning model to accelerate research, drug discovery and translational medicine, which basically means turning scientific discoveries into better health outcomes. * The model includes "enterprise-grade security controls" and access management, suitable for highly-regulated scientific environments, per OpenAI. * The company already partners with Los Alamos National Laboratory on AI-guided protein and catalyst design. Yes, but: Only a few AI-discovered or AI-designed drugs have reached clinical trials. * No fully AI-discovered or AI-designed drug has made it through phase 3 trials. The other side: The rollout comes as researchers warn that AI models trained on biological data could be misused to help design dangerous pathogens. * An international group of more than 100 scientists have called for tighter controls on sensitive biological data used to train AI systems, Axios reported earlier this year. Between the lines: OpenAI is launching the models in research preview to select enterprise customers through a "trusted access program." * It will reserve access for organizations working on improving human health outcomes, conducting legitimate life sciences research, and maintaining strong security and governance controls. * It will be available Thursday for what OpenAI calls "qualified customers," including Amgen, Moderna, the Allen Institute, and Thermo Fisher Scientific. * The goal of limiting the program is to maximize use while mitigating the potential for misuse, Yunyun Wang, OpenAI's life sciences product lead, said. What we're watching: Domain-specific models might be AI's next big phase.

OpenAI to rival Google's AlphaFold with new AI model for life sciences research

The model is the first release in OpenAI's Life Science model series. OpenAI has announced plans to roll out an early version of GPT-Rosalind, its AI reasoning model designed to support research across biology, drug discovery, and translational medicine. In a statement on Thursday (16 April), OpenAI explained, on average, it can take up 15 years to move from target discovery to regulatory approval for a new drug in the US, with progress impacted by the difficulty of the underlying science, as well as the complexity of the research workflow. The organisation said, "Scientists must work across large volumes of literature, specialised databases, experimental data, and evolving hypotheses in order to generate and evaluate new ideas. These workflows are often time-intensive, fragmented and difficult to scale." Named after Rosalind Franklin, a pioneering figure in the field of DNA, GPT‑Rosalind is now available as a research preview in ChatGPT, Codex and the API for qualified customers through OpenAI's access programme, for example to companies such as Amgen, Moderna, the Allen Institute, Thermo and Fisher Scientific. GPT-Rosalind is the latest in a series of life sciences applications launched by an AI-focused platform, with the space becoming increasingly competitive. Last year France's Sorbonne University and Qubit Pharmaceuticals, announced the "world's most powerful" AI model for molecular simulation in pharmaceutical chemistry, FeNNix-Biol. At the time, the research team claimed that FeNNix-Biol's capabilities are beyond that of Google DeepMind's AlphaFold, the Nobel Prize-winning deep-learning machine designed to transform our understanding of the molecular biology that underpins health and disease. OpenAI said, "This is the first release in our Life Sciences model series and we view it as the beginning of a long-term commitment to building AI that can accelerate scientific discovery in areas that matter deeply to society, from human health to broader biological research. "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." Don't miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic's digest of need-to-know sci-tech news.

OpenAI Targets Pharma Giants With Purpose-Built AI Model | PYMNTS.com

The new GPT-Rosalind features improved tool use and a deeper understanding of chemistry, protein engineering and genomics, the company said in a Thursday (April 16) press release. With this new AI model, OpenAI aims to help scientists overcome the current constraints of complex research workflows and reduce the time it takes to move a new drug from target discovery to regulatory approval, which is currently 10 to 15 years, according to the release. "We believe advanced AI systems can help researchers move through these workflows faster -- not just by making existing work more efficient, but by helping scientists explore more possibilities, surface connections that might otherwise be missed, and arrive at better hypotheses sooner," the company said in the release. OpenAI is offering GPT-Rosalind as a research preview in ChatGPT, Codex and the API for qualified customers through the company's trusted access program. It also introduced a Life Sciences research plugin for Codex that is freely accessible and helps scientists connect models to more than 50 scientific tools and data sources. The company is working with customers such as Amgen, Moderna, the Allen Institute, Thermo Fisher Scientific and others to apply GPT-Rosalind in research and discovery, per the release. Sean Bruich, senior vice president of artificial intelligence and data at Amgen, said in the release: "Our unique collaboration with OpenAI enables us to apply their most advanced capabilities and tools in new and innovative ways with the potential to accelerate how we deliver medicines to patients." The PYMNTS Intelligence report "Generative AI Can Elevate Health and Revolutionize Healthcare" found that generative AI innovations expand researchers' capabilities, accelerating drug discovery and diagnostics. It was reported in February that pharmaceutical companies are reshaping their operating models around AI to speed clinical trials and regulatory submissions. In addition, AI is reshaping drug discovery, clinical strategy and manufacturing optimization.

OpenAI's GPT-Rosalind AI Model Promises Faster Drug Breakthroughs and Smarter Experiments

As complexity increases in drug discovery, genomics, and molecular biology, there is a growing need for systems that can precisely handle large scientific data sets. The GPT-Rosalind artificial intelligence model performs three functions: analysis of scientific literature, hypothesis generation, and experimental design. This machine can process massive volumes of and datasets, recognize patterns, and summarize its findings within minutes. Scientists may employ this technology to formulate new research objectives or to improve their current objectives. Designing the experiments is another of its main features.

OpenAI launches AI model GPT-Rosalind for life sciences research

OpenAI on Thursday introduced an artificial intelligence model touting increased biology knowledge and scientific research capabilities, as the startup deepens its push into the life sciences field. The GPT-Rosalind, named after 20th-century British scientist Rosalind Franklin, is designed to support research across biochemistry, drug discovery and translational medicine. Demand for AI-powered tools to accelerate drug discovery and research has risen across pharmaceutical companies, academic institutions and biotech firms. "By supporting ⁠evidence synthesis, hypothesis generation, experimental planning, and other multi-step research tasks, this model is designed to help researchers accelerate the early stages of discovery," OpenAI said in a blog. Researchers using ⁠the model will be able to query databases, read the latest scientific papers, use other scientific tools and suggest new experiments, OpenAI ⁠said in a press briefing. The model was built on top of OpenAI's newest internal models. GPT-Rosalind is available as a research preview in ChatGPT, Codex, and the API for qualified customers through OpenAI's trusted access deployment structure. ⁠The company ⁠is also launching a free Life Sciences research plugin for Codex, connecting scientists to over 50 ⁠scientific tools and data sources. The company said it is working with customers like Amgen, Moderna, Thermo Fisher Scientific and others to apply GPT-Rosalind across workflows. OpenAI, creator of ⁠popular chatbot ChatGPT, on Tuesday unveiled GPT-5.4-Cyber, a variant of its latest flagship model fine-tuned specifically for defensive cybersecurity work, following rival Anthropic's announcement of frontier AI model Mythos.

OpenAI introduces GPT Rosalind for scientific research: What it can do

The model is named after Rosalind Franklin, whose work played a key role in discovering the structure of DNA. OpenAI has introduced a new AI model called GPT-Rosalind, designed to support research across biology, drug discovery and translational medicine. The company says that the new model is built to support complex scientific workflows and can help researchers move faster during the early stages of scientific discovery. Developing a new medicine is a long and complicated process. On average, it can take 10 to 15 years for a potential drug to move from early discovery to final regulatory approval in the US. 'By supporting evidence synthesis, hypothesis generation, experimental planning, and other multi-step research tasks, this model is designed to help researchers accelerate the early stages of discovery. Over time, these systems could help life sciences organisations discover breakthroughs that wouldn't otherwise be possible, with a much higher rate of success,' OpenAI explains. The model is currently available as a research preview in ChatGPT, Codex, and through the API for selected organisations through a trusted access program. Also read: OpenAI upgrades Codex with computer control, image generation to rival Claude Code OpenAI describes GPT-Rosalind as a new 'purpose-built model to accelerate scientific research and drug discovery.' The model is named after Rosalind Franklin, whose work played a key role in discovering the structure of DNA and helped shape modern molecular biology. OpenAI says GPT-Rosalind is the first model in a new life sciences AI series. GPT-Rosalind is said to deliver the best performance on tasks that need reasoning over molecules, proteins, genes, pathways and disease-relevant biology. It can also help with tasks like reviewing scientific literature, planning experiments and data analysis. Also read: Is AI replacing jobs or creating them? Here is what LinkedIn data says OpenAI has also introduced a Life Sciences research plugin for Codex that connects the model to more than 50 scientific tools, databases and research sources. The plugin is available on GitHub. 'We will continue improving the model's biological reasoning, expanding support for tool-heavy and long-horizon research workflows, and working closely with leading scientific institutions to evaluate real-world impact,' the company said.