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OpenAI Has a New AI Model Built for Biology and Science
OpenAI's latest AI model is built to do far more than offer cooking advice or create a spreadsheet. GPT-Rosalind, the company's first model specifically built for life science, is meant to help scientists with drug discovery, biology and translational medicine. The model is named after Rosalind Franklin, whose research revealed the structure of DNA and formed the foundations for modern molecular biology. Scientific research relies heavily on data, and GPT-Rosalind is designed to help sort through it, while also helping reduce the time it takes to develop and get new drugs approved and out on the market. (Disclosure: Ziff Davis, CNET's parent company, in 2025 filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.) It can take 10 to 15 years for a new drug to be developed and approved in the US, OpenAI said in a blog post Thursday. GPT-Rosalind is intended to improve the selection of research targets and create stronger hypotheses for higher-quality experiments. The model has been tested on topics such as its understanding of organic chemistry, proteins and genetics. Researchers can use it to find relevant scientific literature for their work or design experiments. This isn't the first time an AI model has been developed with medical advancements in mind. Google DeepMind has developed many AI models for scientific research, such as AlphaFold, which earned its creators a share of the 2024 Nobel Prize in Chemistry. "For me, the best use case for AI was to improve human health and accelerate scientific discovery," Google DeepMind CEO Demis Hassabis said in a recent interview. Anthropic introduced Claude for Life Sciences in January with the same purpose. Some scientists have expressed concerns in the past about how quickly AI has infiltrated the science space and have warned of vulnerabilities, potential misuse and issues with data representation. OpenAI said GPT-Rosalind has safeguards to protect it from misuse -- like the creation of a biological weapon -- and has teamed up with various biotechnology, pharmaceutical and life sciences technology organizations to support research and scientific discovery. Sean Bruich, senior vice president of artificial intelligence and data at the biopharmaceutical company Amgen, said in a statement that scientific work requires precision: "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."
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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.
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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.
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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.
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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.
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OpenAI launches GPT-Rosalind AI model for drug discovery
OpenAI has introduced GPT-Rosalind, a new reasoning model built for biology, drug discovery, and translational medicine research. Qualified enterprise customers in the U.S. can now try it out as a research preview. Researchers can use the model to handle complex, multi-step scientific tasks. These range from gathering existing evidence and forming new hypotheses to planning experiments. OpenAI said it is working with customers such as Amgen $AMGN, Moderna $MRNA, the Allen Institute, and Thermo Fisher $TMO Scientific to apply the model in discovery workflows. Qualified customers in OpenAI's trusted access program can use the model through ChatGPT, Codex, or the API. OpenAI is also releasing a free Life Sciences research plugin for Codex, which gives scientists access to over 50 data sources and scientific tools. During the research preview, using the model will not use up existing credits or tokens, as long as users follow abuse guardrails, according to OpenAI. The model is named after Rosalind Franklin, the British scientist whose work helped uncover the structure of DNA. Joy Jiao, OpenAI's life sciences research lead, said the company does not yet believe AI can create new disease treatments on its own. However, she told reporters, "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," according to Bloomberg. OpenAI said that on the BixBench benchmark, which tests real-world bioinformatics and data analysis tasks, GPT-Rosalind earned the highest score among models with published results. In another evaluation with gene therapy company Dyno Therapeutics, the model's best ten submissions ranked above the 95th percentile of human experts on an RNA sequence prediction task. OpenAI said that only organizations conducting legitimate scientific research with clear public benefits can access the model. The company has controls for eligibility, access, and governance. According to Bloomberg, Wang said the system watches for signs of bioweapons concerns and triggers what the company calls "high-precision flags" if certain thresholds are reached. After the news about the model, shares of several drug discovery companies dropped. Recursion Pharmaceuticals and Schrodinger each lost more than 5% of their value, IQVIA $IQV Holdings fell by up to 3.2%, and Charles River Laboratories dropped by 2.6%. AI-powered drug discovery is attracting more investment from pharmaceutical companies, academic institutions, and biotech startups. Precedence Research estimates that the drug industry's investment in AI will reach $2.51 billion in 2026 and $16.49 billion by 2034. OpenAI's move into the life sciences model market comes as competition grows. Google $GOOGL DeepMind's AlphaFold protein-structure prediction system earned its creators a share of the 2024 Nobel Prize in Chemistry, and Anthropic has also expanded its AI tools for science and health care. OpenAI noted that drug development in the U.S. usually takes about 10 to 15 years from target discovery to regulatory approval. The company argues that using AI early in the process could lead to better target selection and higher-quality experiments later on.
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OpenAI's New AI Model Rosalind Could Shave Years Off Drug Discovery. You Probably Can't Use It - Decrypt
Access is tightly restricted amid rising biosecurity concerns. OpenAI just named its first domain-specific AI model after Rosalind Franklin -- the British chemist whose X-ray crystallography work helped reveal DNA's double helix, and who was famously denied credit for it during her lifetime. GPT-Rosalind, unveiled Thursday, is a purpose-built reasoning model for biology, drug discovery, and translational medicine. It's the first in what OpenAI is calling a Life Sciences model series -- a direct play for a market where many specialized labs from universities to Google DeepMind are all jostling for position. Getting a drug from target discovery to regulatory approval in the U.S. takes 10 to 15 years on average according to experts.. Most of that time disappears not in eureka moments, but in the grind: parsing thousands of papers, querying databases, designing reagents, and interpreting ambiguous results. This is what GPT-Rosaling is trying to tackle. OpenAI argues the model can compress that early-stage work. As the company put it, GPT-Rosalind is designed to help scientists "explore more possibilities, surface connections that might otherwise be missed, and arrive at better hypotheses sooner." The benchmarks back up at least some of that ambition. On BixBench -- a benchmark built around real-world bioinformatics tasks -- GPT-Rosalind logged a 0.751 pass rate, the top score among models with published results. On LABBench2, it outperformed its predecessor GPT-5.4 on six out of eleven tasks. GPT-Rosalind Beats GPT 5.4 in every single case involving life science, but it's a highly specific model that will underperform in anything other than that. OpenAI also announced Dyno Therapeutics will help test and evaluate its model based on unpublished RNA sequences to rule out memorization. GPT-Rosalind's best-of-ten submissions ranked above the 95th percentile of human experts on sequence prediction tasks, and around the 84th percentile on generation. That said, OpenAI's own life sciences research lead Joy Jiao was measured about what the model can actually do. She explained the company doesn't see Rosalind as a model capable of creating new treatments autonomously, but told reporters that it could be a great help in speeding research up. "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," Jiao said in a press briefing, according to the LA Times. The ecosystem around the model may matter as much as the model itself. OpenAI is also releasing a free Life Sciences research plugin for Codex connecting to over 50 scientific databases and tools -- protein structure lookups, sequence search, literature review, genomics pipelines. Enterprise users with GPT-Rosalind access get the reasoning layer on top. Everyone else gets the plugin with standard models. OpenAI has lined up a roster of pharma and biotech customers for the launch, including Amgen, Moderna, and Thermo Fisher Scientific. Separately, it's running a research collaboration with Los Alamos National Laboratory on AI-guided protein and catalyst design. "The life sciences field demands precision at every step. The questions are highly complex, the data are highly unique, and the stakes are incredibly high," said Sean Bruich, Amgen's Senior VP of AI and Data in the official announcement. Access to Rosalind is deliberately restricted. The model is U.S. enterprise only, gated behind a qualification and safety review. The concern isn't abstract: an international coalition of over 100 scientists has already called for tighter controls on biological data used to train AI, citing pathogen design risks. OpenAI's restricted rollout is a direct response. During the research preview, usage won't consume existing API credits. This also isn't OpenAI's first move into science workflows. The Prism scientific writing workspace launched in January was a first step. GPT-Rosalind is the sharper, more specialized follow-up -- and a signal that domain-specific models are becoming a serious competitive front. No fully AI-discovered drug has cleared phase 3 trials. That number is still zero. But if GPT-Rosalind helps a researcher design a better experiment six months faster across thousands of labs, then the compounding effect on what gets discovered, and when, could be the whole ballgame. That's the actual thesis here, and it's worth watching closely.
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OpenAI launches life science AI model. Here's everything to know
The GPT-Rosalind model is designed to accelerate biological research and drug discovery. OpenAI has launched a new artificial intelligence model designed to support research across biology, drug discovery, and translational medicine. The new tool, called GPT-Rosalind, is named after Rosalind Franklin, a British scientist best known for her role in the discovery of the structure of DNA. The GPT‑Rosalind life sciences model series is built for modern scientific work across published evidence, data, tools, and experiments, the company announced on Friday. OpenAI is increasingly turning its attention to health and medical research, developing new large language models and partnering with international pharmaceutical companies. It is a field that artificial intelligence is already transforming, helping researchers and drugmakers identify promising compounds faster, and speeding up the pipeline from research to clinical use. Progress in the life sciences is constrained not only by the difficulty of the science but by the complexity of the research workflows themselves, OpenAI said. "We believe that 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 wrote. OpenAI said the model delivers the best performance on tasks that require reasoning over molecules, proteins, genes, pathways, and disease-relevant biology. The company stated it is also more effective at using scientific tools and databases in multi-step workflows such as literature review, sequence-to-function interpretation, experimental planning, and data analysis. Following this first release of GPT‑Rosalind life sciences model series, OpenAI said it will continue to expand the model's biochemical reasoning capabilities across long-horizon, tool-heavy scientific workflows. "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," they wrote in the announcement. OpenAI said it is working with biotechnology and pharmaceutical companies, and research centres such as Amgen, Moderna, the Allen Institute, and Thermo Fisher Scientific to apply GPT‑Rosalind across workflows that accelerate research and discovery. "GPT-Rosalind represents an important step in helping scientific teams use advanced AI to reason across complex biological evidence, data, and workflows," said Stéphane Bancel, Chief Executive Officer at Moderna. "At Moderna, we are already seeing how it can synthesise complex data and translate those insights into experimental workflows, with the potential to accelerate the pace of R&D," he added. On 14 April, OpenAI announced a partnership with the Danish pharmaceutical company Novo Nordisk to "help the company bring new and better treatment options to patients faster". "AI is reshaping industries, and in life sciences, it can help people live better, longer lives," said OpenAI's CEO Sam Altman. The pilot programmes will launch across research and development (R&D), manufacturing, and commercial operations, aiming for full integration by the end of the year.
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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.
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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.
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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.
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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.
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OpenAI launches GPT-Rosalind to accelerate life sciences research
Conceived as an advanced assistance tool, GPT-Rosalind enables the synthesis of scientific data, the generation of hypotheses, and the planning of experiments. It aims to meet the needs of pharmaceutical laboratories, academic institutions, and biotechnology firms by facilitating the analysis of recent publications and the exploration of new research avenues. The model is part of a broader strategy to optimize the initial processes of scientific work, where artificial intelligence can significantly accelerate innovation cycles. Access remains controlled, with a preliminary version deployed via ChatGPT, Codex, and the API, reserved for qualified users. OpenAI is also offering a free plugin for Codex, allowing connection to more than 50 specialized tools and databases. The company is already collaborating with major industry players such as Amgen, Moderna, and Thermo Fisher Scientific to integrate the model into real-world research environments. This initiative follows a broader strategy of model specialization, coming on the heels of the recent launch of GPT-5.4-Cyber dedicated to cybersecurity. Facing increased competition, notably from Anthropic, OpenAI seeks to establish itself in high-value-added segments where artificial intelligence could profoundly transform research methodologies and accelerate scientific breakthroughs.
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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.
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OpenAI released GPT-Rosalind, its first domain-specific AI model built for life sciences research. Named after DNA pioneer Rosalind Franklin, the model aims to compress the 10-to-15-year drug development timeline by helping scientists synthesize evidence and generate biological hypotheses. Access is restricted through a trusted access program to enterprise partners including Amgen, Moderna, and Thermo Fisher Scientific.
OpenAI has released GPT-Rosalind, marking the company's first venture into domain-specific artificial intelligence with an AI model for life sciences designed explicitly for drug discovery and biological research
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. Named after Rosalind Franklin, the British chemist whose crystallography work revealed the DNA double helix structure, this frontier reasoning model represents a shift from general-purpose assistants to specialized scientific partners3
. The model is fine-tuned for biochemistry, genomics, and protein engineering, addressing a critical bottleneck in modern pharmaceutical development2
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Source: Analytics Insight
The timing matters. Right now, it takes roughly 10 to 15 years to move a drug from target discovery to regulatory approval in the United States, with only one in 10 drugs entering clinical trials ultimately receiving approval
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. More than 30 million Americans and 300 million people globally living with rare diseases are waiting for better treatments5
. GPT-Rosalind aims to accelerate scientific discovery by helping researchers navigate the fragmented workflows that force them to manually pivot between experimental design equipment, software, and databases4
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Source: Silicon Republic
Unlike typical AI releases, OpenAI is launching GPT-Rosalind through a trusted access program that restricts availability to qualified enterprise customers in the United States
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. Initial partners include pharmaceutical giants Amgen and Moderna, along with Thermo Fisher Scientific and the Allen Institute2
. Organizations requesting access must undergo qualification and safety reviews to ensure they conduct legitimate research with clear public benefit and maintain strong governance controls4
.This controlled deployment addresses growing concerns about potential misuse. An international group of more than 100 scientists have called for tighter controls on sensitive biological data used to train AI systems, warning that models trained on biological data could be misused to help design dangerous pathogens
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. Yunyun Wang, OpenAI's life sciences product lead, confirmed the model includes enterprise-grade security controls and "high-precision flags" if users hit certain indicators or thresholds related to bioweapons2
.Benchmark testing reveals GPT-Rosalind's capabilities extend beyond general language tasks. On BixBench, a bioinformatics benchmark evaluating real-world computational biology tasks, the model achieved a 0.751 pass rate
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. On LABBench2, GPT-Rosalind outperformed GPT-5.4 on six of eleven tasks, with its most significant advantage on CloningQA, a task requiring end-to-end design of reagents for molecular cloning protocols3
.The most striking validation came from Dyno Therapeutics, a gene therapy company. Using unpublished RNA sequences to guard against benchmark contamination, GPT-Rosalind ranked above the 95th percentile of human experts on sequence-to-function prediction tasks and around the 84th percentile on sequence generation
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. This suggests the model can identify expert-relevant patterns that generalist models often overlook4
.OpenAI enters a competitive field where Google, Anthropic, and other tech companies are racing to prove AI can deliver scientific breakthroughs. Google DeepMind's AlphaFold, which predicts protein structures, earned its creators a share of the 2024 Nobel Prize in Chemistry
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. Anthropic introduced Claude for Life Sciences in January with similar goals for translational medicine1
.The announcement triggered immediate market reactions. Shares of companies involved in drug discovery fell sharply, with IQVIA Holdings dropping as much as 3.2%, Charles River Laboratories slipping 2.6%, and Recursion Pharmaceuticals and Schrodinger each falling more than 5%
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. The market response signals investor concern about potential disruption to traditional research workflows.Related Stories
Alongside GPT-Rosalind, OpenAI introduced a Life Sciences research plugin for Codex available on GitHub, connecting models to more than 50 scientific tools and data sources
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. This orchestration layer addresses a fundamental challenge in scientific research: projects often require consulting protein structure databases, searching through decades of clinical literature, and using separate tools for sequence manipulation4
. The plugin provides a unified starting point for multi-step questions, allowing researchers to query specialized databases, parse scientific literature, and interact with computational tools within a single interface1
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Source: Axios
Joy Jiao, who leads OpenAI's life sciences research, emphasized the model is designed to synthesize evidence, generate biological hypotheses, and plan experiments—tasks that traditionally require years of expert synthesis
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. Sean Bruich, senior vice president of AI and data at Amgen, noted that scientific work requires precision, and the collaboration enables the company to apply advanced capabilities in ways that could "accelerate how we deliver medicines to patients"1
. OpenAI is also partnering with Los Alamos National Laboratory on AI-guided protein and catalyst design .While promising, no fully AI-discovered or AI-designed drug has completed phase 3 clinical trials
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. Only a few AI-discovered drugs have reached early clinical trials, making this technology nascent but potentially transformative2
. OpenAI stresses these models are designed to support analysis, not replace expert judgment or real-world validation—humans still belong in the loop5
. Domain-specific models like GPT-Rosalind might represent AI's next phase, signaling a shift from general-purpose tools to specialized reasoning partners that compress the timeline from scientific idea to clinical evidence4
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