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.”
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