OpenAI Unveils GPT-Rosalind AI Model for Life Sciences Research
- tech360.tv
- 1 hour ago
- 1 min read
OpenAI on Thursday introduced GPT-Rosalind, an artificial intelligence model designed to enhance biology knowledge and scientific research capabilities. This launch deepens the organisation’s push into the life sciences field.
The GPT-Rosalind model is named after 20th-century British scientist Rosalind Franklin. It aims to support research across biochemistry, drug discovery, and translational medicine.
Demand for AI-powered tools to accelerate drug discovery and research has grown among pharmaceutical companies, academic institutions, and biotech firms.
The model is designed to help researchers accelerate the early stages of discovery, supporting evidence synthesis, hypothesis generation, experimental planning, and other multi-step research tasks.
Researchers using the model will be able to query databases, read the latest scientific papers, use other scientific tools, and suggest new experiments. GPT-Rosalind was built on OpenAI’s newest internal models.
GPT-Rosalind is available as a research preview within ChatGPT, Codex, and the application programming interface for qualified customers. This access is managed through OpenAI’s trusted access deployment structure.
OpenAI is also launching a free Life Sciences research plugin for Codex, which connects scientists to over 50 scientific tools and data sources.
The company is collaborating with customers such as Amgen, Moderna, and Thermo Fisher Scientific, among others, to apply GPT-Rosalind across various workflows.
Separately, OpenAI on Tuesday unveiled GPT-5.4-Cyber, a variant of its latest flagship model. This model is fine-tuned specifically for defensive cybersecurity work, following rival Anthropic’s introduction of its frontier AI model, Mythos.
OpenAI launched GPT-Rosalind, an AI model for life sciences research.
Named after British scientist Rosalind Franklin, it supports biochemistry, drug discovery, and translational medicine.
The model assists researchers with tasks including evidence synthesis, hypothesis generation, and experimental planning.
Source: REUTERS
