Anthropic has announced two major life sciences partnerships with the Allen Institute and the Howard Hughes Medical Institute (HHMI), aiming to accelerate biological discovery by embedding its AI system, Claude, directly into the scientific research process.

Modern biological research is producing data at an unprecedented scale, from single-cell sequencing to whole-brain connectomics, yet converting that data into validated insights remains a major challenge. Anthropic said the new collaborations are designed to address this bottleneck by supporting knowledge synthesis, hypothesis generation and experimental interpretation through AI systems that work alongside scientists.

The Allen Institute and HHMI will serve as founding life sciences partners, extending Claude’s capabilities into frontier scientific research. The partnerships combine Anthropic’s work in foundation models, agentic AI systems and interpretability with world-class research institutions focused on complex biological and biomedical questions.

At HHMI, the collaboration will operate under the Institute’s AI@HHMI initiative and will be anchored at the Janelia Research Campus. The focus will be on building infrastructure for AI-enabled discovery and developing specialised AI agents that integrate experimental knowledge with advanced scientific instruments and analysis pipelines. Anthropic and HHMI will also work closely on the deployment and continued development of AI models so that tools evolve in response to real laboratory needs.

The Allen Institute partnership will centre on developing multi-agent AI systems capable of analysing and integrating multimodal biological data. These systems will coordinate specialised agents for tasks such as multi-omics integration, knowledge graph management, temporal modelling, and experimental design, with the goal of compressing months of manual analysis into significantly shorter timeframes.

Both collaborations emphasise transparency and scientific rigour, with Anthropic positioning Claude as a tool that augments rather than replaces human judgment. By enabling researchers to trace and evaluate AI-generated reasoning, the partners aim to ensure that insights remain evidence-based and usable across the broader scientific community.