General-Purpose

Biomni is a general-purpose biomedical AI agent designed to autonomously execute a wide spectrum of research tasks across diverse biomedical subfields. It employs an action discovery agent to mine tools, databases, and protocols from tens of thousands of publications across 25 biomedical domains, creating the first unified agentic environment (Biomni-E1). Its generalist agentic architecture (Biomni-A1) integrates LLM reasoning with retrieval-augmented planning and code-based execution, dynamically composing complex workflows without predefined templates. Systematic benchmarking demonstrates strong zero-shot generalization across heterogeneous tasks including causal gene prioritization, drug repurposing, rare disease diagnosis, microbiome analysis, and molecular cloning.

Biomedical research underpins progress in our understanding of human health and disease, drug discovery, and clinical care. However, with the growth of complex lab experiments, large datasets, many analytical tools, and expansive literature, biomedical research is increasingly constrained by repetitive and fragmented workflows that slow discovery and limit innovation. Here, we introduce Biomni, a general-purpose biomedical AI agent designed to autonomously execute a wide spectrum of research tasks across diverse biomedical subfields. To systematically map the biomedical action space, Biomni first employs an action discovery agent to create the first unified agentic environment, mining essential tools, databases, and protocols from tens of thousands of publications across 25 biomedical domains. Built on this foundation, Biomni features a generalist agentic architecture that integrates LLM reasoning with retrieval-augmented planning and code-based execution, enabling it to dynamically compose and carry out complex biomedical workflows entirely without relying on predefined templates or rigid task flows. Systematic benchmarking demonstrates that Biomni achieves strong generalization across heterogeneous biomedical tasks including causal gene prioritization, drug repurposing, rare disease diagnosis, microbiome analysis, and molecular cloning without any task-specific prompt tuning. Real-world case studies further showcase Biomni's ability to interpret complex, multi-modal biomedical datasets and autonomously generate experimentally testable protocols.