Launched TxAgent evaluation portal, our global evaluation of AI for drug decision-making and therapeutic reasoning. Participate in TxAgent evaluations! [TxAgent project]

New preprint on SPATIA: a multimodal model for pediction and generation of spatial cell phenotypes.

New piece in Nature Medicine on AI-enabled drug discovery reaching a clinical milestone.

New preprint on biologically inspired architecture for knowledge tracing. The study on the use of generative AI in education with prospective evaluation of knowledge tracing in the classroom.

New paper in npj Digital Medicine: Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases.

New preprint: One patient, many contexts: Scaling medical AI through contextual intelligence

ToolUniverse now offers access to over 211 cutting-edge biological and medical tools, all integrated with Model Context Protocol (MCP). Any “AI Scientist” agent can tap into these tools for biomedical research. [Tutorial] [ToolUniverse] [TxAgent]

In press at Nature Biomedical Engineering: PDGrapher AI predicts chemicals to reverse disease phenotypic effects — with applications to drug target identification.

New preprint: Decision transformers for generating reach-avoid policies in sequential decision making — with applications from robotics to cell reprogramming.

New preprint introducing COMPASS: A generalizable AI that predicts immunotherapy outcomes across cancers and treatments. [Project website] [Code]

Check out the Kempner Deeper Learning posts describing our latest ATOMICA and TxAgent AI models.

New preprint introducing ATOMICA, a universal model of intermolecular interactions across proteins, small molecules, ions, peptides, RNA, and DNA. [Kempner Institute]

Read about AI in medicine in the latest Harvard Gazette and New York Times.

TxAgent is an AI agent for therapeutic reasoning that consolidates 211 tools from trusted sources, including all US FDA-approved drugs since 1939 and validated clinical insights. [Project website] [TxAgent] [ToolUniverse]

New paper: Multimodal AI approach for designing combination therapies with improved predictive accuracy and clinical relevance. [Project website]

KGARevion is an AI agent designed for complex biomedical QA that integrates the non-codified knowledge of LLMs with the structured, codified knowledge found in knowledge graphs. [ICLR 2025 publication]

Meet MedTok, a multimodal medical code tokenizer that transforms how AI understands structured medical data. By integrating textual descriptions and relational contexts, MedTok enhances tokenization for transformer-based models—powering everything from EHR foundation models to medical QA. [Project website]

What if we could anticipate molecular and medical changes before they happen? Introducing CLEF, an approach for counterfactual generation in biological and medical sequence models. [Project website]

New paper on the role of digital twins as global health and disease learning models for preventive and personalized medicine.

New papers on test-time interventions in language models and knowledge graph based LLM agents accepted to ICLR. [KGARevion]