Lab profile
About Zitnik Lab (Artificial Intelligence for Science and Medicine)
The lab establishes foundations of AI for science through systems that generate biological insight and accelerate discovery, design, and development of treatments for pressing medical challenges. They develop multimodal, generative, and agentic AI models that reason across molecular, cellular, tissue, and patient scales, including autonomous AI scientists that integrate research and clinical data with scientific tools to generate hypotheses, prioritize experiments, and produce scientific insight.
01 · Research focus
Research areas and highlights
Topics and recent work as stated on the lab’s own site.
- Open AI Scientists InitiativeDevelops and studies autonomous AI systems that reason, hypothesize, and experiment alongside human researchers, integrating research and clinical data with scientific tools.
- ToolUniverseAn open platform enabling AI agents to use scientific tools and databases at scale for building AI scientists.
- MedeaAn AI agent that nominates therapeutic targets across cell type contexts, predicts synthetic lethality in cancer cell lines, and forecasts immunotherapy response from multimodal patient profiles.
- ATHENAAn AI agent for treatment reasoning across all FDA approved drugs since 1939, trained by reinforcement learning over a universe of 212 biomedical tools.
- COMPASSA pan-cancer foundation model that predicts immunotherapy response from tumor microenvironments and highlights the biology driving that response.
- AutoScientistsSelf-organizing agent teams for long-running scientific experimentation.
- OptimusKGA modern multimodal knowledge graph that supports graph AI, knowledge-grounded retrieval with large language models, and discovery workflows that generate and evaluate biomedical hypotheses.
- MedLogAn open protocol for event-level logging of medical AI, validated across four real-world pilots in the US, Switzerland, and Vietnam to enable auditing, monitoring, and governance of AI systems.
- Therapeutics Data Commons (TDC)An initiative to access and evaluate AI capability across therapeutic modalities and stages of discovery, establishing a foundation for understanding which AI methods are most suitable for advancing therapeutic science.
- CUREBenchInternational competition in therapeutic reasoning for AI-driven drug discovery.
02 · People
Leadership and researchers
People listed on the lab’s team pages, by role.
03 · Research intelligence
Research Intelligence evidence
Publications, grants and clinical trials linked to the lab’s researchers in Health AI Central’s research data.
Publications & preprints
- GPC: An expressive and tractable deep generative model for genetic variation data.PLoS genetics · 2026
- World models for biomedicine.Cell · 2026
- Reflecting on 25 years of cancer research: transformative advances and unmet expectations.Nature reviews. Cancer · 2026
04 · Updates
Updates and lab news
News and events from the lab’s own site.
- AutoScientistsPublication
- Biological Reasoning ModelsPublication
- MedLogPublication
- ATHENA Agent for Treatment ReasoningPublication
- Immune Checkpoint Inhibitors in Nature MedicinePublication
- An AI agent for therapeutic reasoning across biological contextsPublication
- Verification in the Age of AI ScientistsEvent
- Do LLMs know when they have enough information to answer?Publication
05 · Official presence
Lab sources and channels
The lab’s own pages and accounts.
06 · Related
Related labs and centers
Labs at the same institution and labs working on similar topics.