People, companies, institutions and technologies working on artificial intelligence in cancer care. 30 records carry it: 18 companies, 7 people, 4 institutions, 1 technology.
Related tags
30 records
| Cancers | Other tags | ||||
|---|---|---|---|---|---|
Aignostics Berlin, DE Aignostics is the Berlin pathology AI company that built the Atlas foundation model with Mayo Clinic. | none | none | none | ||
Arc Institute Palo Alto, CA, US The Arc Institute is a well-funded nonprofit research institute building 'virtual cell' AI models and the datasets to train them. | none | none | virtual-cell | ||
Bioptimus Paris, FR French startup behind H-optimus-0, an open 1.1-billion-parameter pathology foundation model. | none | none | none | ||
Chai Discovery San Francisco, CA, US Makes Chai-1 and Chai-2, open-weight structure models used for antibody and binder design. | none | none | protein-design | ||
Chan Zuckerberg Initiative (Biohub) Redwood City, CA, US Funds and builds the Human Cell Atlas infrastructure and the CZI virtual cell models (TranscriptFormer), plus one of the largest nonprofit GPU clusters for biology. | none | none | virtual-cell | ||
Chemistry42 and Pharma.AI (Insilico) Generative chemistry platform behind the first AI-discovered drug to reach phase 2, plus oncology candidates. | none | chemistry | |||
Constance D. Lehman Professor of Radiology, Harvard Medical School; Co-Director, Breast Imaging Research Center, Massachusetts General Hospital · Massachusetts General Hospital Cancer Center Breast radiologist who co-developed the Mirai AI model that predicts breast cancer risk from a mammogram. | HR-positive / HER2-negative breast cancer | none | screening, breast | ||
Cradle Amsterdam / Zurich, NL Cradle is a protein-engineering AI platform used by pharma to optimise antibodies and enzymes. | none | none | protein-design | ||
Daniel E. Spratt Chair of Radiation Oncology, University Hospitals Seidman Cancer Center and Case Western Reserve University · Case Comprehensive Cancer Center Radiation oncologist who built AI models from trial slides to decide which prostate cancer patients need hormone therapy. | Prostate cancer | none | prostate, radiotherapy | ||
EvolutionaryScale New York, NY, US Spun out of Meta's protein team; makes the ESM3 protein language model that generated a new fluorescent protein. | none | none | protein-design | ||
Faisal Mahmood Associate Professor of Pathology, Harvard Medical School and Brigham and Women's Hospital; Associate Member, Broad Institute · Broad Institute of MIT and Harvard Built UNI and CONCH, the pathology foundation models that let AI read whole-slide images across cancer types. | none | none | pathology, foundation-models | ||
Genesis Molecular AI (formerly Genesis Therapeutics) Burlingame, CA, US Genesis Molecular AI does small-molecule discovery on its GEMS platform, which combines physics and deep learning, with oncology programmes in the clinic pipeline. | none | none | none | ||
Google DeepMind (and Google Research) London / Mountain View, GB · GOOGL Google DeepMind built AlphaFold, AlphaMissense, AlphaGenome and Med-Gemini, the reference models for structure, variants, and medical multimodal reasoning. | none | none | none | ||
HistAI Miami, FL, US HistAI, of Miami, released Hibou-B and Hibou-L in 2024, open vision transformer models for pathology trained on more than a million slides and published under the Apache 2.0 licence, which allows commercial use. Whether permissively licensed open models reach regulated clinical products or stay research tools is the open question. | none | none | none | ||
Iambic Therapeutics San Diego, CA, US AI-discovered oncology molecules in the clinic, including a HER2 inhibitor and a CDK2/4 inhibitor. | none | none | none | ||
Institute for Protein Design (University of Washington) University of Washington · Seattle, US David Baker's institute, where de novo protein design and the RFdiffusion models come from (Nobel Prize in Chemistry 2024). | none | none | protein-design | ||
Jakob Nikolas Kather Professor of Clinical Artificial Intelligence, Else Kröner Fresenius Center for Digital Health, TU Dresden; Medical Oncologist, NCT Dresden · NCT/UCC Dresden, University Hospital Carl Gustav Carus Showed that deep learning can read genetic features like microsatellite instability directly from routine pathology slides. | Colorectal cancer, Gastric & gastro-oesophageal junction cancer | none | pathology, biomarkers, germany | ||
kaiko.ai Amsterdam / Zurich, NL Dutch-Swiss company releasing open pathology foundation models (Midnight) and evaluation tooling (eva). | none | none | none | ||
Kristina Lång Associate Professor of Diagnostic Radiology, Lund University; Breast Radiologist, Skåne University Hospital · Skåne University Hospital / Lund University Cancer Centre Led MASAI, the first randomised trial of AI-supported mammography screening, which found more cancers with half the radiologist workload. | HR-positive / HER2-negative breast cancer | none | screening, breast, sweden | ||
Latent Labs London, GB Founded by an AlphaFold co-developer to make protein design programmable; released Latent-X in 2025. | none | none | protein-design | ||
Lila Sciences Cambridge, MA, US Lila Sciences is Flagship Pioneering's 'scientific superintelligence' company, combining AI with autonomous labs, with life science as a first domain. | none | none | none | ||
Microsoft (Research and Health AI) Redmond, WA, US · MSFT Microsoft co-developed Prov-GigaPath and BiomedCLIP and is the compute partner for Paige's Virchow2. | none | none | none | ||
NVIDIA Santa Clara, CA, US · NVDA Supplies the GPUs and the BioNeMo framework most biological foundation models are trained on, and co-developed Evo 2 with Arc. | none | none | infrastructure | ||
Profluent Berkeley, CA, US Profluent uses protein language models to design new gene editors (OpenCRISPR-1) and antibodies. | none | none | protein-design | ||
Providence Health & Services Renton, WA, US Providence is a 51-hospital US health system whose 1.3 billion pathology tiles trained Prov-GigaPath with Microsoft. | none | none | none | ||
Regina Barzilay School of Engineering Distinguished Professor for AI and Health, MIT; AI Faculty Lead, Jameel Clinic · David H. Koch Institute for Integrative Cancer Research at MIT Computer scientist who built Mirai and Sybil, AI models that predict breast and lung cancer risk years before diagnosis. | HR-positive / HER2-negative breast cancer, Non-small-cell lung cancer | none | risk-prediction, screening | ||
Thomas J. Fuchs Dean of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai; Co-founder, Paige · The Mount Sinai Hospital / Tisch Cancer Institute Trained the first clinical-grade AI on tens of thousands of slides, leading to the first FDA-authorised AI pathology product. | Prostate cancer | none | pathology, digital-pathology | ||
Vevo Therapeutics San Francisco, CA, US Produced Tahoe-100M, the largest single-cell drug-perturbation atlas, and trains models on it. | none | none | virtual-cell | ||
Xaira Therapeutics South San Francisco, CA, US Launched in 2024 with over $1 billion to build AI-native drug discovery from Baker-lab protein design. | none | none | none | ||
Yale School of Medicine / Yale Cancer Center Yale University · New Haven, CT, US Home of the Cell2Sentence single-cell language models built with Google, and an NCI-designated comprehensive cancer centre. | none | none | virtual-cell |

















