Peer-Reviewed Publication
Cancer Cell2026;44(3):449-454.March 9, 2026Journal Article
The ADAPT learning cancer treatment system: ARPA-H's initiative to revolutionize cancer therapy.
Andrea H Bild1, Michelle C Sangar2, Jasmine A McQuerry2, Trey Ideker3, Scott Kopetz4, Lisa Carey5, Aritro Nath6, Daniel Marcus7, Allison Regier8, Naim Rashid9, Regina Barzilay10, Eric Winer11, Ravi Salgia6, Jyoti Malhotra6, Andrew Gentles12, Kenneth Buetow13, Faisal Mahmood14, David W Markman15, James A Eddy16,
1Advanced Research Projects Agency for Health (ARPA-H), U.S. Department of Health and Human Services, Washington, DC, USA; Department of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA. Electronic address: andrea.bild@arpa-h.gov.
2ECS Federal, LLC, in support of the Advanced Research Projects Agency for Health (ARPA-H), U.S. Department of Health and Human Services, Washington, DC, USA.
3Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
4Department of Gastrointestinal Medical Oncology, Division of Cancer Medicine, MD Anderson Cancer Center, Houston, TX, USA.
5Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
6Department of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA.
7Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.
8DNAnexus, Mountain View, CA, USA.
9Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
10Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Jameel Clinic, Massachusetts Institute of Technology, Cambridge, MA, USA.
11Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA; Yale Cancer Center, Smilow Cancer Hospital, New Haven, CT, USA.
12Department of Pathology, Stanford University, Stanford, CA, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA, USA; Department of Medicine, Stanford University, Palo Alto, CA, USA.
13School of Life Sciences, Arizona State University, Tempe, AZ, USA; Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA; Computational Sciences and Informatics Program for Complex Adaptive Systems, Arizona State University, Tempe, AZ, USA.
14Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
15Markman Group, LLC, in support of the Advanced Research Projects Agency for Health (ARPA-H), U.S. Department of Health and Human Services, Washington, DC, USA.
16Avantiqor, LLC, in support of the Advanced Research Projects Agency for Health (ARPA-H), U.S. Department of Health and Human Services, Washington, DC, USA.
Abstract
ADAPT is a nationwide initiative to transform cancer care by detecting and responding to tumor evolution in real time. Integrating multimodal data, interpretable AI, and an evolutionary clinical trial platform, ADAPT predicts emerging resistance traits and guides treatment adjustments as tumors change. A unified national infrastructure enables continuous learning across patients, linking discovery…
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