More than 80% of cancer patients who undergo immune checkpoint inhibitor (ICI) therapy experience immune related adverse events, including autoimmunity, following treatment. The overarching goal of this proposal is to test the feasibility and effectiveness of using a physician-validated cohort of cancer patients combined with data from electronic health records (EHRs), and with machine learning strategies as a platform for understanding the mechanisms of human autoimmune disease. The developed model could significantly accelerate precision medicine approaches for employing ICI therapy that minimize the potential autoimmune disease based on personal genetic, environmental and social information.
|Effective start/end date||9/17/19 → 8/31/20|
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (1R61AR076824-01)