Project Grant R01HL174679

This $813,042 federal Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) aims to develop an integrative causal machine learning platform to predict and mitigate hematologic adverse events in patients with myeloid malignancies. The award supports research to: (I) identify key predictors of thrombosis, (II) quantify bleeding risk, and (III) personalize treatment protocols to minimize thrombotic and hemorrhagic complications. This innovative approach departs from conventional methods by linking causal inference techniques with machine learning algorithms. The project will validate the data-driven models through external evaluation. Harvard Medical School is the prime awardee, with sub-awards to Brigham & Women's Hospital, Dana-Farber Cancer Institute, and Harvard Pilgrim Health Care Institute to provide clinical expertise, data integration, and pharmacoepidemiological analysis. The award period is from July 1, 2024 to June 30, 2027.