Chief Data Officer and Institute Scientist
Co-Director, Eric and Wendy Schmidt Center
Broad Institute of MIT and Harvard
Anthony Philippakis is the chief data officer of the Broad
Institute of MIT and Harvard, and the co-director of the Eric and Wendy Schmidt Center.
He trained as a cardiologist at Brigham and Women’s Hospital, with
a focus on rare genetic cardiovascular diseases. At the Broad Institute he is
the founding director of the Data Sciences Platform, an organization of over
200 software engineers and computational biologists that develops software for
analyzing genomic and clinical data. In addition to his roles at the Broad
Institute and Brigham and Women’s Hospital, Philippakis is a venture partner at
GV, focusing on machine learning, distributed computing, and genomics.
Philippakis received his M.D. from Harvard Medical School and
completed a Ph.D. in biophysics at Harvard. As an undergraduate, he studied
mathematics at Yale University, and later completed the Part III (equivalent to
M.Phil.) in mathematics at Cambridge University.
Chief Data Officer and Institute Scientist
Co-Director, Eric and Wendy Schmidt Center
Broad Institute of MIT and Harvard
Anthony Philippakis is the chief data officer of the Broad
Institute of MIT and Harvard, and the co-director of the Eric and Wendy Schmidt Center.
He trained as a cardiologist at Brigham and Women’s Hospital, with
a focus on rare genetic cardiovascular diseases. At the Broad Institute he is
the founding director of the Data Sciences Platform, an organization of over
200 software engineers and computational biologists that develops software for
analyzing genomic and clinical data. In addition to his roles at the Broad
Institute and Brigham and Women’s Hospital, Philippakis is a venture partner at
GV, focusing on machine learning, distributed computing, and genomics.
Philippakis received his M.D. from Harvard Medical School and
completed a Ph.D. in biophysics at Harvard. As an undergraduate, he studied
mathematics at Yale University, and later completed the Part III (equivalent to
M.Phil.) in mathematics at Cambridge University.
Journal article
No abstract
Journal article
Randomized controlled trials (RCTs) remain the gold standard for evaluating medical interventions, yet ethical, practical and financial constraints often necessitate reliance on observational data and trial emulations. This study explores how integrating genetic data can enhance both emulated and traditional trial designs. Using FinnGen (n = 425,483), we emulated four major cardiometabolic RCTs and showed how reduced differences in polygenic scores (PGS) between trial arms track improvement in...