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
CONCLUSIONS: Genomic and clinical risk factors for CAD display time-varying importance across the lifespan. The study underscores the added value of CAD PRS, particularly among individuals younger than 55 years, for enhancing early risk prediction and prevention strategies. All results are available at https://surbut.github.io/dynamicHRpaper/index.html.
Journal article
The 12-lead electrocardiogram (ECG) is inexpensive and widely available. Whether conditions across the human disease landscape can be detected using the ECG is unclear. We developed a deep learning denoising autoencoder and systematically evaluated associations between ECG encodings and ~1,600 Phecode-based diseases in three datasets separate from model development, and meta-analyzed the results. The latent space ECG model identified associations with 645 prevalent and 606 incident Phecodes....