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
Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an...
Journal article
CONCLUSION: Our NLP model developed within a single healthcare system accurately identified HF events relative to the gold-standard CEC in an external multi-center clinical trial. Fine-tuning the model improved agreement and approximated human reproducibility. NLP may improve the efficiency of future multi-center clinical trials by accurately identifying clinical events at scale.
