Session Chair Profile
M.D., Ph.D., Director, Institute for Computational Health Sciences, UCSF
Atul Butte, MD, PhD is the new Director of the new Institute of Computational Health Sciences (ICHS) at the University of California, San Francisco, and a Professor of Pediatrics. Dr. Butte trained in Computer Science at Brown University, worked as a software engineer at Apple and Microsoft, received his MD at Brown University, trained in Pediatrics and Pediatric Endocrinology at Children’s Hospital Boston, then received his PhD from Harvard Medical School and MIT. Dr. Butte has authored nearly 200 publications, with research repeatedly featured in Wired Magazine, the New York Times, and the Wall Street Journal. In 2013, Dr. Butte was recognized by the White House as an Open Science Champion of Change for promoting science through publicly available data. Dr. Butte is also a founder of three investor-backed data-driven companies: Personalis, providing clinical interpretation of whole genome sequences, Carmenta (acquired by Progenity), discovering diagnostics for pregnancy complications, and NuMedii, finding new uses for drugs through open molecular data. Dr. Butte is also the principal investigator of ImmPort, the clinical and molecular data repository for the National Institute of Allergy and Infectious Diseases.
Driving Disease Understanding and Treatment via a Centralized Data Warehouse
Aggregating and integrating large amount of data generated at different medical centers will help advance basic disease research and will add to the understanding of effective therapeutic approaches. Building and maintaining a platform and data warehouse that enables researchers to access the data is a prerequisite to advance health care.
Session Abstract – PMWC 2017 Silicon Valley
Many precision medicine initiatives at medical centers, foundations, and providers are aggregating vast amounts of data (e.g. genomics, clinical, and EMR data). Challenges and bottlenecks to overcome are associated with the data generation and aggregation process, and knowledge extraction from multi-modular healthcare data. Representatives from different organizations will discuss specific approaches and learnings.