Matt Might (University of Utah) – An Algorithm for Precision Medicine

Computer Science speaker series: Matt Might (University of Utah) – “An Algorithm for Precision Medicine.” This talk paints a cautionary yet optimistic portrait of what full-scale precision medicine will entail.

Event date: Thursday, November 19, 2015, at 11:03 AM
Location: BA1170
Speaker: Matt Might
Associate Professor, Department of Computer Science
University of Utah

Title: An algorithm for precision medicine

Abstract:
President Obama recently launched the Precision Medicine Initiative, a confluence of efforts in data science, bioinformatics, systems biology and genomics. Precision medicine’s promise of “the right medicine to the right patient at the right time” is predicated on the assumption that a patient’s health data may be mapped directly to the “right medicine.” It is reasonable to assume that such a mapping exists (in theory), but it is not yet clear how complex the implementation of that mapping will become. With the claim that genomic data will be a key driver in precision medicine, rare genetic disorders offer a window into the genome-guided aspects of precision medicine. This talk paint a cautionary yet optimistic portrait of what full-scale precision medicine will entail, illustrated by the speaker’s first-hand experience with aftermath of the discovery that his son was the first known patient of a novel and ultra-rare genetic disorder — NGLY1 deficiency.

Biography:
Professor Matt Might’s interests focus on making software faster, safer and more secure. He is an expert in automated, semantics-driven analysis of modern software systems and complex formal models. Currently Might is a visiting Associate Professor in Biomedical Informatics at the Harvard Medical School. His interests there include Internet-driven case-finding for rare disease; systematizing delivery of care in genomic medicine; systems pharmacology; and in silico drug discovery. He has been actively engaged with White House and NIH leadership on the Precision Medicine Initiative, serving as an ardent advocate for translational science in precision medicine.

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