MS, LCGC, MBA, Executive VP, GenomeSmart
Biography
Shannon is an innovative and established leader in the field of personal genomics with expertise in oncology and precision medicine. As a board-certified genetic counselor whose career has spanned both clinical and business roles, her work has leveraged both the public’s interest in discovering the “quantified self” and the rapidly evolving companion diagnostics market. Shannon’s research and career focus has been devoted to connecting people with their DNA, and connecting genomic service providers with their end-users. At GenomeSmart, her vision is to make the process of genetic evaluation simple, accessible, and affordable by leveraging AI-powered technologies to make it easier to get the right genetic tests to the right person at the right time. She received her MBA from the Eller College of Management, has served as a consulting founding team member to many startups including Color Genomics and Genome Medical, and has co-founded two companies of her own.
AI and Data Sciences Showcase:
GenomeSmart
GenomeSmart is on a mission to make genetic testing available to everyone. The company launched GenomeBrainTM, the first AI-powered genetic risk assessment and test recommendation platform that matches and identifies people who could benefit from genetic testing.
Make Genetics Part Of Routine Medical Care
Our DNA courses through every part of our body, and every facet of our health. GenomeSmart has developed a formula that brings together genetic labs, providers, patients and medical guidelines to make genetic testing a routine part of everyday care.
Session Abstract – PMWC 2020 Silicon Valley
Track 7 - January 22 9.00 A.M.-3.45 P.M.,Track 6 - January 23 11.15 A.M.-11.30 A.M.,Track 2 - January 24 11.15 A.M.-4.00 P.M.
The PMWC 2020 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.
