Brian Athey has more than 25 years of experience in trans-disciplinary team science-based leadership experience as overall Principal Investigator of national biomedical informatics and computational sciences centers and consortia. These include the National Library of Medicine (NLM) Visible Human Project, the DARPA Telepathology and Virtual Solider Projects, the NIH National Center for Integrative Biomedical Informatics (NCIBI), the CTSA Biomedical Informatics Key Function Committee, and the tranSMART Foundation. Brian has trained over 10 PhD students and has over 100 peer-reviewed papers and conference proceedings. He is currently an active researcher in 2 new fields of pharmacogenomics that are fundamentally extending its scope and potential impact: ‘pharmacoepigenomics’ and ‘pharmacophenomics’. Brian has done extensive consulting for DARPA and the NIH Office of the Director. He is an elected fellow of the American College of Medical Informatics (FACMI) and of the American Association of the Advancement of Sciences (AAAS).
AI and Data Sciences Showcase:
Phenomics Health Inc.
Phenomics Health is a bioinformatics-based platform precision medicine company commercializing AI and machine learning-enabled genetic, epigenetic, multi-omics and health big data into novel pharmacological clinical decision support products and disease-drug response network services.
Resolving Previously Unrecognized Drug Mechanisms Of Action
Phenomics platform supports products and services based on non-coding variants of the human genome consisting of spatial, temporal, and mechanical regulatory mechanisms of gene regulation, transforming our understanding of regulatory genomics, transcriptional hierarchy, and nuclear structural dynamics.
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.