Speaker Profile

Ph.D., Senior Vice President, DPU Head, ln Silico Discovery, GSK Pharmaceuticals

John Baldoni heads a newly formed drug discovery unit dedicated to explore and apply in silico methodology to drug discovery and development at GSK. This new appointment follows his role as Senior Vice President, Platform Technology and Science (PTS), GSK Pharma R&D. Baldoni joined GSK in 1989 and has worked in the pharmaceutical industry for 37 years. His experience spans new chemical entity design, development and commercialization, and biopharmaceutical development. In progressing to his current role, Baldoni has held various positions at GSK including Senior Vice President, Preclinical Development; Vice President, Product Development; Director, Product Development; and Assistant Director, Biopharmaceutical Formulation Development, among others. He has led several key cross-functional problem solving and strategic initiatives. Baldoni has a BS in biochemistry (1974), and MS and Ph.D. degrees in chemistry (1980) from Penn State University.

Session Abstract – PMWC 2018 Silicon Valley

Session Synopsis: In order to facilitate the identification of targets or to provide individualized patient care, the ultimate practice of precision medicine, optimal use of the wide variety of translational data collected on patients is of critical importance. Yet, it is difficult to identify biomarkers with traditional methods given the much larger number of variables measured, compared to the number of patients enrolled in a clinical trial. As a result, very few organizations are leveraging all their data assets to identify what treatments work best for individual patients in an unbiased manner. As the data collected in clinical trials and during a patients’ life journey increases exponentially, this session aims to showcase how machine learning is a critical component to making personalized medicine a reality at the example of predictive biomarker identification, the development of holistic solutions for patients with complex diseases and its potential to impact value based pricing strategies.

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