Brian Schmidt
About Brian Schmidt
Brian Schmidt is the Executive Director, Head of Quantitative Systems Pharmacology & Physiologically Based Pharmacokinetics at Bristol Myers Squibb, with extensive experience in computational biology and systems biology research.
Title
Brian Schmidt is the Executive Director, Head of Quantitative Systems Pharmacology & Physiologically Based Pharmacokinetics at Bristol Myers Squibb.
Company
Brian Schmidt currently works at Bristol Myers Squibb, a global biopharmaceutical company. In his role as Executive Director, he leads the Quantitative Systems Pharmacology & Physiologically Based Pharmacokinetics division.
Work Experience at Bristol Myers Squibb
Brian Schmidt has a long-standing career at Bristol Myers Squibb, starting in 2014 as a Senior Research Investigator in Quantitative Systems Pharmacology. Over the years, he advanced to various positions including Associate Director, Senior Principal Scientist, Director, Research Fellow, and Senior Director before becoming the Executive Director. Throughout these roles, he has managed technical capability functions and multiple teams to inform pharmaceutical research and clinical development.
Previous Experience
Prior to his tenure at Bristol Myers Squibb, Brian Schmidt worked at several research institutes and companies. He was a Postdoctoral Associate in Computational Biology at Sanford-Burnham Medical Research Institute and a Postdoctoral Scholar in Systems Biology at UC San Diego. He also held a position as Dynamics Engineer at Entelos and served as a Postdoctoral Research Associate in Systems Biology at the University of Virginia. Furthermore, he has industry experience as a Quality Engineer at Whatman HemaSure and as an Engineering Co-Op at Bayer.
Education
Brian Schmidt earned his PhD in Biomedical Engineering from the University of Virginia, where he studied from 2003 to 2009. He also has a BS in Chemical Engineering from the University of Pittsburgh, completed between 1997 and 2001.
Research and Expertise
Brian Schmidt has extensive experience in developing and applying computational approaches to calibrate mechanistic population models with multiple datasets. His research focuses on better understanding biological systems and the role of biomarkers. He develops predictions of efficacy for new therapies through computational biology research and has a strong background in systems and computational biology.