When: Mar 4, 2025 2:00PM CETRegister here “Causal Models to Support Better Decisions in Drug Development: PBPK and QSP” Models used for decisions-making in pharmaceutical development have been limited by a bias towards small, statistically feasible models applied to small (e.g. a single trial) datasets. This approach ignores petabytes of relevant biological and physiological data. Additionally, statistical inferences can only be derived for the population tested. Over the past twenty years or so, causal (mechanistic) models have been increasingly applied to leverage these data to support better decisions, especially where predictions must be made of experiments and trials not yet done. In this talk from Jim Bosley, PhD, we cover a brief history of the field and will use Physiologicaly Based PharmacoKinetic (PBPK) and Quantitative Systems Pharmacology (QSP) examples to illustrate why such models support better and more effective drug development decisions. About the Speaker Jim Bosley, PhD Jim has spent over 20 years advancing systems biology modeling and advocating its adoption in pharmaceutical research. Prior to joining Nova In Silico he founded and ran a systems biology modeling consulting company, Clermont, Bosley LLC, serving major pharma/biotech. Prior to this, Jim started the modeling practice at Rosa & Co. building the group from one to ten principals, with the title of Vice President of Modeling and Simulation. We was Sr. Director of Software Products for Pharsight (now a Certara company), as a Consulting Engineer for Entelos and as a Senior Engineer in DuPont’s BioChemical Science and Engineering group. He has written several articles
