Upcoming webinar: Expanding from Basic Towards Systems Pharmacodynamic Models for Methylprednisolone

Expanding from Basic Towards Systems Pharmacodynamic Models for Methylprednisolone Vivaswath S. Ayyar, Ph.D., Research Assistant Professor of Pharmaceutical Sciences, University at Buffalo, NY and PK/PD Scientist, Janssen BioTherapeutics, Spring House, PA Thursday May 23, 2019, 12:00 to 1:00 pm EDT Register at https://register.gotowebinar.com/register/2512261322183894796?source=website Abstract: Evolving upon foundational principles of classical pharmacology mostly applied to static systems, a diversity of basic pharmacokinetic/pharmacodynamic (PK/PD) models have emerged. Placing emphasis on parsimony, the basic "mechanism-based" models incorporate and relate plasma pharmacokinetics, receptor binding, and/or relevant homeostatic mechanisms controlling drug response. Continued refinement of PK/PD models based upon a progressively deeper mechanistic appreciation of physiologically-based PK, pharmacology of drug-target interactions, and systems physiology from the molecular (genomic, proteomic, metabolomic) to cellular to whole body scales have laid the foundation for building mechanistic quantitative systems pharmacology (QSP) models. Previous research based on various animal, clinical, and theoretical studies with corticosteroids have provided ideas to broadly advance the fields of pharmacokinetics and pharmacodynamics. Our recent work on modeling diverse aspects of corticosteroid systems pharmacology reflect the integration of basic pharmacodynamic models along with the assimilation of fundamental insights gained from many focused studies of corticosteroids. These models highlight the application of combined systems (experimental and modeling) approaches to decipher "horizontal" and "vertical" pharmacokinetic/ pharmacodynamic/ pharmacogenomic (PK/PD/PG) relationships of the synthetic corticosteroid, methylprednisolone, in relation to 1) circadian gene expression and inter-tissue responses, 2) biological signaling networks, and 3) sex differences, using systems pharmacology approaches supported with data from microarray and proteomics analysis, systemic physiological measurements, and/or more focused quantitation of mechanistic biomarker(s). The modeling strategies employed, major findings, and lessons learned from these studies are described.