Thursday, November 21, 2024
11/21/2024
Abstract This program seeks firstly to provide increased understanding of pharmacokinetics (PK) and mechanisms of corticosteroid (CS) effects on genomic, proteomic, and physiologic processes associated with endocrine, metabolic, and pharmacologic responses from local to systems levels for CS dosed acutely and chronically. Secondly, the mechanisms of action and interaction of multiple agents offering potential joint therapy of pancreatic cancer will be examined. Thirdly, these specific study results will be integrated with relevant information from the literature to develop improved mechanism-based PK and pharmacodynamic (PK/PD) models and methods spanning and offering insights at basic, complex, and systems pharmacologic levels. Overall, our goals are development of mechanistic pharmacologic and disease models that reveal and interrelate the `rules of biology and pharmacology' at various levels of biological organization and allow improved quantitation and prediction of in vivo hormone and drug effects. The cancer drug studies utilize cell cultures, proteomics, and network analyses with an emphasis on seeking natural synergy of multiple agents and evolving new methods for quantitating drug interactions. Our experimental paradigm for CS studies has been large carefully controlled studies in groups of animals subjected to defined conditions or drug treatments (“giant rat” studies). Blood and major organs will be harvested from male and female rats over timeframes reflecting either endogenous biorhythms or the onset and recovery of changes produced by single drug doses or prolonged disturbances of homeostasis produced by disease and chronic drug exposures. We examine involvement of short rhythms (circadian) within longer biorhythms (estrous cycle, seasons), assess sex differences in disease processes and steroid actions particularly in rheumatoid arthritis, and evolve and apply physiologically relevant basic PK/PD to extensive systems pharmacologic approaches. Our methods and interdisciplinary collaborations include extensive laboratory-based experiments, state-of-the-art bioanalysis methods, generation of “big data” sets of –omics response data, various computational platforms, expert knowledge about diverse biological processes, and offer the imagination and insights to recognize new principles that emerge and underlie the complexities of how drugs, hormones, and natural compounds work and interact in the body. These efforts encompass and enrich both basic PK/PD and systems modeling, but with emphasis on enhanced physiological models that attend complex mechanisms of drug action. These holistic studies and mathematical modeling innovations will provide improved multi-scale understanding of critical biological, hormone, and pharmacologic functions and will continue to offer wide applications in quantitative pharmacology.
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