Mechanism-Based PKPD Models for Rifampicin Evaluation

This research paper demonstrates role of QSP modeling efforts in Rifampicin development program via empirical pharmaceutical research, which were selected to cover a wide range of mathematical modeling methods including agent-based modeling, partial differential equation modeling, and ordinary differential equation modeling. Other applications of systems modeling include evaluation of new target pathways; optimization of compound physicochemical properties; characterization of efficacy and toxicity mechanisms of action; recommendation of treatment posology of monotherapies and combination therapies by balancing efficacy and toxicity; and guidance of study subject stratification strategies based on clinical responder features. Particularly, quantitative systems modeling plays a critical role in predicting clinical hematological toxicity risks by translating preclinical data obtained from micro-physiological systems (MPS). The analysis of Rifampicin as personalized medicine in MPS data is routinely performed to simulate clinical outcomes under various dosage regimens.