title: Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model.
abstract: One critical approach to preclinical evaluation of anti-tuberculosis (anti-TB) drugs is the study of correlations between drug exposure and efficacy in animal TB infection models. While such pharmacokinetic/pharmacodynamic (PK/PD) studies are useful for the identification of optimal clinical dosing regimens, they are resource intensive and are not routinely performed. A mathematical model capable of simulating the PK/PD properties of drug therapy for experimental TB offers a way to mitigate some of the practical obstacles to determining the PK/PD index that best correlates with efficacy. Here, we present a preliminary physiologically based PK/PD model of rifampin therapy in a mouse TB infection model. The computational framework integrates whole-body rifampin PKs, cell population dynamics for the host immune response to Mycobacterium tuberculosis infection, drug-bacteria interactions, and a Bayesian method for parameter estimation. As an initial application, we calibrated the model to a set of available rifampin PK/PD data and simulated a separate dose fractionation experiment for bacterial killing kinetics in the lungs of TB-infected mice. The simulation results qualitatively agreed with the experimentally observed PK/PD correlations, including the identification of area under the concentration-time curve as best correlating with efficacy. This single-drug framework is aimed toward extension to multiple anti-TB drugs in order to facilitate development of optimal combination regimens.
authors.affiliation: Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA, michael.lyons@colostate.edu.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Lyons
authors.forename: Anne J
authors.initials: AJ
authors.lastname: Lenaerts
mesh_terms: D000818:Animals; D000904:Antibiotics, Antitubercular / Q000008:administration & dosage / Q000493:pharmacokinetics* / Q000627:therapeutic use; D001499:Bayes Theorem; D003198:Computer Simulation; D004195:Disease Models, Animal; D004305:Dose-Response Relationship, Drug; D004353:Drug Evaluation, Preclinical; D051379:Mice; D008954:Models, Biological; D009010:Monte Carlo Method; D009169:Mycobacterium tuberculosis / Q000187:drug effects*; D012293:Rifampin / Q000008:administration & dosage / Q000493:pharmacokinetics* / Q000627:therapeutic use; D014397:Tuberculosis, Pulmonary / Q000188:drug therapy / Q000378:metabolism
chemical_list: D000904:Antibiotics, Antitubercular; D012293:Rifampin