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Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model

  • Michael A. LyonsEmail author
  • Anne J. Lenaerts
Original Paper

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.

Keywords

Rifampin PKPD Tuberculosis Mice Immune response Modeling 

Notes

Acknowledgments

The authors wish to thank Scott Irwin and Mary Ann De Groote (Colorado State University (CSU)), Joanne Turner (The Ohio State University), and Radha Shandil (formerly AstraZeneca, Bangalore, India) for helpful discussions. The authors also thank Brad Reisfeld and Raymond Yang (CSU) for a careful review and editing of an earlier version of this manuscript. This work was supported by National Institutes of Health Grant Number K25AI089945.

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© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Microbiology, Immunology and PathologyColorado State UniversityFort CollinsUSA

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