Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model
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| 024 | 7 | 0 | |a 10.1007/s10928-015-9419-z |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s10928-015-9419-z | ||
| 245 | 0 | 0 | |a Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model |h [Elektronische Daten] |c [Michael Lyons, Anne Lenaerts] |
| 520 | 3 | |a 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. | |
| 540 | |a Springer Science+Business Media New York, 2015 | ||
| 690 | 7 | |a Rifampin |2 nationallicence | |
| 690 | 7 | |a PKPD |2 nationallicence | |
| 690 | 7 | |a Tuberculosis |2 nationallicence | |
| 690 | 7 | |a Mice |2 nationallicence | |
| 690 | 7 | |a Immune response |2 nationallicence | |
| 690 | 7 | |a Modeling |2 nationallicence | |
| 700 | 1 | |a Lyons |D Michael |u Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA |4 aut | |
| 700 | 1 | |a Lenaerts |D Anne |u Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA |4 aut | |
| 773 | 0 | |t Journal of Pharmacokinetics and Pharmacodynamics |d Springer US; http://www.springer-ny.com |g 42/4(2015-08-01), 375-389 |x 1567-567X |q 42:4<375 |1 2015 |2 42 |o 10928 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10928-015-9419-z |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s10928-015-9419-z |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Lyons |D Michael |u Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Lenaerts |D Anne |u Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Journal of Pharmacokinetics and Pharmacodynamics |d Springer US; http://www.springer-ny.com |g 42/4(2015-08-01), 375-389 |x 1567-567X |q 42:4<375 |1 2015 |2 42 |o 10928 | ||