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

Overview of attention for article published in Journal of Pharmacokinetics and Pharmacodynamics, May 2015
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About this Attention Score

  • Among the highest-scoring outputs from this source (#21 of 149)
  • Good Attention Score compared to outputs of the same age (73rd percentile)

Mentioned by

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5 tweeters

Citations

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6 Dimensions

Readers on

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26 Mendeley
Title
Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model
Published in
Journal of Pharmacokinetics and Pharmacodynamics, May 2015
DOI 10.1007/s10928-015-9419-z
Pubmed ID
Authors

Michael A. Lyons, Anne J. Lenaerts

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.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 54%
Student > Master 4 15%
Researcher 3 12%
Student > Doctoral Student 3 12%
Student > Postgraduate 1 4%
Other 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 27%
Unspecified 3 12%
Pharmacology, Toxicology and Pharmaceutical Science 3 12%
Medicine and Dentistry 3 12%
Immunology and Microbiology 3 12%
Other 7 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 June 2015.
All research outputs
#3,079,120
of 12,323,473 outputs
Outputs from Journal of Pharmacokinetics and Pharmacodynamics
#21
of 149 outputs
Outputs of similar age
#62,696
of 239,045 outputs
Outputs of similar age from Journal of Pharmacokinetics and Pharmacodynamics
#2
of 4 outputs
Altmetric has tracked 12,323,473 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 149 research outputs from this source. They receive a mean Attention Score of 2.0. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 239,045 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.