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The multistate tuberculosis pharmacometric model: a semi-mechanistic pharmacokinetic-pharmacodynamic model for studying drug effects in an acute tuberculosis mouse model

Overview of attention for article published in Journal of Pharmacokinetics and Pharmacodynamics, February 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Citations

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28 Mendeley
Title
The multistate tuberculosis pharmacometric model: a semi-mechanistic pharmacokinetic-pharmacodynamic model for studying drug effects in an acute tuberculosis mouse model
Published in
Journal of Pharmacokinetics and Pharmacodynamics, February 2017
DOI 10.1007/s10928-017-9508-2
Pubmed ID
Authors

Chunli Chen, Fatima Ortega, Joaquin Rullas, Laura Alameda, Iñigo Angulo-Barturen, Santiago Ferrer, Ulrika SH Simonsson

Abstract

The Multistate Tuberculosis Pharmacometric (MTP) model, a pharmacokinetic-pharmacodynamic disease model, has been used to describe the effects of rifampicin on Mycobacterium tuberculosis (M. tuberculosis) in vitro. The aim of this work was to investigate if the MTP model could be used to describe the rifampicin treatment response in an acute tuberculosis mouse model. Sixty C57BL/6 mice were intratracheally infected with M. tuberculosis H37Rv strain on Day 0. Fifteen mice received no treatment and were sacrificed on Days 1, 9 and 18 (5 each day). Twenty-five mice received oral rifampicin (1, 3, 9, 26 or 98 mg·kg(-1)·day(-1); Days 1-8; 5 each dose level) and were sacrificed on Day 9. Twenty mice received oral rifampicin (30 mg·kg(-1)·day(-1); up to 8 days) and were sacrificed on Days 2, 3, 4 and 9 (5 each day). The MTP model was linked to a rifampicin population pharmacokinetic model to describe the change in colony forming units (CFU) in the lungs over time. The transfer rates between the different bacterial states were fixed to estimates from in vitro data. The MTP model described well the change in CFU over time after different exposure levels of rifampicin in an acute tuberculosis mouse model. Rifampicin significantly inhibited the growth of fast-multiplying bacteria and stimulated the death of fast- and slow-multiplying bacteria. The data did not support an effect of rifampicin on non-multiplying bacteria possibly due to the short duration of the study. The pharmacometric modelling framework using the MTP model can be used to perform investigations and predictions of the efficacy of anti-tubercular drugs against different bacterial states.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 36%
Researcher 5 18%
Other 3 11%
Student > Postgraduate 3 11%
Student > Master 2 7%
Other 3 11%
Unknown 2 7%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 9 32%
Medicine and Dentistry 8 29%
Chemistry 2 7%
Agricultural and Biological Sciences 2 7%
Mathematics 1 4%
Other 2 7%
Unknown 4 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 24 March 2017.
All research outputs
#7,850,834
of 25,382,440 outputs
Outputs from Journal of Pharmacokinetics and Pharmacodynamics
#117
of 477 outputs
Outputs of similar age
#145,291
of 448,866 outputs
Outputs of similar age from Journal of Pharmacokinetics and Pharmacodynamics
#2
of 9 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 477 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 75% 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 448,866 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 67% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.