ArticleThe Journal of antimicrobial chemotherapy2016
A multistate tuberculosis pharmacometric model: a framework for studying anti-tubercular drug effects in vitro.
Article in The Journal of antimicrobial chemotherapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Drug Effect of Clofazimine on Persisters Explains an Unexpected Increase in Bacterial Load in Patients.Antimicrobial agents and chemotherapy · 2020Trial
- Characterization of spectinamide 1599 efficacy against different mycobacterial phenotypes.Tuberculosis (Edinburgh, Scotland) · 2023Article
- Article
- Standards for model-based early bactericidal activity analysis and sample size determination in tuberculosis drug development.Frontiers in pharmacology · 2023Article
- Combined quantitative tuberculosis biomarker model for time-to-positivity and colony forming unit to support tuberculosis drug development.Frontiers in pharmacology · 2023Article
- Bacterial growth dynamics and pharmacokinetic-pharmacodynamic relationships of rifampicin and bedaquiline in BALB/c mice.British journal of pharmacology · 2022Article
- Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation ofFrontiers in pharmacology · 2022Review
- Model-Based Exposure-Response Assessment for Spectinamide 1810 in a Mouse Model of Tuberculosis.Antimicrobial agents and chemotherapy · 2021Article
- Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis.Annual review of pharmacology and toxicology · 2021Review
- Anti-tuberculosis effect of isoniazid scales accurately from zebrafish to humans.British journal of pharmacology · 2020Article
- Quantification of Natural Growth of Two Strains of Mycobacterium Marinum for Translational Antituberculosis Drug Development.Clinical and translational science · 2020Article
- A model-based analysis identifies differences in phenotypic resistance between in vitro and in vivo: implications for translational medicine within tuberculosis.Journal of pharmacokinetics and pharmacodynamics · 2020Article
- Longitudinal Pharmacokinetic-Pharmacodynamic Biomarkers Correlate With Treatment Outcome in Drug-Sensitive Pulmonary Tuberculosis: A Population Pharmacokinetic-Pharmacodynamic Analysis.Open forum infectious diseases · 2020Article
- Advanced Quantification Methods To Improve the 18b Dormancy Model for Assessing the Activity of Tuberculosis DrugsAntimicrobial agents and chemotherapy · 2020Article
- Review
- Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?The Journal of antimicrobial chemotherapy · 2019Article
- Re-growth ofAntimicrobial agents and chemotherapy · 2019Article
- Quantitative assessment of the activity of antituberculosis drugs and regimens.Expert review of anti-infective therapy · 2019Review
- Forecasting Clinical Dose-Response From Preclinical Studies in Tuberculosis Research: Translational Predictions With Rifampicin.Clinical pharmacology and therapeutics · 2018Article
- A quantitative systems pharmacology (QSP) model for Pneumocystis treatment in mice.BMC systems biology · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesMycobacterium tuberculosis can exist in different states in vitro, which can be denoted as fast multiplying, slow multiplying and non-multiplying. Characterizing the natural growth of M. tuberculosis could provide a framework for accurate characterization of drug effects on the different bacterial states.
methodsThe natural growth data of M. tuberculosis H37Rv used in this study consisted of viability defined as cfu versus time based on data from an in vitro hypoxia system. External validation of the natural growth model was conducted using data representing the rate of incorporation of radiolabelled methionine into proteins by the bacteria. Rifampicin time-kill curves from log-phase (0.25-16 mg/L) and stationary-phase (0.5-64 mg/L) cultures were used to assess the model's ability to describe drug effects by evaluating different linear and non-linear exposure-response relationships.
resultsThe final pharmacometric model consisted of a three-compartment differential equation system representing fast-, slow- and non-multiplying bacteria. Model predictions correlated well with the external data (R(2) = 0.98). The rifampicin effects on log-phase and stationary-phase cultures were separately and simultaneously described by including the drug effect on the different bacterial states. The predicted reduction in log10 cfu after 14 days and at 0.5 mg/L was 2.2 and 0.8 in the log-phase and stationary-phase systems, respectively.
conclusionsThe model provides predictions of the change in bacterial numbers for the different bacterial states with and without drug effect and could thus be used as a framework for studying anti-tubercular drug effects in vitro.
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