ArticleAntimicrobial agents and chemotherapy2016
A Physiologically Based Pharmacokinetic Model of Isoniazid and Its Application in Individualizing Tuberculosis Chemotherapy.
Article in Antimicrobial agents and chemotherapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05124678 (A Phase II Trial to Describe the Pharmacokinetics, Safety and Efficacy of Pharmacogenetics-guided Dosing of Isoniazid in Patients With HIV-associated TB), which is not on this map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Phase II Trial to Describe the Pharmacokinetics, Safety and Efficacy of Pharmacogenetics-guided Dosing of Isoniazid in Patients With HIV-associated TB
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Influence of N-acetyltransferase 2 (NAT2) genotype/single nucleotide polymorphisms on clearance of isoniazid in tuberculosis patients: a systematic review of population pharmacokinetic models.European journal of clinical pharmacology · 2022Pooled it
- The association between the NAT2 genetic polymorphisms and risk of DILI during anti-TB treatment: a systematic review and meta-analysis.British journal of clinical pharmacology · 2018Pooled it
- Sex as a Biological Variable in Tuberculosis Pathogenesis.Immunological reviews · 2026Review
- Precision Medicine Strategies to Improve Isoniazid Therapy in Patients with Tuberculosis.European journal of drug metabolism and pharmacokinetics · 2024Review
- Pharmacokinetics of standard versus high-dose isoniazid for treatment of multidrug-resistant tuberculosis.The Journal of antimicrobial chemotherapy · 2022Observational
- Recent advances in the translation of drug metabolism and pharmacokinetics science for drug discovery and development.Acta pharmaceutica Sinica. B · 2022Review
- Semi-Automated Therapeutic Drug Monitoring as a Pillar toward Personalized Medicine for Tuberculosis Management.Pharmaceutics · 2022Review
- PBPK Analysis to Study the Impact of Genetic Polymorphism of NAT2 on Drug-Drug Interaction Potential of Isoniazid.Pharmaceutical research · 2021Article
- The Role of PK/PD Analysis in the Development and Evaluation of Antimicrobials.Pharmaceutics · 2021Review
- Population Pharmacokinetic Properties of Antituberculosis Drugs in Vietnamese Children with Tuberculous Meningitis.Antimicrobial agents and chemotherapy · 2020Article
- Can the personalized medicine approach contribute in controlling tuberculosis in general and India in particular?Precision clinical medicine · 2020Article
- Population pharmacokinetics of isoniazid and dose recommendations in Mexican patients with tuberculosis.International journal of clinical pharmacy · 2020Article
- Scientific considerations for global drug development.Science translational medicine · 2020Review
- Quantitative assessment of the activity of antituberculosis drugs and regimens.Expert review of anti-infective therapy · 2019Review
- What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing.The AAPS journal · 2019Article
- A Physiology-Based Model of Human Bile Acid Metabolism for Predicting Bile Acid Tissue Levels After Drug Administration in Healthy Subjects and BRIC Type 2 Patients.Frontiers in physiology · 2019Article
- Current research toward optimizing dosing of first-line antituberculosis treatment.Expert review of anti-infective therapy · 2019Review
- Physiologically based pharmacokinetic modelling of atomoxetine with regard to CYP2D6 genotypes.Scientific reports · 2018Article
- Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.NPJ systems biology and applications · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to its high early bactericidal activity, isoniazid (INH) plays an essential role in tuberculosis treatment. Genetic polymorphisms of N-acetyltransferase type 2 (NAT2) cause a trimodal distribution of INH pharmacokinetics in slow, intermediate, and fast acetylators. The success of INH-based chemotherapy is associated with acetylator and patient health status. Still, a standard dose recommended by the FDA is administered regardless of acetylator type or immune status, even though adverse effects occur in 5 to 33% of all patients. Slow acetylators have a higher risk of development of drug-induced toxicity, while fast acetylators and immune-deficient patients face lower treatment success rates. To mechanistically assess the trade-off between toxicity and efficacy, we developed a physiologically based pharmacokinetic (PBPK) model describing the NAT2-dependent pharmacokinetics of INH and its metabolites. We combined the PBPK model with a pharmacodynamic (PD) model of antimycobacterial drug effects in the lungs. The resulting PBPK/PD model allowed the simultaneous simulation of treatment efficacies at the site of infection and exposure to toxic metabolites in off-target organs. Subsequently, we evaluated various INH dosing regimens in NAT2-specific immunocompetent and immune-deficient virtual populations. Our results suggest the need for acetylator-specific dose adjustments for optimal treatment outcomes. A reduced dose for slow acetylators substantially lowers the exposure to toxic metabolites and thereby the risk of adverse events, while it maintains sufficient treatment efficacies. Vice versa, intermediate and fast acetylators benefit from increased INH doses and a switch to a twice-daily administration schedule. Our analysis outlines how PBPK/PD modeling may be used to design and individualize treatment regimens.
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