ArticleCurrent therapeutic research, clinical and experimental
A Bayesian Approach for Population Pharmacokinetic Modeling of Alcohol in Japanese Individuals.
Article in Current therapeutic research, clinical and experimental. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Model-Based Exposure-Response Assessment for Spectinamide 1810 in a Mouse Model of Tuberculosis.Antimicrobial agents and chemotherapy · 2021Article
- Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine.Journal of pharmacokinetics and pharmacodynamics · 2020Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBlood alcohol concentration data that were previously obtained from 34 healthy Japanese subjects with limited sampling times were reanalyzed. Characteristics of the data were that the concentrations were obtained from only the early part of the time-concentration curve.
objectiveTo explore significant covariates for the population pharmacokinetic analysis of alcohol by incorporating external data using a Bayesian method, and to estimate effects of the covariates.
methodsThe data were analyzed using a Markov chain Monte Carlo Bayesian estimation with NONMEM 7.3 (ICON Clinical Research LLC, North Wales, Pennsylvania). Informative priors were obtained from the external study.
resultsA 1-compartment model with Michaelis-Menten elimination was used. The typical value for the apparent volume of distribution was 49.3 L at the age of 29.4 years. Volume of distribution was estimated to be 20.4 L smaller in subjects with the
conclusionsA population pharmacokinetic model for alcohol was updated. A Bayesian approach allowed interpretation of significant covariate relationships, even if the current dataset is not informative about all parameters. This is the first study reporting an estimate of the effect of the
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