ArticleJournal of pharmacokinetics and pharmacodynamics2019
Population pharmacokinetic reanalysis of a Diazepam PBPK model: a comparison of Stan and GNU MCSim.
Article in Journal of pharmacokinetics and pharmacodynamics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- Review on Predictive Models and Integration Strategies for Holistic Impact Assessment of Chemicals and Materials.Environmental science & technology · 2026Review
- Comparing computational times for simulations when using PBPK model template and stand-alone implementations of PBPK models.Frontiers in toxicology · 2025Article
- A Meta-Analysis Methodology in Stan to Estimate Population Pharmacokinetic Parameters from Multiple Aggregate Concentration-Time Datasets: Application to Gevokizumab mPBPK Model.Pharmaceutics · 2024Article
- Parameter grouping and co-estimation in physiologically based kinetic models using genetic algorithms.Toxicological sciences : an official journal of the Society of Toxicology · 2024Article
- Investigation of simplified physiologically-based pharmacokinetic models in rat and human.CPT: pharmacometrics & systems pharmacology · 2023Article
- The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment.International journal of environmental research and public health · 2023Review
- Population PBPK modeling using parametric and nonparametric methods of the Simcyp Simulator, and Bayesian samplers.CPT: pharmacometrics & systems pharmacology · 2022Article
- A Physiologically Based Pharmacokinetic Model for Predicting Diazepam Pharmacokinetics after Intravenous, Oral, Intranasal, and Rectal Applications.Pharmaceutics · 2021Article
- Well-tempered MCMC simulations for population pharmacokinetic models.Journal of pharmacokinetics and pharmacodynamics · 2020Article
- Population Pharmacodynamic Modeling of Epoetin Alfa in End-Stage Renal Disease Patients Receiving Maintenance Treatment Using Bayesian Approach.CPT: pharmacometrics & systems pharmacology · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The aim of this study is to benchmark two Bayesian software tools, namely Stan and GNU MCSim, that use different Markov chain Monte Carlo (MCMC) methods for the estimation of physiologically based pharmacokinetic (PBPK) model parameters. The software tools were applied and compared on the problem of updating the parameters of a Diazepam PBPK model, using time-concentration human data. Both tools produced very good fits at the individual and population levels, despite the fact that GNU MCSim is not able to consider multivariate distributions. Stan outperformed GNU MCSim in sampling efficiency, due to its almost uncorrelated sampling. However, GNU MCSim exhibited much faster convergence and performed better in terms of effective samples produced per unit of time.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.