ArticlePloS one2015
Bayesian Population Physiologically-Based Pharmacokinetic (PBPK) Approach for a Physiologically Realistic Characterization of Interindividual Variability in Clinically Relevant Populations.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Simultaneous Ivabradine Parent-Metabolite PBPK/PD Modelling Using a Bayesian Estimation Method.The AAPS journal · 2020Trial
- Model-Informed Dose Selection of Intranasal Epinephrine in Young Children.Journal of clinical pharmacology · 2026Article
- From Population-Based PBPK to Individualized Virtual Twins: Clinical Validation and Applications in Medicine.Journal of clinical medicine · 2026Review
- Integrated Physiologically-based Pharmacokinetic Model with a Quantitative Systems Pharmacology and Toxicology Model for Statins in Disease Population. Part 2: MIDD and MIPD Applications.The AAPS journal · 2025Article
- Exploring the Impact of Developmental Clearance Saturation on Propylene Glycol Exposure in Adults and Term Neonates Using Physiologically Based Pharmacokinetic Modeling.Journal of clinical pharmacology · 2025Article
- Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025Review
- The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment.Toxics · 2023Review
- Review
- Streamlining physiologically-based pharmacokinetic model design for intravenous delivery of nanoparticle drugs.CPT: pharmacometrics & systems pharmacology · 2022Article
- A population physiologically-based pharmacokinetic model to characterize antibody disposition in pediatrics and evaluation of the model using infliximab.British journal of clinical pharmacology · 2022Article
- Current and prospective computational approaches and challenges for developing COVID-19 vaccines.Advanced drug delivery reviews · 2021Review
- General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy.Clinical pharmacology and therapeutics · 2020Article
- Development of a physiologically-based pharmacokinetic model for cyclosporine in Asian children with renal impairment.Translational and clinical pharmacology · 2019Article
- Population pharmacokinetic reanalysis of a Diazepam PBPK model: a comparison of Stan and GNU MCSim.Journal of pharmacokinetics and pharmacodynamics · 2019Article
- Translational learning from clinical studies predicts drug pharmacokinetics across patient populations.NPJ systems biology and applications · 2017Article
- Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance.Current pharmacology reportsReview
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interindividual variability in anatomical and physiological properties results in significant differences in drug pharmacokinetics. The consideration of such pharmacokinetic variability supports optimal drug efficacy and safety for each single individual, e.g. by identification of individual-specific dosings. One clear objective in clinical drug development is therefore a thorough characterization of the physiological sources of interindividual variability. In this work, we present a Bayesian population physiologically-based pharmacokinetic (PBPK) approach for the mechanistically and physiologically realistic identification of interindividual variability. The consideration of a generic and highly detailed mechanistic PBPK model structure enables the integration of large amounts of prior physiological knowledge, which is then updated with new experimental data in a Bayesian framework. A covariate model integrates known relationships of physiological parameters to age, gender and body height. We further provide a framework for estimation of the a posteriori parameter dependency structure at the population level. The approach is demonstrated considering a cohort of healthy individuals and theophylline as an application example. The variability and co-variability of physiological parameters are specified within the population; respectively. Significant correlations are identified between population parameters and are applied for individual- and population-specific visual predictive checks of the pharmacokinetic behavior, which leads to improved results compared to present population approaches. In the future, the integration of a generic PBPK model into an hierarchical approach allows for extrapolations to other populations or drugs, while the Bayesian paradigm allows for an iterative application of the approach and thereby a continuous updating of physiological knowledge with new data. This will facilitate decision making e.g. from preclinical to clinical development or extrapolation of PK behavior from healthy to clinically significant populations.
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