ArticleThe AAPS journal2015
Are Physiologically Based Pharmacokinetic Models Reporting the Right C(max)? Central Venous Versus Peripheral Sampling Site.
Article in The AAPS journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 23 citations in OpenAlex.
- Manuscript DMD-D-25-00346 The impact of glycocalyx on partitioning and distribution of basic drugs.Drug metabolism and disposition: the biological fate of chemicals · 2026Article
- A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans.Pharmaceutical research · 2024Review
- A physiologically based pharmacokinetic analysis to predict the pharmacokinetics of intravenous isavuconazole in patients with or without hepatic impairment.Antimicrobial agents and chemotherapy · 2023Article
- A permeability- and perfusion-based PBPK model for improved prediction of concentration-time profiles.Clinical and translational science · 2022Article
- PBPK Simulation-Based Evaluation of Ganciclovir Crystalluria Risk Factors: Effect of Renal Impairment, Old Age, and Low Fluid Intake.The AAPS journal · 2021Article
- Predicting monoclonal antibody pharmacokinetics following subcutaneous administration via whole-body physiologically-based modeling.Journal of pharmacokinetics and pharmacodynamics · 2020Article
- Sampling Site Has a Critical Impact on Physiologically Based Pharmacokinetic Modeling.The Journal of pharmacology and experimental therapeutics · 2020Article
- Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide Optimal Dosing Regimens for Imatinib and Potential Drug Interactions in Paediatrics.Frontiers in pharmacology · 2019Article
- The use of PBPK modeling across the pediatric age range using propofol as a case.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model.CPT: pharmacometrics & systems pharmacology · 2016Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Physiologically based pharmacokinetic (PBPK) models can over-predict maximum plasma concentrations (C(max)) following intravenous administration. A proposed explanation is that invariably PBPK models report the concentration in the central venous compartment, rather than the site where the samples are drawn. The purpose of this study was to identify and validate potential corrective models based on anatomy and physiology governing the blood supply at the site of sampling and incorporate them into a PBPK platform. Four models were developed and scrutinised for their corrective potential. All assumed the peripheral sampling site concentration could be described by contributions from surrounding tissues and utilised tissue-specific concentration-time profiles reported from the full-PBPK model within the Simcyp Simulator. Predicted concentrations for the peripheral site were compared to the observed C(max). The models results were compared to clinical data for 15 studies over seven compounds (alprazolam, imipramine, metoprolol, midazolam, omeprazole, rosiglitazone and theophylline). The final model utilised tissue concentrations from adipose, skin, muscle and a contribution from artery. Predicted C(max) values considering the central venous compartment can over-predict the observed values up to 10-fold whereas the new sampling site predictions were within 2-fold of observed values. The model was particularly relevant for studies where traditional PBPK models over-predict early time point concentrations. A successful corrective model for C(max) prediction has been developed, subject to further validation. These models can be enrolled as built-up modules into PBPK platforms and potentially account for factors that may affect the initial mixing of the blood at the site of sampling.
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