Cited by 353Pharmaceutical studies and practicesPharmacogenetics and Drug MetabolismAnimal testing and alternatives

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A Novel Strategy for Physiologically Based Predictions of Human Pharmacokinetics

Jones, Hannah M, Parrott, Neil, Jorga, Karin, Lav??, Thierry·2006·Clinical Pharmacokinetics

DOI 10.2165/00003088-200645050-00006

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Abstract

Background The major aim of this study was to develop a strategy for predicting human pharmacokinetics using physiologically based pharmacokinetic (PBPK) modelling. This was compared with allometry (of plasma concentration-time profiles using the Dedrick approach), in order to determine the best approaches and strategies for the prediction of human pharmacokinetics.Methods PBPK and Dedrick predictions were made for 19 F. Hoffmann-La Roche compounds. A strategy for the prediction of human pharmacokinetics using PBPK modelling was proposed in this study. Predicted values (pharmacokinetic parameters, plasma concentrations) were compared with observed values obtained after intravenous and oral administration in order to assess the accuracy of the prediction methods.Results By following the proposed strategy for PBPK, a prediction would have been made prospectively for approximately 70% of the compounds. The prediction accuracy for these compounds in terms of the percentage of compounds with an average-fold error of <2-fold was 83%, 50%, 75%, 67%, 92% and 100% for apparent oral clearance (CL/F), apparent volume of distribution during terminal phase after oral administration (V(z)/F), terminal elimination half-life (t(1/2)), peak plasma concentration (C(max)), area under the plasma concentration-time curve (AUC) and time to reach C(max) (t(max)), respectively. For the other 30% compounds, unacceptable prediction accuracy was obtained in animals; therefore, a prospective prediction of human pharmacokinetics would not have been made using PBPK. For these compounds, prediction accuracy was also poor using the Dedrick approach. In the majority of cases, PBPK gave more accurate predictions of pharmacokinetic parameters and plasma concentration-time profiles than the Dedrick approach.Conclusions Based on the dataset evaluated in this study, PBPK gave reasonable predictions of human pharmacokinetics using preclinical data and is the recommended approach in the majority of cases. In addition, PBPK modelling is a useful tool to gain insights into the properties of a compound. Thus, PBPK can guide experimental efforts to obtain the relevant information necessary to understand the compound's properties before entry into human, ultimately resulting in a higher level of prediction accuracy.

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Authors: Jones, H. M., Parrott, N., Jorga, K., & Lav??, T.
Affiliations: F. Hoffmann-La Roche AG (CH)
Corresponding author: Jones, Hannah M
ORCID: Jones, Hannah M
Parrott, Neil
Venue: Clinical Pharmacokinetics
Publisher: Springer Science and Business Media LLC
Published: 2006
Volume: 45
Issue: 5
Pages: 511-542
ISSN: 0312-5963 (ISSN-L)
DOI: 10.2165/00003088-200645050-00006
OpenAlex: W2146393360
Cited by: 352
References: 76
Citations by year: 2026: 10 · 2025: 13 · 2024: 10 · 2023: 13 · 2022: 18 · 2021: 17 · 2020: 16 · 2019: 17 · 2018: 13 · 2017: 14 · 2016: 20 · 2015: 19 · 2014: 19 · 2013: 19 · 2012: 26
FWCI: 20.15
Type: journal article
Language: en
Open access: closed
Locations: Clinical Pharmacokinetics (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
Keywords: physiologically based pharmacokinetic modelling, human pharmacokinetic prediction, allometry, plasma concentration-time curve, oral clearance, volume of distribution, elimination half-life, prediction accuracy, pharmaceutical compounds
MeSH terms: Animals, Pharmaceutical Preparations, Humans, Models, Biological, Pharmacokinetics

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A Novel Strategy for Physiologically Based Predictions of Human Pharmacokinetics

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