The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.
A Novel Strategy for Physiologically Based Predictions of Human Pharmacokinetics
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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In the citing paper
“Physiologically based pharmacokinetic modelling has been shown to be superior to empirical scaling [16, 18], but the benefits of the PBPK approach go beyond the accuracy of the prediction to include an improved mechanistic understanding.”
In the citing paper
“A seminal paper from Jones et al. [16] first demonstrated that PBPK modelling, with verification of predictive performance first performed in preclinical species, is superior to empirical methods for predicting pharmacokinetics.”
From Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies (2019) · cites this paper as Jones et al. [16]
In the citing paper
“Given the importance of assessing the ability to predict a compound's pharmacokinetic properties in preclinical species and for appropriate mechanistic studies to inform model development as appropriate, it is not surprising that the Pharmaceutical Research and Manufacturers of America application of PBPK modelling resulted in poor predictions, particularly in comparison to other assessments that”
Citations
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Cited by
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Mechanism-Based Concepts of Size and Maturity in Pharmacokinetics
Anderson, B. J., & Holford, N. H. G. (2007) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev.pharmtox.48.113006.094708 · Cited by 1,158
Physiologically-Based Pharmacokinetics in Drug Development and Regulatory Science
Rowland, M., Peck, C., & Tucker, G. (2011) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010510-100540 · Cited by 662
Basic Concepts in Physiologically Based Pharmacokinetic Modeling in Drug Discovery and Development
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Self-citationTo Scale or Not to Scale: The Principles of Dose Extrapolation
Sharma, V., & McNeill, J. H. (2009) · British Journal of Pharmacology · doi:10.1111/j.1476-5381.2009.00267.x · Cited by 544
The Simcyp ® Population-based ADME Simulator
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Metadata
- Authors
- Jones, H. M., Parrott, N., Jorga, K., & Lav??, T.
- Affiliations
- F. Hoffmann-La Roche AG (CH)
- Corresponding author
- Jones, Hannah M
- Venue
- Clinical Pharmacokinetics
- Published
- 2006
- Volume
- 45
- Issue
- 5
- Pages
- 511-542
- ISSN
- 0312-5963 (ISSN-L)
- 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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