Development of a Hybrid Physiologically Based Pharmacokinetic Model with Drug‐Specific Scaling Factors in Rat to Improve Prediction of Human Pharmacokinetics

Sayama, Hiroyuki; Komura, Hiroshi; Kogayu, Motohiro; Iwaki, Masahiro

doi:10.1002/jps.23726

Cited by 16Pharmaceutical studies and practicesPharmacogenetics and Drug MetabolismAnimal testing and alternatives

Development of a Hybrid Physiologically Based Pharmacokinetic Model with Drug‐Specific Scaling Factors in Rat to Improve Prediction of Human Pharmacokinetics

Sayama, Hiroyuki, Komura, Hiroshi, Kogayu, Motohiro, Iwaki, Masahiro·2013·Journal of Pharmaceutical Sciences

DOI 10.1002/jps.23726

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Abstract

Accurate prediction of pharmacokinetics (PK) in humans has been a vital part of drug discovery. The aims of this study are to verify the usefulness of scaling factors for clearance (CL) and apparent volume of distribution at the steady state (Vss ) estimated from the difference between observed and predicted PK profiles in rats for human PK prediction, and to develop a novel hybrid physiologically based pharmacokinetic (PBPK) model with the two scaling factors. The human prediction accuracies for CL with in vitro-in vivo extrapolation and Vss with a tissue composition model were improved by using rat-scaling factors. This improvement was explainable by data that the scaling factors for CL and Vss in rats were correlated with those in humans. The predictability of plasma concentration-time profiles by the hybrid PBPK model incorporating two scaling factors was compared mainly with that by the conventional PBPK model. The hybrid PBPK model yielded higher prediction accuracy for plasma concentrations than the conventional method. Furthermore, we proposed a tiered approach using the three prediction methods, including the hybrid Dedrick approach, that were previously reported (Sayama H, Komura H, Kogayu M. 2013. Drug Metab Dispos 41:498-507), taking the available information in the individual stages of drug discovery and development into consideration.

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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 [49]

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Authors: Sayama, H., Komura, H., Kogayu, M., & Iwaki, M.
Affiliations: Japan Tobacco (Japan) (JP)
Kindai University (JP)
Corresponding author: Komura, Hiroshi
ORCID: Komura, Hiroshi
Venue: Journal of Pharmaceutical Sciences
Publisher: Elsevier BV
Published: 2013-11
Volume: 102
Issue: 11
Pages: 4193-4204
ISSN: 0022-3549 (ISSN-L)
DOI: 10.1002/jps.23726
OpenAlex: W2016381390
Cited by: 16
References: 29
Citations by year: 2021: 1 · 2020: 2 · 2019: 4 · 2018: 3 · 2017: 1 · 2016: 3 · 2014: 2
FWCI: 1.56
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Journal of Pharmaceutical Sciences (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: scale factor, human pharmacokinetic prediction, rat-to-human extrapolation, in vitro-in vivo extrapolation, clearance, volume of distribution, plasma concentration-time curve
MeSH terms: Animals, Computer Simulation, Pharmaceutical Preparations, Humans, Metabolic Clearance Rate, Models, Biological, Pharmacokinetics, Rats

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Development of a Hybrid Physiologically Based Pharmacokinetic Model with Drug‐Specific Scaling Factors in Rat to Improve Prediction of Human Pharmacokinetics

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