Literature DB >> 24018828

Development of a hybrid physiologically based pharmacokinetic model with drug-specific scaling factors in rat to improve prediction of human pharmacokinetics.

Hiroyuki Sayama1, Hiroshi Komura, Motohiro Kogayu, Masahiro Iwaki.   

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.
© 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Entities:  

Keywords:  ADME; PBPK modeling; in vitro-in vivo extrapolation (IVIVE); metabolic clearance; modeling and simulation; pharmacokinetics; physiological model; prediction of human pharmacokinetics; simulations; translational research

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Year:  2013        PMID: 24018828     DOI: 10.1002/jps.23726

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  2 in total

1.  Application of a physiologically based pharmacokinetic model informed by a top-down approach for the prediction of pharmacokinetics in chronic kidney disease patients.

Authors:  Hiroyuki Sayama; Hiroaki Takubo; Hiroshi Komura; Motohiro Kogayu; Masahiro Iwaki
Journal:  AAPS J       Date:  2014-06-11       Impact factor: 4.009

Review 2.  Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies.

Authors:  Neil A Miller; Micaela B Reddy; Aki T Heikkinen; Viera Lukacova; Neil Parrott
Journal:  Clin Pharmacokinet       Date:  2019-06       Impact factor: 6.447

  2 in total

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