Literature DB >> 30420404

Prediction of Human Distribution Volumes of Compounds in Various Elimination Phases Using Physiologically Based Pharmacokinetic Modeling and Experimental Pharmacokinetics in Animals.

Hidetoshi Shimizu1, Kosuke Yoshida2, Tomohisa Nakada2, Koki Kojima2, Akihito Ogasawara2, Yoshinobu Nakamaru2, Hiroshi Yamazaki1.   

Abstract

Predicting the pharmacokinetics of compounds in humans is an important part of the drug development process. In this study, the plasma concentration profiles of 10 marketed compounds exhibiting two-phase elimination after intravenous administration in humans were evaluated in terms of distribution volumes just after intravenous administration (V 1), at steady state (V ss), and in the elimination phase (Vβ ) using physiologically based pharmacokinetic (PBPK) modeling implemented in a commercially available simulator (Simcyp). When developing human PBPK models, the insight gained from prior animal PBPK models based on nonclinical data informed the optimization of the lipophilicity input of the compounds and the selection of the appropriate mechanistic tissue partition methods. The accuracy of V 1, V ss, and Vβ values predicted that using human PBPK models developed in accordance with prior animal PBPK models was superior to using those predicted using conventional approaches, such as allometric scaling, especially for V 1 and Vβ By conventional approaches, the V 1 and Vβ values of 4-5 of 10 compounds were predicted within a 3-fold error of observed values, whereas V ss values for their majority were predicted as such. PBPK models predicted V 1, V ss, and Vβ values for almost all compounds within 3-fold errors, resulting in better predictions of plasma concentration profiles than allometric scaling. The distribution volumes predicted using human PBPK models based on prior animal PBPK modeling were more accurate than those predicted without reference to animal models. This study demonstrated that human PBPK models developed with consideration of animal PBPK models could accurately predict distribution volumes in various elimination phases.
Copyright © 2019 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2018        PMID: 30420404     DOI: 10.1124/dmd.118.083642

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  3 in total

1.  A Mechanistic Absorption and Disposition Model of Ritonavir to Predict Exposure and Drug-Drug Interaction Potential of CYP3A4/5 and CYP2D6 Substrates.

Authors:  Sumit Arora; Amita Pansari; Peter J Kilford; Masoud Jamei; David B Turner; Iain Gardner
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2022-04-29       Impact factor: 2.441

2.  Physiologically-Based Pharmacokinetic Models of CYP2D6 Substrate and Inhibitors Nebivolol, Cinacalcet and Mirabegron to Simulate Drug-Drug Interactions.

Authors:  Peter Kilford; Nika Khoshaein; Roz Southall; Iain Gardner
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2022-07-15       Impact factor: 2.569

3.  Prediction of CYP-mediated DDIs involving inhibition: Approaches to address the requirements for system qualification of the Simcyp Simulator.

Authors:  Peter J Kilford; Kuan-Fu Chen; Kim Crewe; Iain Gardner; Oliver Hatley; Alice Ban Ke; Sibylle Neuhoff; Mian Zhang; Karen Rowland Yeo
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-04-28
  3 in total

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