Literature DB >> 23209193

Application of hybrid approach based on empirical and physiological concept for predicting pharmacokinetics in humans--usefulness of exponent on prospective evaluation of predictability.

Hiroyuki Sayama1, Hiroshi Komura, Motohiro Kogayu.   

Abstract

We developed a hybrid method for predicting plasma concentration-time curves in humans by integrating species differences in in vitro intrinsic clearance (CL(int)) into the Dedrick approach based on the allometry concept. With prediction of clearance (CL) by allometric scaling, taking in vitro CL(int) into consideration improved the accuracy and reduced the average fold error from 2.72 to 1.99. With the hybrid approach of applying the same concept to the Dedrick approach, the predictability of plasma concentration profiles was compared with the results of the conventional Dedrick approach and the physiologically based pharmacokinetic model using 15 compounds with widely ranging physicochemical and pharmacokinetic profiles. The hybrid approach showed the highest predictability among the examined methods. For CL and the apparent volume of distribution at the steady state (V(ss)), the relationship between the exponent of allometric equation and fold error was also evaluated with the hybrid approach. The relationship appeared to be a horseshoe curve. Six compounds with exponents ranging from 0.7 to 1.1 for both CL and V(ss) [antipyrine, caffeine, epiroprim, propafenone, theophylline, and verapamil] displayed higher predictability. Three compounds with an exponent ranging from 0.7 to 1.1 for CL showed better predictability for CL, and the other four compounds appeared to display similar relationship between the exponent and predictability for V(ss). These findings indicated that the exponent becomes a preliminary index to speculate on predictability. Combination of the hybrid approach and exponent allows us to prospectively draw human plasma concentration-time curves, with the implication of possible prediction accuracy prior to clinical studies.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 23209193     DOI: 10.1124/dmd.112.048819

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


  5 in total

1.  A Generic Model for Quantitative Prediction of Interactions Mediated by Efflux Transporters and Cytochromes: Application to P-Glycoprotein and Cytochrome 3A4.

Authors:  Michel Tod; S Goutelle; N Bleyzac; L Bourguignon
Journal:  Clin Pharmacokinet       Date:  2019-04       Impact factor: 6.447

2.  Prediction of drug disposition in diabetic patients by means of a physiologically based pharmacokinetic model.

Authors:  Jia Li; Hai-Fang Guo; Can Liu; Zeyu Zhong; Li Liu; Xiao-Dong Liu
Journal:  Clin Pharmacokinet       Date:  2015-02       Impact factor: 6.447

Review 3.  Current Approaches for Predicting Human PK for Small Molecule Development Candidates: Findings from the IQ Human PK Prediction Working Group Survey.

Authors:  Carl Petersson; Xin Zhou; Joerg Berghausen; David Cebrian; Michael Davies; Kevin DeMent; Peter Eddershaw; Arian Emami Riedmaier; Alix F Leblanc; Nenad Manveski; Punit Marathe; Panteleimon D Mavroudis; Robin McDougall; Neil Parrott; Andreas Reichel; Charles Rotter; David Tess; Laurie P Volak; Guangqing Xiao; Zheng Yang; James Baker
Journal:  AAPS J       Date:  2022-07-19       Impact factor: 3.603

4.  Prediction of Deoxypodophyllotoxin Disposition in Mouse, Rat, Monkey, and Dog by Physiologically Based Pharmacokinetic Model and the Extrapolation to Human.

Authors:  Yang Chen; Kaijing Zhao; Fei Liu; Qiushi Xie; Zeyu Zhong; Mingxing Miao; Xiaodong Liu; Li Liu
Journal:  Front Pharmacol       Date:  2016-12-16       Impact factor: 5.810

5.  Vitreous humor analysis for the detection of xenobiotics in forensic toxicology: a review.

Authors:  Fabien Bévalot; Nathalie Cartiser; Charline Bottinelli; Laurent Fanton; Jérôme Guitton
Journal:  Forensic Toxicol       Date:  2015-10-28       Impact factor: 4.096

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.