Literature DB >> 20354105

Quantitative prediction of intestinal metabolism in humans from a simplified intestinal availability model and empirical scaling factor.

Keitaro Kadono1, Takafumi Akabane, Kenji Tabata, Katsuhiko Gato, Shigeyuki Terashita, Toshio Teramura.   

Abstract

This study aimed to establish a practical and convenient method of predicting intestinal availability (F(g)) in humans for highly permeable compounds at the drug discovery stage, with a focus on CYP3A4-mediated metabolism. We constructed a "simplified F(g) model," described using only metabolic parameters, assuming that passive diffusion is dominant when permeability is high and that the effect of transporters in epithelial cells is negligible. Five substrates for CYP3A4 (alprazolam, amlodipine, clonazepam, midazolam, and nifedipine) and four for both CYP3A4 and P-glycoprotein (P-gp) (nicardipine, quinidine, tacrolimus, and verapamil) were used as model compounds. Observed fraction of drug absorbed (F(a)F(g)) values for these compounds were calculated from in vivo pharmacokinetic (PK) parameters, whereas in vitro intestinal intrinsic clearance (CL(int,intestine)) was determined using human intestinal microsomes. The CL(int,intestine) for the model compounds corrected with that of midazolam was defined as CL(m,index) and incorporated into a simplified F(g) model with empirical scaling factor. Regardless of whether the compound was a P-gp substrate, the F(a)F(g) could be reasonably fitted by the simplified F(g) model, and the value of the empirical scaling factor was well estimated. These results suggest that the effects of P-gp on F(a) and F(g) are substantially minor, at least in the case of highly permeable compounds. Furthermore, liver intrinsic clearance (CL(int,liver)) can be used as a surrogate index of intestinal metabolism based on the relationship between CL(int,liver) and CL(m,index). F(g) can be easily predicted using a simplified F(g) model with the empirical scaling factor, enabling more confident selection of drug candidates with desirable PK profiles in humans.

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Year:  2010        PMID: 20354105     DOI: 10.1124/dmd.109.029322

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


  12 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 nonlinear intestinal absorption of CYP3A4 and P-glycoprotein substrates from their in vitro Km values.

Authors:  Tatsuhiko Tachibana; Motohiro Kato; Yuichi Sugiyama
Journal:  Pharm Res       Date:  2011-09-13       Impact factor: 4.200

Review 3.  Gut Wall Metabolism. Application of Pre-Clinical Models for the Prediction of Human Drug Absorption and First-Pass Elimination.

Authors:  Christopher R Jones; Oliver J D Hatley; Anna-Lena Ungell; Constanze Hilgendorf; Sheila Annie Peters; Amin Rostami-Hodjegan
Journal:  AAPS J       Date:  2016-03-10       Impact factor: 4.009

4.  Physiologically Based Pharmacokinetic Modeling of Fimasartan, Amlodipine, and Hydrochlorothiazide for the Investigation of Drug-Drug Interaction Potentials.

Authors:  Su-Jin Rhee; Hyun A Lee; Soyoung Lee; Eunwoo Kim; Inseung Jeon; Im-Sook Song; Kyung-Sang Yu
Journal:  Pharm Res       Date:  2018-10-15       Impact factor: 4.200

Review 5.  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

6.  Quantitative assessment of intestinal first-pass metabolism of oral drugs using portal-vein cannulated rats.

Authors:  Yoshiki Matsuda; Yoshihiro Konno; Takashi Hashimoto; Mika Nagai; Takayuki Taguchi; Masahiro Satsukawa; Shinji Yamashita
Journal:  Pharm Res       Date:  2014-08-28       Impact factor: 4.200

Review 7.  Sex differences in drug disposition.

Authors:  Offie P Soldin; Sarah H Chung; Donald R Mattison
Journal:  J Biomed Biotechnol       Date:  2011-02-23

Review 8.  Predicting Drug Extraction in the Human Gut Wall: Assessing Contributions from Drug Metabolizing Enzymes and Transporter Proteins using Preclinical Models.

Authors:  Sheila Annie Peters; Christopher R Jones; Anna-Lena Ungell; Oliver J D Hatley
Journal:  Clin Pharmacokinet       Date:  2016-06       Impact factor: 6.447

9.  A comparative evaluation of models to predict human intestinal metabolism from nonclinical data.

Authors:  Estelle Yau; Carl Petersson; Hugues Dolgos; Sheila Annie Peters
Journal:  Biopharm Drug Dispos       Date:  2017-04       Impact factor: 1.627

10.  Drug Transport at the Brain and Endothelial Dysfunction in Preeclampsia: Implications and Perspectives.

Authors:  Pablo Torres-Vergara; Carlos Escudero; Jeffrey Penny
Journal:  Front Physiol       Date:  2018-11-06       Impact factor: 4.566

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