Literature DB >> 17344337

Use of hepatocytes to assess the contribution of hepatic uptake to clearance in vivo.

Matthew G Soars1, Ken Grime, Joanne L Sproston, Peter J H Webborn, Robert J Riley.   

Abstract

The wealth of information that has emerged in recent years detailing the substrate specificity of hepatic transporters necessitates an investigation into their potential role in drug elimination. Therefore, an assay in which the loss of parent compound from the incubation medium into hepatocytes ("media loss" assay) was developed to assess the impact of hepatic uptake on unbound drug intrinsic clearance in vivo (CL(int ub in vivo)). Studies using conventional hepatocyte incubations for a subset of 36 AstraZeneca new chemical entities (NCEs) resulted in a poor projection of CL(int ub in vivo) (r2 = 0.25, p = 0.002, average fold error = 57). This significant underestimation of CL(int ub in vivo) suggested that metabolism was not the dominant clearance mechanism for the majority of compounds examined. However, CL(int ub in vivo) was described well for this dataset using an initial compound "disappearance" CL(int) obtained from media loss assays (r2 = 0.72, p = 6.3 x 10(-11), average fold error = 3). Subsequent studies, using this method for the same 36 NCEs, suggested that the active uptake into human hepatocytes was generally slower (3-fold on average) than that observed with rat hepatocytes. The accurate prediction of human CL(int ub in vivo) (within 4-fold) for the marketed drug transporter substrates montelukast, bosentan, atorvastatin, and pravastatin confirmed further the utility of this assay. This work has described a simple method, amenable for use within a drug discovery setting, for predicting the in vivo clearance of drugs with significant hepatic uptake.

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Year:  2007        PMID: 17344337     DOI: 10.1124/dmd.106.014464

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


  20 in total

1.  Use of mechanistic modeling to assess interindividual variability and interspecies differences in active uptake in human and rat hepatocytes.

Authors:  Karelle Ménochet; Kathryn E Kenworthy; J Brian Houston; Aleksandra Galetin
Journal:  Drug Metab Dispos       Date:  2012-06-04       Impact factor: 3.922

2.  Simultaneous assessment of uptake and metabolism in rat hepatocytes: a comprehensive mechanistic model.

Authors:  Karelle Ménochet; Kathryn E Kenworthy; J Brian Houston; Aleksandra Galetin
Journal:  J Pharmacol Exp Ther       Date:  2011-12-21       Impact factor: 4.030

3.  Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS).

Authors:  Manthena V Varma; Stefanus J Steyn; Charlotte Allerton; Ayman F El-Kattan
Journal:  Pharm Res       Date:  2015-07-09       Impact factor: 4.200

4.  Characterization of non-radiolabeled Thyroxine (T4) uptake in cryopreserved rat hepatocyte suspensions: Pharmacokinetic implications for PFOA and PFOS chemical exposure.

Authors:  Julian Selano; Vicki Richardson; John Washington; Chris Mazur
Journal:  Toxicol In Vitro       Date:  2019-03-28       Impact factor: 3.500

Review 5.  Prediction of hepatic clearance in human from in vitro data for successful drug development.

Authors:  Masato Chiba; Yasuyuki Ishii; Yuichi Sugiyama
Journal:  AAPS J       Date:  2009-04-30       Impact factor: 4.009

6.  Novel in vitro-in vivo extrapolation (IVIVE) method to predict hepatic organ clearance in rat.

Authors:  Ken-ichi Umehara; Gian Camenisch
Journal:  Pharm Res       Date:  2011-10-20       Impact factor: 4.200

7.  Prediction of pharmacokinetic profile of valsartan in human based on in vitro uptake transport data.

Authors:  Agnès Poirier; Anne-Christine Cascais; Christoph Funk; Thierry Lavé
Journal:  J Pharmacokinet Pharmacodyn       Date:  2009-11-20       Impact factor: 2.745

8.  Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Clearance and Liver Partitioning of OATP and OCT Substrates in Cynomolgus Monkeys.

Authors:  Bridget L Morse; Jamus G MacGuire; Anthony M Marino; Yue Zhao; Maxine Fox; Yueping Zhang; Hong Shen; W Griffith Humphreys; Punit Marathe; Yurong Lai
Journal:  AAPS J       Date:  2017-10-10       Impact factor: 4.009

9.  Physiologically Based Pharmacokinetic (PBPK) Modeling of Pitavastatin and Atorvastatin to Predict Drug-Drug Interactions (DDIs).

Authors:  Peng Duan; Ping Zhao; Lei Zhang
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-08       Impact factor: 2.441

10.  Fusidic Acid Inhibits Hepatic Transporters and Metabolic Enzymes: Potential Cause of Clinical Drug-Drug Interaction Observed with Statin Coadministration.

Authors:  Anshul Gupta; Jennifer J Harris; Jianrong Lin; James P Bulgarelli; Bruce K Birmingham; Scott W Grimm
Journal:  Antimicrob Agents Chemother       Date:  2016-09-23       Impact factor: 5.191

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