Literature DB >> 11727321

The prediction of human clearance from hepatic microsomal metabolism data.

R S Obach1.   

Abstract

Human liver microsomal intrinsic clearance has become a commonly measured parameter during drug discovery, and such data are used to design compounds predicted to possess optimal drug disposition characteristics. Liver microsomal intrinsic clearance values can be scaled and used to predict hepatic clearance in humans. Clearance, when combined with the volume of distribution, determines the half-life of a drug. Hepatic clearance, when combined with absorption, determines the oral bioavailability of a drug. Half-life and oral bioavailability are key determinants of the dosing regimen, i.e., size of dose and frequency of administration. Thus, the accurate prediction of human clearance is important in the selection of new compounds for progression into development, as new drugs on the market must not only be efficacious and safe, but must also be convenient to use for patients and physicians. Over the past decade, exploring methods whereby human clearance can be predicted from in vitro data has been an area of active research in drug metabolism science. Human liver microsomes have been a key tool in this research. This in vitro system possesses many of the major drug metabolizing enzymes and is thus applicable to a wide variety of compounds. This review describes the theoretical and practical aspects of predicting clearance from human liver microsomal intrinsic clearance data, a summary of advantages and shortcomings of this in vitro system, a synopsis of recent applications of human liver microsomal intrinsic clearance data in clearance predictions, and a discussion of potential future directions for this field.

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Year:  2001        PMID: 11727321

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  13 in total

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2.  Metabolic assessment in liver microsomes by co-activating cytochrome P450s and UDP-glycosyltransferases.

Authors:  Z Yan; G W Caldwell
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2003 Jul-Sep       Impact factor: 2.441

Review 3.  Modeling kinetics of subcellular disposition of chemicals.

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Journal:  AAPS J       Date:  2017-10-10       Impact factor: 4.009

6.  Determination of a human hepatic microsomal scaling factor for predicting in vivo drug clearance.

Authors:  Nancy Hakooz; Kiyomi Ito; Helen Rawden; Helen Gill; Lynn Lemmers; Alan R Boobis; Robert J Edwards; David J Carlile; Brian G Lake; J Brian Houston
Journal:  Pharm Res       Date:  2006-02-28       Impact factor: 4.200

7.  Allometric scaling of pharmacokinetic parameters in drug discovery: can human CL, Vss and t1/2 be predicted from in-vivo rat data?

Authors:  Gary W Caldwell; John A Masucci; Zhengyin Yan; William Hageman
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2004 Apr-Jun       Impact factor: 2.441

8.  Correlating the metabolic stability of psychedelic 5-HT₂A agonists with anecdotal reports of human oral bioavailability.

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Journal:  Neurochem Res       Date:  2014-02-12       Impact factor: 3.996

9.  Discovery and in Vitro Optimization of 3-Sulfamoylbenzamides as ROMK Inhibitors.

Authors:  Matthew F Sammons; Sujay V Kharade; Kevin J Filipski; Markus Boehm; Aaron C Smith; Andre Shavnya; Dilinie P Fernando; Matthew S Dowling; Philip A Carpino; Neil A Castle; Shannon G Zellmer; Brett M Antonio; James R Gosset; Anthony Carlo; Jerod S Denton
Journal:  ACS Med Chem Lett       Date:  2018-01-19       Impact factor: 4.345

10.  Small structural changes of the imidazopyridine diacylglycerol acyltransferase 2 (DGAT2) inhibitors produce an improved safety profile.

Authors:  K Futatsugi; K Huard; D W Kung; J C Pettersen; D A Flynn; J R Gosset; G E Aspnes; R J Barnes; S Cabral; M S Dowling; D P Fernando; T C Goosen; W P Gorczyca; D Hepworth; M Herr; S Lavergne; Q Li; M Niosi; S T M Orr; I D Pardo; S M Perez; J Purkal; T J Schmahai; N Shirai; A M Shoieb; J Zhou; B Goodwin
Journal:  Medchemcomm       Date:  2016-11-22       Impact factor: 3.597

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