Literature DB >> 14985145

Predicting drug clearance from recombinantly expressed CYPs: intersystem extrapolation factors.

N J Proctor1, G T Tucker, A Rostami-Hodjegan.   

Abstract

1. Recombinantly expressed human cytochromes P450 (rhCYPs) have been underused for the prediction of human drug clearance (CL). 2. Differences in intrinsic activity (per unit CYP) between rhCYP and human liver enzymes complicate the issue and these discrepancies have not been investigated systematically. We define intersystem extrapolation factors (ISEFs) that allow the use of rhCYP data for the in vitro-in vivo extrapolation of human drug CL and the variance that is associated with interindividual variation of CYP abundance due to genetic and environmental effects. 3. A large database (n = 451) of metabolic stability data has been compiled and used to derive ISEFs for the most commonly used expression systems and CYP enzymes. 4. Statistical models were constructed for the ISEFs to determine major covariates in order to optimize experimental design to increase prediction accuracy. 5. Suggestions have been made for the conduct of future studies using rhCYP to predict human drug clearance.

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Year:  2004        PMID: 14985145     DOI: 10.1080/00498250310001646353

Source DB:  PubMed          Journal:  Xenobiotica        ISSN: 0049-8254            Impact factor:   1.908


  43 in total

1.  A quantitative framework and strategies for management and evaluation of metabolic drug-drug interactions in oncology drug development: new molecular entities as object drugs.

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2.  A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance.

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Journal:  Clin Pharmacokinet       Date:  2010-03       Impact factor: 6.447

3.  Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction.

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4.  Prediction of the effects of genetic polymorphism on the pharmacokinetics of CYP2C9 substrates from in vitro data.

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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.  Prediction and reverse prediction in therapeutics and toxicology.

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Review 7.  Reaction phenotyping: current industry efforts to identify enzymes responsible for metabolizing drug candidates.

Authors:  Timothy W Harper; Patrick J Brassil
Journal:  AAPS J       Date:  2008-04-05       Impact factor: 4.009

8.  Physiologically-Based Pharmacokinetic Modeling of Macitentan: Prediction of Drug-Drug Interactions.

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Journal:  Clin Pharmacokinet       Date:  2016-03       Impact factor: 6.447

9.  A physiologically based pharmacokinetic analysis to predict the pharmacokinetics of intravenous isavuconazole in patients with or without hepatic impairment.

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Journal:  Antimicrob Agents Chemother       Date:  2021-02-22       Impact factor: 5.191

10.  Cytochrome P450-mediated oxidative metabolism of abused synthetic cannabinoids found in K2/Spice: identification of novel cannabinoid receptor ligands.

Authors:  Krishna C Chimalakonda; Kathryn A Seely; Stacie M Bratton; Lisa K Brents; Cindy L Moran; Gregory W Endres; Laura P James; Paul F Hollenberg; Paul L Prather; Anna Radominska-Pandya; Jeffery H Moran
Journal:  Drug Metab Dispos       Date:  2012-08-17       Impact factor: 3.922

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