Document Detail

In vivo quantitative prediction of the effect of gene polymorphisms and drug interactions on drug exposure for CYP2C19 substrates.
MedLine Citation:
PMID:  23319287     Owner:  NLM     Status:  MEDLINE    
We present a unified quantitative approach to predict the in vivo alteration in drug exposure caused by either cytochrome P450 (CYP) gene polymorphisms or CYP-mediated drug-drug interactions (DDI). An application to drugs metabolized by CYP2C19 is presented. The metrics used is the ratio of altered drug area under the curve (AUC) to the AUC in extensive metabolizers with no mutation or no interaction. Data from 42 pharmacokinetic studies performed in CYP2C19 genetic subgroups and 18 DDI studies were used to estimate model parameters and predicted AUC ratios by using Bayesian approach. Pharmacogenetic information was used to estimate a parameter of the model which was then used to predict DDI. The method adequately predicted the AUC ratios published in the literature, with mean errors of -0.15 and -0.62 and mean absolute errors of 0.62 and 1.05 for genotype and DDI data, respectively. The approach provides quantitative prediction of the effect of five genotype variants and 10 inhibitors on the exposure to 25 CYP2C19 substrates, including a number of unobserved cases. A quantitative approach for predicting the effect of gene polymorphisms and drug interactions on drug exposure has been successfully applied for CYP2C19 substrates. This study shows that pharmacogenetic information can be used to predict DDI. This may have important implications for the development of personalized medicine and drug development.
Sylvain Goutelle; Laurent Bourguignon; Nathalie Bleyzac; Johanna Berry; Fannie Clavel-Grabit; Michel Tod
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Publication Detail:
Type:  Journal Article     Date:  2013-01-15
Journal Detail:
Title:  The AAPS journal     Volume:  15     ISSN:  1550-7416     ISO Abbreviation:  AAPS J     Publication Date:  2013 Apr 
Date Detail:
Created Date:  2013-04-05     Completed Date:  2013-10-22     Revised Date:  2014-01-23    
Medline Journal Info:
Nlm Unique ID:  101223209     Medline TA:  AAPS J     Country:  United States    
Other Details:
Languages:  eng     Pagination:  415-26     Citation Subset:  IM    
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MeSH Terms
Area Under Curve
Aryl Hydrocarbon Hydroxylases / genetics*,  metabolism*
Bayes Theorem
Biological Availability
Drug Interactions
Individualized Medicine
Models, Biological*
Pharmaceutical Preparations / metabolism*
Polymorphism, Genetic*
Reproducibility of Results
Risk Assessment
Risk Factors
Substrate Specificity
Reg. No./Substance:
0/Pharmaceutical Preparations; EC Hydrocarbon Hydroxylases; EC protein, human

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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