Literature DB >> 25609219

Physiologically based pharmacokinetic modeling for sequential metabolism: effect of CYP2C19 genetic polymorphism on clopidogrel and clopidogrel active metabolite pharmacokinetics.

Nassim Djebli1, David Fabre2, Xavier Boulenc2, Gérard Fabre2, Eric Sultan2, Fabrice Hurbin2.   

Abstract

Clopidogrel is a prodrug that needs to be converted to its active metabolite (clopi-H4) in two sequential cytochrome P450 (P450)-dependent steps. In the present study, a dynamic physiologically based pharmacokinetic (PBPK) model was developed in Simcyp for clopidogrel and clopi-H4 using a specific sequential metabolite module in four populations with phenotypically different CYP2C19 activity (poor, intermediate, extensive, and ultrarapid metabolizers) receiving a loading dose of 300 mg followed by a maintenance dose of 75 mg. This model was validated using several approaches. First, a comparison of predicted-to-observed area under the curve (AUC)0-24 obtained from a randomized crossover study conducted in four balanced CYP2C19-phenotype metabolizer groups was performed using a visual predictive check method. Second, the interindividual and intertrial variability (on the basis of AUC0-24 comparisons) between the predicted trials and the observed trial of individuals, for each phenotypic group, were compared. Finally, a further validation, on the basis of drug-drug-interaction prediction, was performed by comparing observed values of clopidogrel and clopi-H4 with or without dronedarone (moderate CYP3A4 inhibitor) coadministration using a previously developed and validated physiologically based PBPK dronedarone model. The PBPK model was well validated for both clopidogrel and its active metabolite clopi-H4, in each CYP2C19-phenotypic group, whatever the treatment period (300-mg loading dose and 75-mg last maintenance dose). This is the first study proposing a full dynamic PBPK model able to accurately predict simultaneously the pharmacokinetics of the parent drug and of its primary and secondary metabolites in populations with genetically different activity for a metabolizing enzyme.
Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2015        PMID: 25609219     DOI: 10.1124/dmd.114.062596

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


  18 in total

Review 1.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Authors:  Jennifer E Sager; Jingjing Yu; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2015-08-21       Impact factor: 3.922

Review 2.  The expanding role of prodrugs in contemporary drug design and development.

Authors:  Jarkko Rautio; Nicholas A Meanwell; Li Di; Michael J Hageman
Journal:  Nat Rev Drug Discov       Date:  2018-04-27       Impact factor: 84.694

3.  Pharmacokinetic interactions and dosing rationale for antiepileptic drugs in adults and children.

Authors:  Sven C van Dijkman; Willem M Rauwé; Meindert Danhof; Oscar Della Pasqua
Journal:  Br J Clin Pharmacol       Date:  2017-11-07       Impact factor: 4.335

Review 4.  Towards Personalized Antithrombotic Treatments: Focus on P2Y12 Inhibitors and Direct Oral Anticoagulants.

Authors:  Jean Terrier; Youssef Daali; Pierre Fontana; Chantal Csajka; Jean-Luc Reny
Journal:  Clin Pharmacokinet       Date:  2019-12       Impact factor: 6.447

5.  Physiologically based pharmacokinetic (PBPK) modelling of tamsulosin related to CYP2D6*10 allele.

Authors:  Pureum Kang; Hye-Jung Park; Chang-Keun Cho; Yun Jeong Lee; Jung-Woo Bae; Choon-Gon Jang; Seok-Yong Lee
Journal:  Arch Pharm Res       Date:  2021-11-09       Impact factor: 4.946

6.  Development of a physiology-directed population pharmacokinetic and pharmacodynamic model for characterizing the impact of genetic and demographic factors on clopidogrel response in healthy adults.

Authors:  Xi-Ling Jiang; Snehal Samant; Joshua P Lewis; Richard B Horenstein; Alan R Shuldiner; Laura M Yerges-Armstrong; Lambertus A Peletier; Lawrence J Lesko; Stephan Schmidt
Journal:  Eur J Pharm Sci       Date:  2015-10-30       Impact factor: 4.384

7.  Pitfalls of using numerical predictive checks for population physiologically-based pharmacokinetic model evaluation.

Authors:  Anil R Maharaj; Huali Wu; Christoph P Hornik; Michael Cohen-Wolkowiez
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-04-23       Impact factor: 2.410

Review 8.  Pharmacokinetic and Pharmacodynamic Responses to Clopidogrel: Evidences and Perspectives.

Authors:  Yan-Jiao Zhang; Mu-Peng Li; Jie Tang; Xiao-Ping Chen
Journal:  Int J Environ Res Public Health       Date:  2017-03-14       Impact factor: 3.390

9.  Physiologically based pharmacokinetic (PBPK) modeling for prediction of celecoxib pharmacokinetics according to CYP2C9 genetic polymorphism.

Authors:  Young-Hoon Kim; Pureum Kang; Chang-Keun Cho; Eui Hyun Jung; Hye-Jeong Park; Yun Jeong Lee; Jung-Woo Bae; Choon-Gon Jang; Seok-Yong Lee
Journal:  Arch Pharm Res       Date:  2021-07-25       Impact factor: 4.946

Review 10.  Pharmacogenomic Impact of CYP2C19 Variation on Clopidogrel Therapy in Precision Cardiovascular Medicine.

Authors:  Sherry-Ann Brown; Naveen Pereira
Journal:  J Pers Med       Date:  2018-01-30
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