{"title":"通过 PBPK 模型预测文拉法辛及其活性代谢物在不同 CYP2D6 基因型中的药代动力学,以及与克拉霉素和帕罗西汀的药物相互作用。","authors":"Chang-Keun Cho, Pureum Kang, Choon-Gon Jang, Seok-Yong Lee, Yun Jeong Lee, Jung-Woo Bae, Chang-Ik Choi","doi":"10.1007/s12272-024-01495-0","DOIUrl":null,"url":null,"abstract":"<div><p>Venlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI), is indicated for the treatment of major depressive disorder, social anxiety disorder, generalized anxiety disorder, and panic disorder. Venlafaxine is metabolized to the active metabolite desvenlafaxine mainly by CYP2D6. Genetic polymorphism of <i>CYP2D6</i> and coadministration with other medications can significantly affect the pharmacokinetics and/or pharmacodynamics of venlafaxine and its active metabolite. This study aimed to establish the PBPK models of venlafaxine and its active metabolite related to <i>CYP2D6</i> genetic polymorphism and to predict drug–drug interactions (DDIs) with clarithromycin and paroxetine in different <i>CYP2D6</i> genotypes. Clinical pharmacogenomic data for venlafaxine and desvenlafaxine were collected to build the PBPK model. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) characteristics of respective compounds were obtained from previously reported data, predicted by the PK-Sim<sup>®</sup> software, or optimized to capture the plasma concentration–time profiles. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and plasma concentration–time profiles to the observed data. Predicted plasma concentration–time profiles of venlafaxine and its active metabolite were visually similar to the observed profiles and all predicted AUC and C<sub>max</sub> values for respective compounds were included in the twofold error range of observed values in non-genotyped populations and different <i>CYP2D6</i> genotypes. When clarithromycin or clarithromycin plus paroxetine was concomitantly administered, predicted plasma concentration–time profiles of venlafaxine properly captured the observed profiles in two different <i>CYP2D6</i> genotypes and all predicted DDI ratios for AUC and C<sub>max</sub> were included within the acceptance range. Consequently, the present model successfully captured the pharmacokinetic alterations of venlafaxine and its active metabolite according to <i>CYP2D6</i> genetic polymorphism as well as the DDIs between venlafaxine and two CYP inhibitors. The present model can be used to predict the pharmacokinetics of venlafaxine and its active metabolite considering different races, ages, coadministered drugs, and CYP2D6 activity of individuals and it can contribute to individualized pharmacotherapy of venlafaxine.</p></div>","PeriodicalId":8287,"journal":{"name":"Archives of Pharmacal Research","volume":"47 5","pages":"481 - 504"},"PeriodicalIF":6.9000,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PBPK modeling to predict the pharmacokinetics of venlafaxine and its active metabolite in different CYP2D6 genotypes and drug–drug interactions with clarithromycin and paroxetine\",\"authors\":\"Chang-Keun Cho, Pureum Kang, Choon-Gon Jang, Seok-Yong Lee, Yun Jeong Lee, Jung-Woo Bae, Chang-Ik Choi\",\"doi\":\"10.1007/s12272-024-01495-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Venlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI), is indicated for the treatment of major depressive disorder, social anxiety disorder, generalized anxiety disorder, and panic disorder. Venlafaxine is metabolized to the active metabolite desvenlafaxine mainly by CYP2D6. Genetic polymorphism of <i>CYP2D6</i> and coadministration with other medications can significantly affect the pharmacokinetics and/or pharmacodynamics of venlafaxine and its active metabolite. This study aimed to establish the PBPK models of venlafaxine and its active metabolite related to <i>CYP2D6</i> genetic polymorphism and to predict drug–drug interactions (DDIs) with clarithromycin and paroxetine in different <i>CYP2D6</i> genotypes. Clinical pharmacogenomic data for venlafaxine and desvenlafaxine were collected to build the PBPK model. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) characteristics of respective compounds were obtained from previously reported data, predicted by the PK-Sim<sup>®</sup> software, or optimized to capture the plasma concentration–time profiles. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and plasma concentration–time profiles to the observed data. Predicted plasma concentration–time profiles of venlafaxine and its active metabolite were visually similar to the observed profiles and all predicted AUC and C<sub>max</sub> values for respective compounds were included in the twofold error range of observed values in non-genotyped populations and different <i>CYP2D6</i> genotypes. When clarithromycin or clarithromycin plus paroxetine was concomitantly administered, predicted plasma concentration–time profiles of venlafaxine properly captured the observed profiles in two different <i>CYP2D6</i> genotypes and all predicted DDI ratios for AUC and C<sub>max</sub> were included within the acceptance range. Consequently, the present model successfully captured the pharmacokinetic alterations of venlafaxine and its active metabolite according to <i>CYP2D6</i> genetic polymorphism as well as the DDIs between venlafaxine and two CYP inhibitors. The present model can be used to predict the pharmacokinetics of venlafaxine and its active metabolite considering different races, ages, coadministered drugs, and CYP2D6 activity of individuals and it can contribute to individualized pharmacotherapy of venlafaxine.</p></div>\",\"PeriodicalId\":8287,\"journal\":{\"name\":\"Archives of Pharmacal Research\",\"volume\":\"47 5\",\"pages\":\"481 - 504\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of Pharmacal Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12272-024-01495-0\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Pharmacal Research","FirstCategoryId":"3","ListUrlMain":"https://link.springer.com/article/10.1007/s12272-024-01495-0","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
PBPK modeling to predict the pharmacokinetics of venlafaxine and its active metabolite in different CYP2D6 genotypes and drug–drug interactions with clarithromycin and paroxetine
Venlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI), is indicated for the treatment of major depressive disorder, social anxiety disorder, generalized anxiety disorder, and panic disorder. Venlafaxine is metabolized to the active metabolite desvenlafaxine mainly by CYP2D6. Genetic polymorphism of CYP2D6 and coadministration with other medications can significantly affect the pharmacokinetics and/or pharmacodynamics of venlafaxine and its active metabolite. This study aimed to establish the PBPK models of venlafaxine and its active metabolite related to CYP2D6 genetic polymorphism and to predict drug–drug interactions (DDIs) with clarithromycin and paroxetine in different CYP2D6 genotypes. Clinical pharmacogenomic data for venlafaxine and desvenlafaxine were collected to build the PBPK model. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) characteristics of respective compounds were obtained from previously reported data, predicted by the PK-Sim® software, or optimized to capture the plasma concentration–time profiles. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and plasma concentration–time profiles to the observed data. Predicted plasma concentration–time profiles of venlafaxine and its active metabolite were visually similar to the observed profiles and all predicted AUC and Cmax values for respective compounds were included in the twofold error range of observed values in non-genotyped populations and different CYP2D6 genotypes. When clarithromycin or clarithromycin plus paroxetine was concomitantly administered, predicted plasma concentration–time profiles of venlafaxine properly captured the observed profiles in two different CYP2D6 genotypes and all predicted DDI ratios for AUC and Cmax were included within the acceptance range. Consequently, the present model successfully captured the pharmacokinetic alterations of venlafaxine and its active metabolite according to CYP2D6 genetic polymorphism as well as the DDIs between venlafaxine and two CYP inhibitors. The present model can be used to predict the pharmacokinetics of venlafaxine and its active metabolite considering different races, ages, coadministered drugs, and CYP2D6 activity of individuals and it can contribute to individualized pharmacotherapy of venlafaxine.
期刊介绍:
Archives of Pharmacal Research is the official journal of the Pharmaceutical Society of Korea and has been published since 1976. Archives of Pharmacal Research is an interdisciplinary journal devoted to the publication of original scientific research papers and reviews in the fields of drug discovery, drug development, and drug actions with a view to providing fundamental and novel information on drugs and drug candidates.