{"title":"基于生理学的药代动力学(PBPK)模型预测不同 CYP2C9 基因型的厄贝沙坦药代动力学","authors":"Chang-Keun Cho, Pureum Kang, Choon-Gon Jang, Seok-Yong Lee, Yun Jeong Lee, Chang-Ik Choi","doi":"10.1007/s12272-023-01472-z","DOIUrl":null,"url":null,"abstract":"<div><p>Irbesartan, a potent and selective angiotensin II type-1 (AT<sub>1</sub>) receptor blocker (ARB), is one of the representative medications for the treatment of hypertension. Cytochrome P450 (CYP) 2C9 is primarily involved in the oxidation of irbesartan. CYP2C9 is highly polymorphic, and genetic polymorphism of this enzyme is the leading cause of significant alterations in the pharmacokinetics of irbesartan. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of irbesartan in different <i>CYP2C9</i> genotypes. The irbesartan PBPK model was established using the PK-Sim<sup>®</sup> software. Our previously reported pharmacogenomic data for irbesartan was leveraged in the development of the PBPK model and collected clinical pharmacokinetic data for irbesartan was used for the validation of the model. Physicochemical and ADME properties of irbesartan were obtained from previously reported data, predicted by the modeling software, or optimized to fit the observed plasma concentration–time profiles. Model evaluation was performed by comparing the predicted plasma concentration–time profiles and pharmacokinetic parameters to the observed results. Predicted plasma concentration–time profiles were visually similar to observed profiles. Predicted AUC<sub>inf</sub> in <i>CYP2C9*1/*3</i> and <i>CYP2C9*1/*13</i> genotypes were increased by 1.54- and 1.62-fold compared to <i>CYP2C9*1/*1</i> genotype, respectively. All fold error values for AUC and C<sub>max</sub> in non-genotyped and <i>CYP2C9</i> genotyped models were within the two-fold error criterion. We properly established the PBPK model of irbesartan in different <i>CYP2C9</i> genotypes. It can be used to predict the pharmacokinetics of irbesartan for personalized pharmacotherapy in individuals of various races, ages, and <i>CYP2C9</i> genotypes.</p></div>","PeriodicalId":8287,"journal":{"name":"Archives of Pharmacal Research","volume":"46 11-12","pages":"939 - 953"},"PeriodicalIF":6.9000,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Physiologically based pharmacokinetic (PBPK) modeling to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes\",\"authors\":\"Chang-Keun Cho, Pureum Kang, Choon-Gon Jang, Seok-Yong Lee, Yun Jeong Lee, Chang-Ik Choi\",\"doi\":\"10.1007/s12272-023-01472-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Irbesartan, a potent and selective angiotensin II type-1 (AT<sub>1</sub>) receptor blocker (ARB), is one of the representative medications for the treatment of hypertension. Cytochrome P450 (CYP) 2C9 is primarily involved in the oxidation of irbesartan. CYP2C9 is highly polymorphic, and genetic polymorphism of this enzyme is the leading cause of significant alterations in the pharmacokinetics of irbesartan. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of irbesartan in different <i>CYP2C9</i> genotypes. The irbesartan PBPK model was established using the PK-Sim<sup>®</sup> software. Our previously reported pharmacogenomic data for irbesartan was leveraged in the development of the PBPK model and collected clinical pharmacokinetic data for irbesartan was used for the validation of the model. Physicochemical and ADME properties of irbesartan were obtained from previously reported data, predicted by the modeling software, or optimized to fit the observed plasma concentration–time profiles. Model evaluation was performed by comparing the predicted plasma concentration–time profiles and pharmacokinetic parameters to the observed results. Predicted plasma concentration–time profiles were visually similar to observed profiles. Predicted AUC<sub>inf</sub> in <i>CYP2C9*1/*3</i> and <i>CYP2C9*1/*13</i> genotypes were increased by 1.54- and 1.62-fold compared to <i>CYP2C9*1/*1</i> genotype, respectively. All fold error values for AUC and C<sub>max</sub> in non-genotyped and <i>CYP2C9</i> genotyped models were within the two-fold error criterion. We properly established the PBPK model of irbesartan in different <i>CYP2C9</i> genotypes. It can be used to predict the pharmacokinetics of irbesartan for personalized pharmacotherapy in individuals of various races, ages, and <i>CYP2C9</i> genotypes.</p></div>\",\"PeriodicalId\":8287,\"journal\":{\"name\":\"Archives of Pharmacal Research\",\"volume\":\"46 11-12\",\"pages\":\"939 - 953\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2023-12-08\",\"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/s12272-023-01472-z\",\"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/s12272-023-01472-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
Physiologically based pharmacokinetic (PBPK) modeling to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes
Irbesartan, a potent and selective angiotensin II type-1 (AT1) receptor blocker (ARB), is one of the representative medications for the treatment of hypertension. Cytochrome P450 (CYP) 2C9 is primarily involved in the oxidation of irbesartan. CYP2C9 is highly polymorphic, and genetic polymorphism of this enzyme is the leading cause of significant alterations in the pharmacokinetics of irbesartan. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes. The irbesartan PBPK model was established using the PK-Sim® software. Our previously reported pharmacogenomic data for irbesartan was leveraged in the development of the PBPK model and collected clinical pharmacokinetic data for irbesartan was used for the validation of the model. Physicochemical and ADME properties of irbesartan were obtained from previously reported data, predicted by the modeling software, or optimized to fit the observed plasma concentration–time profiles. Model evaluation was performed by comparing the predicted plasma concentration–time profiles and pharmacokinetic parameters to the observed results. Predicted plasma concentration–time profiles were visually similar to observed profiles. Predicted AUCinf in CYP2C9*1/*3 and CYP2C9*1/*13 genotypes were increased by 1.54- and 1.62-fold compared to CYP2C9*1/*1 genotype, respectively. All fold error values for AUC and Cmax in non-genotyped and CYP2C9 genotyped models were within the two-fold error criterion. We properly established the PBPK model of irbesartan in different CYP2C9 genotypes. It can be used to predict the pharmacokinetics of irbesartan for personalized pharmacotherapy in individuals of various races, ages, and CYP2C9 genotypes.
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.