{"title":"利用体外信息预测代谢酶介导的临床药物相互作用","authors":"Suein Choi, D. Yim, S. Bae","doi":"10.12793/tcp.2022.30.e6","DOIUrl":null,"url":null,"abstract":"Evaluation of drug interactions is an essential step in the new drug development process. Regulatory agencies, including U.S. Food and Drug Administrations and European Medicines Agency, have been published documents containing guidelines to evaluate potential drug interactions. Here, we have streamlined in vitro experiments to assess metabolizing enzyme-mediated drug interactions and provided an overview of the overall process to evaluate potential clinical drug interactions using in vitro data. An experimental approach is presented when an investigational drug (ID) is either a victim or a perpetrator, respectively, and the general procedure to obtain in vitro drug interaction parameters is also described. With the in vitro inhibitory and/or inductive parameters of the ID, basic, static, and/or dynamic models were used to evaluate potential clinical drug interactions. In addition to basic and static models which assume the most conservative conditions, such as the concentration of perpetrators as Cmax, dynamic models including physiologically-based pharmacokinetic models take into account changes in in vivo concentrations and metabolizing enzyme levels over time.","PeriodicalId":23288,"journal":{"name":"Translational and Clinical Pharmacology","volume":"30 1","pages":"1 - 12"},"PeriodicalIF":1.1000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information\",\"authors\":\"Suein Choi, D. Yim, S. Bae\",\"doi\":\"10.12793/tcp.2022.30.e6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evaluation of drug interactions is an essential step in the new drug development process. Regulatory agencies, including U.S. Food and Drug Administrations and European Medicines Agency, have been published documents containing guidelines to evaluate potential drug interactions. Here, we have streamlined in vitro experiments to assess metabolizing enzyme-mediated drug interactions and provided an overview of the overall process to evaluate potential clinical drug interactions using in vitro data. An experimental approach is presented when an investigational drug (ID) is either a victim or a perpetrator, respectively, and the general procedure to obtain in vitro drug interaction parameters is also described. With the in vitro inhibitory and/or inductive parameters of the ID, basic, static, and/or dynamic models were used to evaluate potential clinical drug interactions. In addition to basic and static models which assume the most conservative conditions, such as the concentration of perpetrators as Cmax, dynamic models including physiologically-based pharmacokinetic models take into account changes in in vivo concentrations and metabolizing enzyme levels over time.\",\"PeriodicalId\":23288,\"journal\":{\"name\":\"Translational and Clinical Pharmacology\",\"volume\":\"30 1\",\"pages\":\"1 - 12\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational and Clinical Pharmacology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12793/tcp.2022.30.e6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational and Clinical Pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12793/tcp.2022.30.e6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information
Evaluation of drug interactions is an essential step in the new drug development process. Regulatory agencies, including U.S. Food and Drug Administrations and European Medicines Agency, have been published documents containing guidelines to evaluate potential drug interactions. Here, we have streamlined in vitro experiments to assess metabolizing enzyme-mediated drug interactions and provided an overview of the overall process to evaluate potential clinical drug interactions using in vitro data. An experimental approach is presented when an investigational drug (ID) is either a victim or a perpetrator, respectively, and the general procedure to obtain in vitro drug interaction parameters is also described. With the in vitro inhibitory and/or inductive parameters of the ID, basic, static, and/or dynamic models were used to evaluate potential clinical drug interactions. In addition to basic and static models which assume the most conservative conditions, such as the concentration of perpetrators as Cmax, dynamic models including physiologically-based pharmacokinetic models take into account changes in in vivo concentrations and metabolizing enzyme levels over time.
期刊介绍:
Translational and Clinical Pharmacology (Transl Clin Pharmacol, TCP) is the official journal of the Korean Society for Clinical Pharmacology and Therapeutics (KSCPT). TCP is an interdisciplinary journal devoted to the dissemination of knowledge relating to all aspects of translational and clinical pharmacology. The categories for publication include pharmacokinetics (PK) and drug disposition, drug metabolism, pharmacodynamics (PD), clinical trials and design issues, pharmacogenomics and pharmacogenetics, pharmacometrics, pharmacoepidemiology, pharmacovigilence, and human pharmacology. Studies involving animal models, pharmacological characterization, and clinical trials are appropriate for consideration.