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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 stream...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society for Clinical Pharmacology and Therapeutics
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979758/ https://www.ncbi.nlm.nih.gov/pubmed/35419310 http://dx.doi.org/10.12793/tcp.2022.30.e6 |
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author | Choi, Suein Yim, Dong-Seok Bae, Soo Hyeon |
author_facet | Choi, Suein Yim, Dong-Seok Bae, Soo Hyeon |
author_sort | Choi, Suein |
collection | PubMed |
description | 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 C(max), dynamic models including physiologically-based pharmacokinetic models take into account changes in in vivo concentrations and metabolizing enzyme levels over time. |
format | Online Article Text |
id | pubmed-8979758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Korean Society for Clinical Pharmacology and Therapeutics |
record_format | MEDLINE/PubMed |
spelling | pubmed-89797582022-04-12 Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information Choi, Suein Yim, Dong-Seok Bae, Soo Hyeon Transl Clin Pharmacol Tutorial 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 C(max), dynamic models including physiologically-based pharmacokinetic models take into account changes in in vivo concentrations and metabolizing enzyme levels over time. Korean Society for Clinical Pharmacology and Therapeutics 2022-03 2022-03-21 /pmc/articles/PMC8979758/ /pubmed/35419310 http://dx.doi.org/10.12793/tcp.2022.30.e6 Text en Copyright © 2022 Translational and Clinical Pharmacology https://creativecommons.org/licenses/by-nc/4.0/It is identical to the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/). |
spellingShingle | Tutorial Choi, Suein Yim, Dong-Seok Bae, Soo Hyeon Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information |
title | Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information |
title_full | Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information |
title_fullStr | Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information |
title_full_unstemmed | Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information |
title_short | Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information |
title_sort | prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information |
topic | Tutorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979758/ https://www.ncbi.nlm.nih.gov/pubmed/35419310 http://dx.doi.org/10.12793/tcp.2022.30.e6 |
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