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Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations
Physiologically‐based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug–drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time‐dependent inhibition, enzyme indu...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232864/ https://www.ncbi.nlm.nih.gov/pubmed/31628859 http://dx.doi.org/10.1002/cpt.1693 |
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author | Taskar, Kunal S. Pilla Reddy, Venkatesh Burt, Howard Posada, Maria M. Varma, Manthena Zheng, Ming Ullah, Mohammed Emami Riedmaier, Arian Umehara, Ken‐ichi Snoeys, Jan Nakakariya, Masanori Chu, Xiaoyan Beneton, Maud Chen, Yuan Huth, Felix Narayanan, Rangaraj Mukherjee, Dwaipayan Dixit, Vaishali Sugiyama, Yuichi Neuhoff, Sibylle |
author_facet | Taskar, Kunal S. Pilla Reddy, Venkatesh Burt, Howard Posada, Maria M. Varma, Manthena Zheng, Ming Ullah, Mohammed Emami Riedmaier, Arian Umehara, Ken‐ichi Snoeys, Jan Nakakariya, Masanori Chu, Xiaoyan Beneton, Maud Chen, Yuan Huth, Felix Narayanan, Rangaraj Mukherjee, Dwaipayan Dixit, Vaishali Sugiyama, Yuichi Neuhoff, Sibylle |
author_sort | Taskar, Kunal S. |
collection | PubMed |
description | Physiologically‐based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug–drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time‐dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome‐P450‐mediated DDIs and is routinely used. However, the application of PBPK for transporter‐mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling. |
format | Online Article Text |
id | pubmed-7232864 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72328642020-05-19 Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations Taskar, Kunal S. Pilla Reddy, Venkatesh Burt, Howard Posada, Maria M. Varma, Manthena Zheng, Ming Ullah, Mohammed Emami Riedmaier, Arian Umehara, Ken‐ichi Snoeys, Jan Nakakariya, Masanori Chu, Xiaoyan Beneton, Maud Chen, Yuan Huth, Felix Narayanan, Rangaraj Mukherjee, Dwaipayan Dixit, Vaishali Sugiyama, Yuichi Neuhoff, Sibylle Clin Pharmacol Ther Reviews Physiologically‐based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug–drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time‐dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome‐P450‐mediated DDIs and is routinely used. However, the application of PBPK for transporter‐mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling. John Wiley and Sons Inc. 2019-12-31 2020-05 /pmc/articles/PMC7232864/ /pubmed/31628859 http://dx.doi.org/10.1002/cpt.1693 Text en © 2019 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Reviews Taskar, Kunal S. Pilla Reddy, Venkatesh Burt, Howard Posada, Maria M. Varma, Manthena Zheng, Ming Ullah, Mohammed Emami Riedmaier, Arian Umehara, Ken‐ichi Snoeys, Jan Nakakariya, Masanori Chu, Xiaoyan Beneton, Maud Chen, Yuan Huth, Felix Narayanan, Rangaraj Mukherjee, Dwaipayan Dixit, Vaishali Sugiyama, Yuichi Neuhoff, Sibylle Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations |
title | Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations |
title_full | Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations |
title_fullStr | Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations |
title_full_unstemmed | Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations |
title_short | Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations |
title_sort | physiologically‐based pharmacokinetic models for evaluating membrane transporter mediated drug–drug interactions: current capabilities, case studies, future opportunities, and recommendations |
topic | Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232864/ https://www.ncbi.nlm.nih.gov/pubmed/31628859 http://dx.doi.org/10.1002/cpt.1693 |
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