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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
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.
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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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