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Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling
Naloxegol, a peripherally acting μ‐opioid receptor antagonist for the treatment of opioid‐induced constipation, is a substrate for cytochrome P450 (CYP) 3A4/3A5 and the P‐glycoprotein (P‐gp) transporter. By integrating in silico, preclinical, and clinical pharmacokinetic (PK) findings, minimal and f...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879473/ https://www.ncbi.nlm.nih.gov/pubmed/27299937 http://dx.doi.org/10.1002/psp4.12070 |
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author | Zhou, D Bui, K Sostek, M Al‐Huniti, N |
author_facet | Zhou, D Bui, K Sostek, M Al‐Huniti, N |
author_sort | Zhou, D |
collection | PubMed |
description | Naloxegol, a peripherally acting μ‐opioid receptor antagonist for the treatment of opioid‐induced constipation, is a substrate for cytochrome P450 (CYP) 3A4/3A5 and the P‐glycoprotein (P‐gp) transporter. By integrating in silico, preclinical, and clinical pharmacokinetic (PK) findings, minimal and full physiologically based pharmacokinetic (PBPK) models were developed to predict the drug‐drug interaction (DDI) potential for naloxegol. The models reasonably predicted the observed changes in naloxegol exposure with ketoconazole (increase of 13.1‐fold predicted vs. 12.9‐fold observed), diltiazem (increase of 2.8‐fold predicted vs. 3.4‐fold observed), rifampin (reduction of 76% predicted vs. 89% observed), and quinidine (increase of 1.2‐fold predicted vs. 1.4‐fold observed). The moderate CYP3A4 inducer efavirenz was predicted to reduce naloxegol exposure by ∼50%, whereas weak CYP3A inhibitors were predicted to minimally affect exposure. In summary, the PBPK models reasonably estimated interactions with various CYP3A modulators and can be used to guide dosing in clinical practice when naloxegol is coadministered with such agents. |
format | Online Article Text |
id | pubmed-4879473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-48794732016-06-21 Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling Zhou, D Bui, K Sostek, M Al‐Huniti, N CPT Pharmacometrics Syst Pharmacol Original Articles Naloxegol, a peripherally acting μ‐opioid receptor antagonist for the treatment of opioid‐induced constipation, is a substrate for cytochrome P450 (CYP) 3A4/3A5 and the P‐glycoprotein (P‐gp) transporter. By integrating in silico, preclinical, and clinical pharmacokinetic (PK) findings, minimal and full physiologically based pharmacokinetic (PBPK) models were developed to predict the drug‐drug interaction (DDI) potential for naloxegol. The models reasonably predicted the observed changes in naloxegol exposure with ketoconazole (increase of 13.1‐fold predicted vs. 12.9‐fold observed), diltiazem (increase of 2.8‐fold predicted vs. 3.4‐fold observed), rifampin (reduction of 76% predicted vs. 89% observed), and quinidine (increase of 1.2‐fold predicted vs. 1.4‐fold observed). The moderate CYP3A4 inducer efavirenz was predicted to reduce naloxegol exposure by ∼50%, whereas weak CYP3A inhibitors were predicted to minimally affect exposure. In summary, the PBPK models reasonably estimated interactions with various CYP3A modulators and can be used to guide dosing in clinical practice when naloxegol is coadministered with such agents. John Wiley and Sons Inc. 2016-04-16 2016-05 /pmc/articles/PMC4879473/ /pubmed/27299937 http://dx.doi.org/10.1002/psp4.12070 Text en © 2016 The Authors CPT: Pharmacometrics & Systems Pharmacology 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 Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Zhou, D Bui, K Sostek, M Al‐Huniti, N Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling |
title | Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling |
title_full | Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling |
title_fullStr | Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling |
title_full_unstemmed | Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling |
title_short | Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling |
title_sort | simulation and prediction of the drug‐drug interaction potential of naloxegol by physiologically based pharmacokinetic modeling |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879473/ https://www.ncbi.nlm.nih.gov/pubmed/27299937 http://dx.doi.org/10.1002/psp4.12070 |
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