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Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions
Eliglustat is a glucosylceramide synthase inhibitor indicated as a long‐term substrate reduction therapy for adults with type 1 Gaucher disease, a lysosomal rare disease. It is primarily metabolized by cytochrome P450 2D6 (CYP2D6), and variants in the gene encoding this enzyme are important determin...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828395/ https://www.ncbi.nlm.nih.gov/pubmed/36056771 http://dx.doi.org/10.1002/cpt.2738 |
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author | Sahasrabudhe, Siddhee A. Cheng, Shen Al‐Kofahi, Mahmoud Jarnes, Jeanine R. Weinreb, Neal J. Kartha, Reena V. |
author_facet | Sahasrabudhe, Siddhee A. Cheng, Shen Al‐Kofahi, Mahmoud Jarnes, Jeanine R. Weinreb, Neal J. Kartha, Reena V. |
author_sort | Sahasrabudhe, Siddhee A. |
collection | PubMed |
description | Eliglustat is a glucosylceramide synthase inhibitor indicated as a long‐term substrate reduction therapy for adults with type 1 Gaucher disease, a lysosomal rare disease. It is primarily metabolized by cytochrome P450 2D6 (CYP2D6), and variants in the gene encoding this enzyme are important determinants of eliglustat pharmacokinetics (PK) and drug–drug interactions (DDIs). The existing drug label addresses the DDIs to some extent but has omitted scenarios where both metabolizing CYPs (2D6 and 3A4) are mildly or moderately inhibited. The objectives of this study were (i) to develop and validate an eliglustat physiologically‐based pharmacokinetic (PBPK) model with and without drug interactions, (ii) to simulate untested DDI scenarios, and (iii) to explore potential dosing flexibility using lower dose strength of eliglustat (commercially not available). PK data from healthy adults receiving eliglustat with or without interacting drugs were obtained from literature and used for the PBPK model development and validation. The model‐predicted single‐dose and steady‐state maximum concentration (C(max)) and area under the concentration‐time curve (AUC) of eliglustat were within 50–150% of the observed values when eliglustat was administered alone or coadministered with ketoconazole or paroxetine. Then as model‐based simulations, we illustrated eliglustat exposure as a victim of interaction when coadministered with fluvoxamine following the US Food and Drug Administration (FDA) dosing recommendations. Second, we showed that with lower eliglustat doses (21 mg, 42 mg once daily) the exposure in participants of intermediate and poor metabolizer phenotypes was within the outlined safety margin (C(max) <250 ng/mL) when eliglustat was administered with ketoconazole, where the current recommendation is a contraindication of coadministration (84 mg). The present study demonstrated that patients with CYP2D6 deficiency may benefit from lower doses of eliglustat. |
format | Online Article Text |
id | pubmed-9828395 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98283952023-01-11 Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions Sahasrabudhe, Siddhee A. Cheng, Shen Al‐Kofahi, Mahmoud Jarnes, Jeanine R. Weinreb, Neal J. Kartha, Reena V. Clin Pharmacol Ther Research Eliglustat is a glucosylceramide synthase inhibitor indicated as a long‐term substrate reduction therapy for adults with type 1 Gaucher disease, a lysosomal rare disease. It is primarily metabolized by cytochrome P450 2D6 (CYP2D6), and variants in the gene encoding this enzyme are important determinants of eliglustat pharmacokinetics (PK) and drug–drug interactions (DDIs). The existing drug label addresses the DDIs to some extent but has omitted scenarios where both metabolizing CYPs (2D6 and 3A4) are mildly or moderately inhibited. The objectives of this study were (i) to develop and validate an eliglustat physiologically‐based pharmacokinetic (PBPK) model with and without drug interactions, (ii) to simulate untested DDI scenarios, and (iii) to explore potential dosing flexibility using lower dose strength of eliglustat (commercially not available). PK data from healthy adults receiving eliglustat with or without interacting drugs were obtained from literature and used for the PBPK model development and validation. The model‐predicted single‐dose and steady‐state maximum concentration (C(max)) and area under the concentration‐time curve (AUC) of eliglustat were within 50–150% of the observed values when eliglustat was administered alone or coadministered with ketoconazole or paroxetine. Then as model‐based simulations, we illustrated eliglustat exposure as a victim of interaction when coadministered with fluvoxamine following the US Food and Drug Administration (FDA) dosing recommendations. Second, we showed that with lower eliglustat doses (21 mg, 42 mg once daily) the exposure in participants of intermediate and poor metabolizer phenotypes was within the outlined safety margin (C(max) <250 ng/mL) when eliglustat was administered with ketoconazole, where the current recommendation is a contraindication of coadministration (84 mg). The present study demonstrated that patients with CYP2D6 deficiency may benefit from lower doses of eliglustat. John Wiley and Sons Inc. 2022-09-30 2022-12 /pmc/articles/PMC9828395/ /pubmed/36056771 http://dx.doi.org/10.1002/cpt.2738 Text en © 2022 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://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 | Research Sahasrabudhe, Siddhee A. Cheng, Shen Al‐Kofahi, Mahmoud Jarnes, Jeanine R. Weinreb, Neal J. Kartha, Reena V. Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions |
title | Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions |
title_full | Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions |
title_fullStr | Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions |
title_full_unstemmed | Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions |
title_short | Physiologically‐Based Pharmacokinetic Model Development, Validation, and Application for Prediction of Eliglustat Drug–Drug Interactions |
title_sort | physiologically‐based pharmacokinetic model development, validation, and application for prediction of eliglustat drug–drug interactions |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828395/ https://www.ncbi.nlm.nih.gov/pubmed/36056771 http://dx.doi.org/10.1002/cpt.2738 |
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