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Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions

PURPOSE: To build a physiologically based pharmacokinetic (PBPK) model of the clinical OATP1B1/OATP1B3/BCRP victim drug rosuvastatin for the investigation and prediction of its transporter-mediated drug-drug interactions (DDIs). METHODS: The Rosuvastatin model was developed using the open-source PBP...

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Autores principales: Hanke, Nina, Gómez-Mantilla, José David, Ishiguro, Naoki, Stopfer, Peter, Nock, Valerie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602162/
https://www.ncbi.nlm.nih.gov/pubmed/34664206
http://dx.doi.org/10.1007/s11095-021-03109-6
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author Hanke, Nina
Gómez-Mantilla, José David
Ishiguro, Naoki
Stopfer, Peter
Nock, Valerie
author_facet Hanke, Nina
Gómez-Mantilla, José David
Ishiguro, Naoki
Stopfer, Peter
Nock, Valerie
author_sort Hanke, Nina
collection PubMed
description PURPOSE: To build a physiologically based pharmacokinetic (PBPK) model of the clinical OATP1B1/OATP1B3/BCRP victim drug rosuvastatin for the investigation and prediction of its transporter-mediated drug-drug interactions (DDIs). METHODS: The Rosuvastatin model was developed using the open-source PBPK software PK-Sim®, following a middle-out approach. 42 clinical studies (dosing range 0.002–80.0 mg), providing rosuvastatin plasma, urine and feces data, positron emission tomography (PET) measurements of tissue concentrations and 7 different rosuvastatin DDI studies with rifampicin, gemfibrozil and probenecid as the perpetrator drugs, were included to build and qualify the model. RESULTS: The carefully developed and thoroughly evaluated model adequately describes the analyzed clinical data, including blood, liver, feces and urine measurements. The processes implemented to describe the rosuvastatin pharmacokinetics and DDIs are active uptake by OATP2B1, OATP1B1/OATP1B3 and OAT3, active efflux by BCRP and Pgp, metabolism by CYP2C9 and passive glomerular filtration. The available clinical rifampicin, gemfibrozil and probenecid DDI studies were modeled using in vitro inhibition constants without adjustments. The good prediction of DDIs was demonstrated by simulated rosuvastatin plasma profiles, DDI AUC(last) ratios (AUC(last) during DDI/AUC(last) without co-administration) and DDI C(max) ratios (C(max) during DDI/C(max) without co-administration), with all simulated DDI ratios within 1.6-fold of the observed values. CONCLUSIONS: A whole-body PBPK model of rosuvastatin was built and qualified for the prediction of rosuvastatin pharmacokinetics and transporter-mediated DDIs. The model is freely available in the Open Systems Pharmacology model repository, to support future investigations of rosuvastatin pharmacokinetics, rosuvastatin therapy and DDI studies during model-informed drug discovery and development (MID3). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11095-021-03109-6.
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spelling pubmed-86021622021-12-03 Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions Hanke, Nina Gómez-Mantilla, José David Ishiguro, Naoki Stopfer, Peter Nock, Valerie Pharm Res Research Paper PURPOSE: To build a physiologically based pharmacokinetic (PBPK) model of the clinical OATP1B1/OATP1B3/BCRP victim drug rosuvastatin for the investigation and prediction of its transporter-mediated drug-drug interactions (DDIs). METHODS: The Rosuvastatin model was developed using the open-source PBPK software PK-Sim®, following a middle-out approach. 42 clinical studies (dosing range 0.002–80.0 mg), providing rosuvastatin plasma, urine and feces data, positron emission tomography (PET) measurements of tissue concentrations and 7 different rosuvastatin DDI studies with rifampicin, gemfibrozil and probenecid as the perpetrator drugs, were included to build and qualify the model. RESULTS: The carefully developed and thoroughly evaluated model adequately describes the analyzed clinical data, including blood, liver, feces and urine measurements. The processes implemented to describe the rosuvastatin pharmacokinetics and DDIs are active uptake by OATP2B1, OATP1B1/OATP1B3 and OAT3, active efflux by BCRP and Pgp, metabolism by CYP2C9 and passive glomerular filtration. The available clinical rifampicin, gemfibrozil and probenecid DDI studies were modeled using in vitro inhibition constants without adjustments. The good prediction of DDIs was demonstrated by simulated rosuvastatin plasma profiles, DDI AUC(last) ratios (AUC(last) during DDI/AUC(last) without co-administration) and DDI C(max) ratios (C(max) during DDI/C(max) without co-administration), with all simulated DDI ratios within 1.6-fold of the observed values. CONCLUSIONS: A whole-body PBPK model of rosuvastatin was built and qualified for the prediction of rosuvastatin pharmacokinetics and transporter-mediated DDIs. The model is freely available in the Open Systems Pharmacology model repository, to support future investigations of rosuvastatin pharmacokinetics, rosuvastatin therapy and DDI studies during model-informed drug discovery and development (MID3). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11095-021-03109-6. Springer US 2021-10-18 2021 /pmc/articles/PMC8602162/ /pubmed/34664206 http://dx.doi.org/10.1007/s11095-021-03109-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Paper
Hanke, Nina
Gómez-Mantilla, José David
Ishiguro, Naoki
Stopfer, Peter
Nock, Valerie
Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions
title Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions
title_full Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions
title_fullStr Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions
title_full_unstemmed Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions
title_short Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions
title_sort physiologically based pharmacokinetic modeling of rosuvastatin to predict transporter-mediated drug-drug interactions
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602162/
https://www.ncbi.nlm.nih.gov/pubmed/34664206
http://dx.doi.org/10.1007/s11095-021-03109-6
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