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Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions

The immunosuppressant and narrow therapeutic index drug tacrolimus is metabolized mainly via cytochrome P450 (CYP) 3A4 and CYP3A5. For its pharmacokinetics (PK), high inter‐ and intra‐individual variability can be observed. Underlying causes include the effect of food intake on tacrolimus absorption...

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Autores principales: Loer, Helena Leonie Hanae, Feick, Denise, Rüdesheim, Simeon, Selzer, Dominik, Schwab, Matthias, Teutonico, Donato, Frechen, Sebastian, van der Lee, Maaike, Moes, Dirk Jan A. R., Swen, Jesse J., Lehr, Thorsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196430/
https://www.ncbi.nlm.nih.gov/pubmed/36808892
http://dx.doi.org/10.1002/psp4.12946
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author Loer, Helena Leonie Hanae
Feick, Denise
Rüdesheim, Simeon
Selzer, Dominik
Schwab, Matthias
Teutonico, Donato
Frechen, Sebastian
van der Lee, Maaike
Moes, Dirk Jan A. R.
Swen, Jesse J.
Lehr, Thorsten
author_facet Loer, Helena Leonie Hanae
Feick, Denise
Rüdesheim, Simeon
Selzer, Dominik
Schwab, Matthias
Teutonico, Donato
Frechen, Sebastian
van der Lee, Maaike
Moes, Dirk Jan A. R.
Swen, Jesse J.
Lehr, Thorsten
author_sort Loer, Helena Leonie Hanae
collection PubMed
description The immunosuppressant and narrow therapeutic index drug tacrolimus is metabolized mainly via cytochrome P450 (CYP) 3A4 and CYP3A5. For its pharmacokinetics (PK), high inter‐ and intra‐individual variability can be observed. Underlying causes include the effect of food intake on tacrolimus absorption as well as genetic polymorphism in the CYP3A5 gene. Furthermore, tacrolimus is highly susceptible to drug–drug interactions, acting as a victim drug when coadministered with CYP3A perpetrators. This work describes the development of a whole‐body physiologically based pharmacokinetic model for tacrolimus as well as its application for investigation and prediction of (i) the impact of food intake on tacrolimus PK (food–drug interactions [FDIs]) and (ii) drug–drug(−gene) interactions (DD[G]Is) involving the CYP3A perpetrator drugs voriconazole, itraconazole, and rifampicin. The model was built in PK‐Sim® Version 10 using a total of 37 whole blood concentration–time profiles of tacrolimus (training and test) compiled from 911 healthy individuals covering the administration of tacrolimus as intravenous infusions as well as immediate‐release and extended‐release capsules. Metabolism was incorporated via CYP3A4 and CYP3A5, with varying activities implemented for different CYP3A5 genotypes and study populations. The good predictive model performance is demonstrated for the examined food effect studies with 6/6 predicted FDI area under the curve determined between first and last concentration measurements (AUC(last)) and 6/6 predicted FDI maximum whole blood concentration (C(max)) ratios within twofold of the respective observed ratios. In addition, 7/7 predicted DD(G)I AUC(last) and 6/7 predicted DD(G)I C(max) ratios were within twofold of their observed values. Potential applications of the final model include model‐informed drug discovery and development or the support of model‐informed precision dosing.
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spelling pubmed-101964302023-05-20 Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions Loer, Helena Leonie Hanae Feick, Denise Rüdesheim, Simeon Selzer, Dominik Schwab, Matthias Teutonico, Donato Frechen, Sebastian van der Lee, Maaike Moes, Dirk Jan A. R. Swen, Jesse J. Lehr, Thorsten CPT Pharmacometrics Syst Pharmacol Research The immunosuppressant and narrow therapeutic index drug tacrolimus is metabolized mainly via cytochrome P450 (CYP) 3A4 and CYP3A5. For its pharmacokinetics (PK), high inter‐ and intra‐individual variability can be observed. Underlying causes include the effect of food intake on tacrolimus absorption as well as genetic polymorphism in the CYP3A5 gene. Furthermore, tacrolimus is highly susceptible to drug–drug interactions, acting as a victim drug when coadministered with CYP3A perpetrators. This work describes the development of a whole‐body physiologically based pharmacokinetic model for tacrolimus as well as its application for investigation and prediction of (i) the impact of food intake on tacrolimus PK (food–drug interactions [FDIs]) and (ii) drug–drug(−gene) interactions (DD[G]Is) involving the CYP3A perpetrator drugs voriconazole, itraconazole, and rifampicin. The model was built in PK‐Sim® Version 10 using a total of 37 whole blood concentration–time profiles of tacrolimus (training and test) compiled from 911 healthy individuals covering the administration of tacrolimus as intravenous infusions as well as immediate‐release and extended‐release capsules. Metabolism was incorporated via CYP3A4 and CYP3A5, with varying activities implemented for different CYP3A5 genotypes and study populations. The good predictive model performance is demonstrated for the examined food effect studies with 6/6 predicted FDI area under the curve determined between first and last concentration measurements (AUC(last)) and 6/6 predicted FDI maximum whole blood concentration (C(max)) ratios within twofold of the respective observed ratios. In addition, 7/7 predicted DD(G)I AUC(last) and 6/7 predicted DD(G)I C(max) ratios were within twofold of their observed values. Potential applications of the final model include model‐informed drug discovery and development or the support of model‐informed precision dosing. John Wiley and Sons Inc. 2023-03-10 /pmc/articles/PMC10196430/ /pubmed/36808892 http://dx.doi.org/10.1002/psp4.12946 Text en © 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology 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
Loer, Helena Leonie Hanae
Feick, Denise
Rüdesheim, Simeon
Selzer, Dominik
Schwab, Matthias
Teutonico, Donato
Frechen, Sebastian
van der Lee, Maaike
Moes, Dirk Jan A. R.
Swen, Jesse J.
Lehr, Thorsten
Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions
title Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions
title_full Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions
title_fullStr Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions
title_full_unstemmed Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions
title_short Physiologically based pharmacokinetic modeling of tacrolimus for food–drug and CYP3A drug–drug–gene interaction predictions
title_sort physiologically based pharmacokinetic modeling of tacrolimus for food–drug and cyp3a drug–drug–gene interaction predictions
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196430/
https://www.ncbi.nlm.nih.gov/pubmed/36808892
http://dx.doi.org/10.1002/psp4.12946
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