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Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data

BACKGROUND AND OBJECTIVES: Model-informed precision dosing (MIPD) frequently uses nonlinear mixed-effects (NLME) models to predict and optimize therapy outcomes based on patient characteristics and therapeutic drug monitoring data. MIPD is indicated for compounds with narrow therapeutic range and co...

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Autores principales: Kluwe, Franziska, Michelet, Robin, Huisinga, Wilhelm, Zeitlinger, Markus, Mikus, Gerd, Kloft, Charlotte
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520167/
https://www.ncbi.nlm.nih.gov/pubmed/37603216
http://dx.doi.org/10.1007/s40262-023-01274-y
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author Kluwe, Franziska
Michelet, Robin
Huisinga, Wilhelm
Zeitlinger, Markus
Mikus, Gerd
Kloft, Charlotte
author_facet Kluwe, Franziska
Michelet, Robin
Huisinga, Wilhelm
Zeitlinger, Markus
Mikus, Gerd
Kloft, Charlotte
author_sort Kluwe, Franziska
collection PubMed
description BACKGROUND AND OBJECTIVES: Model-informed precision dosing (MIPD) frequently uses nonlinear mixed-effects (NLME) models to predict and optimize therapy outcomes based on patient characteristics and therapeutic drug monitoring data. MIPD is indicated for compounds with narrow therapeutic range and complex pharmacokinetics (PK), such as voriconazole, a broad-spectrum antifungal drug for prevention and treatment of invasive fungal infections. To provide guidance and recommendations for evidence-based application of MIPD for voriconazole, this work aimed to (i) externally evaluate and compare the predictive performance of a published so-called ‘hybrid’ model for MIPD (an aggregate model comprising features and prior information from six previously published NLME models) versus two ‘standard’ NLME models of voriconazole, and (ii) investigate strategies and illustrate the clinical impact of Bayesian forecasting for voriconazole. METHODS: A workflow for external evaluation and application of MIPD for voriconazole was implemented. Published voriconazole NLME models were externally evaluated using a comprehensive in-house clinical database comprising nine voriconazole studies and prediction-/simulation-based diagnostics. The NLME models were applied using different Bayesian forecasting strategies to assess the influence of prior observations on model predictivity. RESULTS: The overall best predictive performance was obtained using the aggregate model. However, all NLME models showed only modest predictive performance, suggesting that (i) important PK processes were not sufficiently implemented in the structural submodels, (ii) sources of interindividual variability were not entirely captured, and (iii) interoccasion variability was not adequately accounted for. Predictive performance substantially improved by including the most recent voriconazole observations in MIPD. CONCLUSION: Our results highlight the potential clinical impact of MIPD for voriconazole and indicate the need for a comprehensive (pre-)clinical database as basis for model development and careful external model evaluation for compounds with complex PK before their successful use in MIPD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40262-023-01274-y.
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spelling pubmed-105201672023-09-27 Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data Kluwe, Franziska Michelet, Robin Huisinga, Wilhelm Zeitlinger, Markus Mikus, Gerd Kloft, Charlotte Clin Pharmacokinet Original Research Article BACKGROUND AND OBJECTIVES: Model-informed precision dosing (MIPD) frequently uses nonlinear mixed-effects (NLME) models to predict and optimize therapy outcomes based on patient characteristics and therapeutic drug monitoring data. MIPD is indicated for compounds with narrow therapeutic range and complex pharmacokinetics (PK), such as voriconazole, a broad-spectrum antifungal drug for prevention and treatment of invasive fungal infections. To provide guidance and recommendations for evidence-based application of MIPD for voriconazole, this work aimed to (i) externally evaluate and compare the predictive performance of a published so-called ‘hybrid’ model for MIPD (an aggregate model comprising features and prior information from six previously published NLME models) versus two ‘standard’ NLME models of voriconazole, and (ii) investigate strategies and illustrate the clinical impact of Bayesian forecasting for voriconazole. METHODS: A workflow for external evaluation and application of MIPD for voriconazole was implemented. Published voriconazole NLME models were externally evaluated using a comprehensive in-house clinical database comprising nine voriconazole studies and prediction-/simulation-based diagnostics. The NLME models were applied using different Bayesian forecasting strategies to assess the influence of prior observations on model predictivity. RESULTS: The overall best predictive performance was obtained using the aggregate model. However, all NLME models showed only modest predictive performance, suggesting that (i) important PK processes were not sufficiently implemented in the structural submodels, (ii) sources of interindividual variability were not entirely captured, and (iii) interoccasion variability was not adequately accounted for. Predictive performance substantially improved by including the most recent voriconazole observations in MIPD. CONCLUSION: Our results highlight the potential clinical impact of MIPD for voriconazole and indicate the need for a comprehensive (pre-)clinical database as basis for model development and careful external model evaluation for compounds with complex PK before their successful use in MIPD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40262-023-01274-y. Springer International Publishing 2023-08-21 2023 /pmc/articles/PMC10520167/ /pubmed/37603216 http://dx.doi.org/10.1007/s40262-023-01274-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial 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-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research Article
Kluwe, Franziska
Michelet, Robin
Huisinga, Wilhelm
Zeitlinger, Markus
Mikus, Gerd
Kloft, Charlotte
Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
title Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
title_full Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
title_fullStr Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
title_full_unstemmed Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
title_short Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
title_sort towards model-informed precision dosing of voriconazole: challenging published voriconazole nonlinear mixed-effects models with real-world clinical data
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520167/
https://www.ncbi.nlm.nih.gov/pubmed/37603216
http://dx.doi.org/10.1007/s40262-023-01274-y
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