dc.contributor.author
Kluwe, Franziska
dc.contributor.author
Michelet, Robin
dc.contributor.author
Huisinga, Wilhelm
dc.contributor.author
Zeitlinger, Markus
dc.contributor.author
Mikus, Gerd
dc.contributor.author
Kloft, Charlotte
dc.date.accessioned
2023-10-09T08:41:50Z
dc.date.available
2023-10-09T08:41:50Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/40573
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-40294
dc.description.abstract
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.
en
dc.format.extent
17 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by-nc/4.0/
dc.subject
model-informed precision dosing
en
dc.subject
voriconazole
en
dc.subject
nonlinear mixed-effects models
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::615 Pharmakologie, Therapeutik
dc.title
Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1007/s40262-023-01274-y
dcterms.bibliographicCitation.journaltitle
Clinical Pharmacokinetics
dcterms.bibliographicCitation.number
10
dcterms.bibliographicCitation.pagestart
1461
dcterms.bibliographicCitation.pageend
1477
dcterms.bibliographicCitation.volume
62
dcterms.bibliographicCitation.url
https://doi.org/10.1007/s40262-023-01274-y
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Pharmazie
refubium.funding
Springer Nature DEAL
refubium.note.author
Die Publikation wurde aus Open Access Publikationsgeldern der Freien Universität Berlin gefördert.
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1179-1926