Personalized Antifungal Therapy Through Model-Informed Precision Dosing of Posaconazole.


Journal

Clinical pharmacokinetics
ISSN: 1179-1926
Titre abrégé: Clin Pharmacokinet
Pays: Switzerland
ID NLM: 7606849

Informations de publication

Date de publication:
26 Mar 2024
Historique:
accepted: 13 02 2024
medline: 27 3 2024
pubmed: 27 3 2024
entrez: 27 3 2024
Statut: aheadofprint

Résumé

Posaconazole is a pharmacotherapeutic pillar for prophylaxis and treatment of invasive fungal diseases. Dose individualization is of utmost importance as achieving adequate antifungal exposure is associated with improved outcome. This study aimed to select and evaluate a model-informed precision dosing strategy for posaconazole. Available population pharmacokinetic models for posaconazole administered as a solid oral tablet were extracted from the literature and evaluated using data from a previously published prospective study combined with data collected during routine clinical practice. External evaluation and selection of the most accurate and precise model was based on graphical goodness-of-fit and predictive performance. Measures for bias and imprecision included mean percentage error (MPE) and normalized relative root mean squared error (NRMSE), respectively. Subsequently, the best-performing model was evaluated for its a posteriori fit-for-purpose and its suitability in a limited sampling strategy. Seven posaconazole models were evaluated using 764 posaconazole plasma concentrations from 143 patients. Multiple models showed adequate predictive performance illustrated by acceptable goodness-of-fit and MPE and NRMSE below ± 10% and ± 25%, respectively. In the fit-for-purpose analysis, the selected model showed adequate a posteriori predictive performance. Bias and imprecision were lowest in the presence of two prior measurements. Additionally, this model showed to be useful in a limited sampling strategy as it adequately predicted total posaconazole exposure from one (non-)trough concentration. We validated an MIPD strategy for posaconazole for its fit-for-purpose. Thereby, this study is an important first step towards MIPD-supported posaconazole dosage optimization with the goal to improve antifungal treatment in clinical practice.

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
Posaconazole is a pharmacotherapeutic pillar for prophylaxis and treatment of invasive fungal diseases. Dose individualization is of utmost importance as achieving adequate antifungal exposure is associated with improved outcome. This study aimed to select and evaluate a model-informed precision dosing strategy for posaconazole.
METHODS METHODS
Available population pharmacokinetic models for posaconazole administered as a solid oral tablet were extracted from the literature and evaluated using data from a previously published prospective study combined with data collected during routine clinical practice. External evaluation and selection of the most accurate and precise model was based on graphical goodness-of-fit and predictive performance. Measures for bias and imprecision included mean percentage error (MPE) and normalized relative root mean squared error (NRMSE), respectively. Subsequently, the best-performing model was evaluated for its a posteriori fit-for-purpose and its suitability in a limited sampling strategy.
RESULTS RESULTS
Seven posaconazole models were evaluated using 764 posaconazole plasma concentrations from 143 patients. Multiple models showed adequate predictive performance illustrated by acceptable goodness-of-fit and MPE and NRMSE below ± 10% and ± 25%, respectively. In the fit-for-purpose analysis, the selected model showed adequate a posteriori predictive performance. Bias and imprecision were lowest in the presence of two prior measurements. Additionally, this model showed to be useful in a limited sampling strategy as it adequately predicted total posaconazole exposure from one (non-)trough concentration.
CONCLUSION CONCLUSIONS
We validated an MIPD strategy for posaconazole for its fit-for-purpose. Thereby, this study is an important first step towards MIPD-supported posaconazole dosage optimization with the goal to improve antifungal treatment in clinical practice.

Identifiants

pubmed: 38532053
doi: 10.1007/s40262-024-01361-8
pii: 10.1007/s40262-024-01361-8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. The Author(s).

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Auteurs

Anouk M E Jansen (AME)

Department of Pharmacy, Radboud University Medical Center, Radboud Institute for Medical Innovation, Nijmegen, The Netherlands. anouk.me.jansen@radboudumc.nl.
Center of Expertise in Mycology, Radboud University Medical Center/Canisius Wilhelmina Ziekenhuis, Nijmegen, The Netherlands. anouk.me.jansen@radboudumc.nl.

Kim Snijdelaar (K)

Department of Pharmacy, Radboud University Medical Center, Radboud Institute for Medical Innovation, Nijmegen, The Netherlands.

Ron J Keizer (RJ)

InsightRX, San Francisco, CA, USA.

Isabel Spriet (I)

Department of Pharmacy, University Hospitals Leuven, Leuven, Belgium.
Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.

Erwin Dreesen (E)

Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.

Roger J M Brüggemann (RJM)

Department of Pharmacy, Radboud University Medical Center, Radboud Institute for Medical Innovation, Nijmegen, The Netherlands.
Center of Expertise in Mycology, Radboud University Medical Center/Canisius Wilhelmina Ziekenhuis, Nijmegen, The Netherlands.

Rob Ter Heine (R)

Department of Pharmacy, Radboud University Medical Center, Radboud Institute for Medical Innovation, Nijmegen, The Netherlands.

Classifications MeSH