Development of a dosing algorithm integrating pharmacogenetic markers and inflammation for individualization of initial voriconazole maintenance doses

ABSTRACT Achieving early therapeutic trough concentrations (Cmin) of voriconazole (VRC) is crucial for treatment efficacy and to avoid side effects. Since VRC Cmin are influenced by numerous determinants, this multicenter retrospective study aimed to develop a multiparametric dosing algorithm for individualizing initial VRC maintenance doses. Individual data regarding VRC Cmin from adult patients and associated parameters (age, sex, underlying disease [presence of hematological disease/other], weight, dose, route of administration, indication: curative/prophylactic, cytochrome [CYP]2C19 and 3A genotypes, C-reactive protein [CRP], transaminases, bilirubin, and proton pump inhibitor treatment) were collected from six previously published studies and routine care data from seven laboratories (building cohort). A mixed-effects model predicting VRC Cmin was developed on this building cohort using a stepwise cross-validation procedure and then externally validated on an independent cohort (validation cohort). The building and validation cohorts included 977 VRC Cmin in 277 patients and 47 VRC Cmin in 33 patients, respectively. The initial model, which integrated VRC daily dose, CYP2C19 genotype, and CRP, was enriched by two additional covariates: age and underlying disease. The final model had an R ² of 0.69 but tended to underestimate low VRC Cmin and overestimate high VRC Cmin. Finally, a formula derived from this final model was proposed and integrated into an Excel sheet to individualize initial VRC maintenance doses. The developed predictive model allowed for the creation of a multiparametric dosing algorithm for the individualization of initial VRC maintenance doses. The benefit of this algorithm will soon be evaluated in a prospective pilot study to improve initial VRC exposure.

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Publication Details

Journal
Antimicrobial Agents and Chemotherapy
Published
2026-09-11
DOI
https://doi.org/10.1128/aac.00278-26
Primary Topic
Antifungal resistance and susceptibility
Type
article
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article

Development of a dosing algorithm integrating pharmacogenetic markers and inflammation for individualization of initial voriconazole maintenance doses

Jan‐Willem C. Alffenaar, Matthieu Roustit, Sylvia D. Klomp, Christelle Boglione‐Kerrien et al.
Antimicrobial Agents and Chemotherapy
Antifungal resistance and susceptibility
article

Development of a dosing algorithm integrating pharmacogenetic markers and inflammation for individualization of initial voriconazole maintenance doses

Jan‐Willem C. Alffenaar, Matthieu Roustit, Sylvia D. Klomp, Christelle Boglione‐Kerrien, Charles Khouri, Benjamin Hennart, Fabien Lamoureux, Françoise Stanke‐Labesque, Caroline Solas, Anette Veringa, Jesse J. Swen, Capucine Arrivé, Nicolas Pallet, Elodie Gautier‐Veyret, Céline Verstuyft, Takafumi Naito, Sarah Baklouti, on behalf of the Therapeutic Drug Monitoring and Personalization Treatment group of the French Society of Pharmacology and Therapeutics and the French-Speaking Network of Pharmacogenetics (RNPGx), Othilie Giannoni, Takahiro Yamada, Marc Manceau
article en

Abstract

ABSTRACT Achieving early therapeutic trough concentrations (Cmin) of voriconazole (VRC) is crucial for treatment efficacy and to avoid side effects. Since VRC Cmin are influenced by numerous determinants, this multicenter retrospective study aimed to develop a multiparametric dosing algorithm for individualizing initial VRC maintenance doses. Individual data regarding VRC Cmin from adult patients and associated parameters (age, sex, underlying disease [presence of hematological disease/other], weight, dose, route of administration, indication: curative/prophylactic, cytochrome [CYP]2C19 and 3A genotypes, C-reactive protein [CRP], transaminases, bilirubin, and proton pump inhibitor treatment) were collected from six previously published studies and routine care data from seven laboratories (building cohort). A mixed-effects model predicting VRC Cmin was developed on this building cohort using a stepwise cross-validation procedure and then externally validated on an independent cohort (validation cohort). The building and validation cohorts included 977 VRC Cmin in 277 patients and 47 VRC Cmin in 33 patients, respectively. The initial model, which integrated VRC daily dose, CYP2C19 genotype, and CRP, was enriched by two additional covariates: age and underlying disease. The final model had an R ² of 0.69 but tended to underestimate low VRC Cmin and overestimate high VRC Cmin. Finally, a formula derived from this final model was proposed and integrated into an Excel sheet to individualize initial VRC maintenance doses. The developed predictive model allowed for the creation of a multiparametric dosing algorithm for the individualization of initial VRC maintenance doses. The benefit of this algorithm will soon be evaluated in a prospective pilot study to improve initial VRC exposure.

Antimicrobial Agents and Chemotherapy
University Medical Center Groningen (NL), Inserm (FR), American Pharmacists Association (US), Leiden University Medical Center (NL), Centre Hospitalier Universitaire de Grenoble (FR), Centre Hospitalier Universitaire de Lille (FR), Hamamatsu University School of Medicine (JP), HES-SO Genève (CH), Assistance Publique – Hôpitaux de Paris (FR), Orbits Lightwave (United States) (US), Normandie Université (FR), Hôpital Européen (FR), Shinshu University Hospital (JP), Hôpital Purpan (FR), Société Française de Cardiologie (FR), Hôpitaux Universitaires de Strasbourg (FR), Grenoble Institute of Neurosciences (FR), Hôpital de la Timone (FR), Université de Rouen Normandie (FR), Université Grenoble Alpes (FR)
Good health and well-being
Openalex Percentile: Top 11%
Antifungal resistance and susceptibility
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