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

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 R² 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.