GROUP PHARMACOKINETICS OF FLUCONAZOLE IN PATIENTS WITH SEVERE INFECTION
Keywords:
Voriconazole, Population pharmacokinetics, Exposure-response relationshipAbstract
Objective: The aim was to investigate the population pharmacokinetics (PopPK) model of Vorticamole (VRC), identify significant covariates and corresponding dose optimization strategies in the existing clinical patient VRC PopPK model, and explore the characteristics of the existing VRC PopPK model. Methods: We searched the PubMed database for clinical PopPK studies of VRC using the nonlinear mixed-effects method from the establishment of the database to May 2025, and screened the relevant references. Results: A total of 29 studies that met the inclusion criteria were finally included. One-compartment and two-compartment models were reported in 21 and 7 studies, respectively, as the best models to describe the PopPK of VRC, and one study used a three-compartment model. More than 40 covariates were included in the screening, with the most common covariates being CYP2C19 phenotype and body weight, and ALB being a secondary covariate. The typical volume of distribution in adult and pediatric patients was similar, but the estimated clearance in pediatric patients was significantly higher than that in adult patients, and the estimated bioavailability in pediatric patients was significantly lower than that in adult patients. The typical values of voriconazole clearance and total apparent volume of distribution exhibit substantial variability, ranging from 2.29–7.35 L/h and 76–194 L, respectively. Twenty-four studies used the exponential model as the basic model to describe the inter-individual variation. Only three studies used external methods to evaluate the model. Conclusion: First, this paper emphasizes the broadness and variability of the estimated PopPK parameters of VRC and provides the covariates that affect the clearance and apparent volume of distribution in such patients. Second, external evaluation of PopPK models should be conducted, and the predictive performance of various models should be further compared to improve the extrapolation ability of the models. In addition, it is recommended to conduct Monte Carlo simulations based on the significant covariates derived from different patient groups, and to supplement PopPK models to guide the differences in clinical efficacy between dose and traditional empirical dose, track the individualized medication effects of patients guided by PopPK models, and conduct supplementary trials based on actual clinical efficacy to facilitate the more reasonable application of models in clinical practice.References
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