Population pharmacokinetics of voriconazole and initial dosage optimization in patients with talaromycosis

Enhancing voriconazole therapy in liver dysfunction: exploring administration schemes and predictive factors for trough concentration and efficacy

Introduction: The application of voriconazole in patients with liver dysfunction lacks pharmacokinetic data. In previous study, we proposed to develop voriconazole dosing regimens for these patients according to their total bilirubin, but the regimens are based on Monte Carlo simulation and has not been further verified in clinical practice. Besides, there are few reported factors that significantly affect the efficacy of voriconazole. Methods: We collected the information of patients with liver dysfunction hospitalized in our hospital from January 2018 to May 2022 retrospectively, including their baseline information and laboratory data. We mainly evaluated the efficacy of voriconazole and the target attainment of voriconazole trough concentration. Results: A total of 157 patients with liver dysfunction were included, from whom 145 initial and 139 final voriconazole trough concentrations were measured. 60.5% (95/157) of patients experienced the adjustment of dose or frequency. The initial voriconazole trough concentrations were significantly higher than the final (mean, 4.47 versus 3.90 μg/mL, p = 0.0297). Furthermore, daily dose, direct bilirubin, lymphocyte counts and percentage, platelet, blood urea nitrogen and creatinine seven covariates were identified as the factors significantly affect the voriconazole trough concentration. Binary logistic regression analysis revealed that the lymphocyte percentage significantly affected the efficacy of voriconazole (OR 1.138, 95% CI 1.016-1.273), which was further validated by the receiver operating characteristic curve. Conclusion: The significant variation in voriconazole trough concentrations observed in patients with liver dysfunction necessitates caution when prescribing this drug. Clinicians should consider the identified factors, particularly lymphocyte percentage, when dosing voriconazole in this population.

Can we predict the influence of inflammation on voriconazole exposure? An overview

Voriconazole is a triazole antifungal indicated for invasive fungal infections that exhibits a high degree of inter-individual and intra-individual pharmacokinetic variability. Voriconazole pharmacokinetics is non-linear, making dosage adjustments more difficult. Therapeutic drug monitoring is recommended by measurement of minimum plasma concentrations. Several factors are responsible for the high pharmacokinetic variability of voriconazole: age, feeding (which decreases absorption), liver function, genetic polymorphism of the CYP2C19 gene, drug interactions and inflammation. Invasive fungal infections are indeed very frequently associated with inflammation, which engenders a risk of voriconazole overexposure. Many studies have reviewed this topic in both the adult and paediatric populations, but few studies have focused on the specific point of the prediction, to evaluate the influence of inflammation on voriconazole pharmacokinetics. Predicting the impact of inflammation on voriconazole pharmacokinetics could help optimize antifungal therapy and improve patient management. This review summarizes the existing data on the influence of inflammation on voriconazole pharmacokinetics in adult populations. We also evaluate the role of C-reactive protein, the impact of inflammation on patient metabolic phenotypes, and the tools that can be used to predict the effect of inflammation on voriconazole pharmacokinetics.

Voriconazole exposure is influenced by inflammation: A population pharmacokinetic model

BACKGROUND

Voriconazole is an antifungal drug used for the treatment of invasive fungal infections. Due to highly variable drug exposure, therapeutic drug monitoring (TDM) has been recommended. TDM may be helpful to predict exposure accurately, but covariates, such as severe inflammation, that influence the metabolism of voriconazole have not been included in the population pharmacokinetic (popPK) models suitable for routine TDM.

OBJECTIVES

To investigate whether the effect of inflammation, reflected by C-reactive protein (CRP), could improve a popPK model that can be applied in clinical care.

PATIENTS AND METHODS

Data from two previous studies were included in the popPK modelling. PopPK modelling was performed using Edsim++. Different popPK models were compared using Akaike Information Criterion and goodness-of-fit plots.

RESULTS

In total, 1060 voriconazole serum concentrations from 54 patients were included in this study. The final model was a one-compartment model with non-linear elimination. Only CRP was a significant covariate, and was included in the final model and found to affect the maximum rate of enzyme activity (V_max). For the final popPK model, the mean volume of distribution was 145 L [coefficient of variation percentage (CV%)=61%], mean Michaelis-Menten constant was 5.7 mg/L (CV%=119%), mean V_max was 86.4 mg/h (CV%=99%) and mean bioavailability was 0.83 (CV%=143%). Internal validation using bootstrapping resulted in median values close to the population parameter estimates.

CONCLUSIONS

This one-compartment model with non-linear elimination and CRP as a covariate described the pharmacokinetics of voriconazole adequately.