Application of a Physiologically Based Pharmacokinetic Model to Characterize Time-dependent Metabolism of Voriconazole in Children and Support Dose Optimization.

Yahui Zhang,Pengxiang Zhou,Sixuan Zhao,Suodi Zhai,Chuhui Wang

doi:10.3389/fphar.2021.636097

Abstract

Background: Voriconazole is a potent antifungal drug with complex pharmacokinetics caused by time-dependent inhibition and polymorphisms of metabolizing enzymes. It also exhibits different pharmacokinetic characteristics between adults and children. An understanding of these alterations in pharmacokinetics is essential for pediatric dose optimization. Objective: To determine voriconazole plasma exposure in the pediatric population and further investigate optimal dosage regimens. Methods: An adult and pediatric physiologically based pharmacokinetic (PBPK) model of voriconazole, integrating auto-inhibition of cytochrome P450 3A4 (CYP3A4) and CYP2C19 gene polymorphisms, was developed. The model was evaluated with visual predictive checks and quantitative measures of the predicted/observed ratio of the area under the plasma concentration-time curve (AUC) and maximum concentration (Cmax). The validated pediatric PBPK model was used in simulations to optimize pediatric dosage regimens. The probability of reaching a ratio of free drug (unbound drug concentration) AUC during a 24-h period to minimum inhibitory concentration greater than or equal to 25 (fAUC24h/MIC ≥ 25) was assessed as the pharmacokinetic/pharmacodynamic index. Results: The developed PBPK model well represented voriconazole's pharmacokinetic characteristics in adults; 78% of predicted/observed AUC ratios and 85% of Cmax ratios were within the 1.25-fold range. The model maintained satisfactory prediction performance for intravenous administration in pediatric populations after incorporating developmental changes in anatomy/physiology and metabolic enzymes, with all predicted AUC values within 2-fold and 73% of the predicted Cmax within 1.25-fold of the observed values. The simulation results of the PBPK model suggested that different dosage regimens should be administered to children according to their age, CYP2C19 genotype, and infectious fungal genera. Conclusion: The PBPK model integrating CYP3A4 auto-inhibition and CYP2C19 gene polymorphisms successfully predicted voriconazole pharmacokinetics during intravenous administration in children and could further be used to optimize dose strategies. The infectious fungal genera should be considered in clinical settings, and further research with large sample sizes is required to confirm the current findings.

Highlights

Voriconazole is an essential triazole antifungal agent with in vivo activity against a broad spectrum of yeasts and filamentous fungi, commonly used for the prophylaxis and treatment of various invasive fungal infections (IFI) (Clancy and Nguyen, 1998; Saravolatz et al, 2013; Perfect et al, 2003)
A proper fit was achieved in the adult model, as shown in Figure 2, and most of the observed concentrations fell within the 5% and 95% concentration-time prediction intervals
The physiologically based pharmacokinetic (PBPK) model well captured the pharmacokinetic features in children after integrating in vivo ontogeny profiles

Summary

Introduction

Voriconazole is an essential triazole antifungal agent with in vivo activity against a broad spectrum of yeasts and filamentous fungi, commonly used for the prophylaxis and treatment of various invasive fungal infections (IFI) (Clancy and Nguyen, 1998; Saravolatz et al, 2013; Perfect et al, 2003). A high interindividual plasma variability has been observed partially due to its nonlinear and time-dependent pharmacokinetics (Purkins et al, 2003; Pfizer, 2010). It exhibits differences in clearance and bioavailability between adults and children (Schulz et al, 2019). All these factors Parameter Unit Value Source. Voriconazole is a potent antifungal drug with complex pharmacokinetics caused by time-dependent inhibition and polymorphisms of metabolizing enzymes. It exhibits different pharmacokinetic characteristics between adults and children. An understanding of these alterations in pharmacokinetics is essential for pediatric dose optimization

Methods

Results

Conclusion