AUTHOR=Zhang Yahui , Zhao Sixuan , Wang Chuhui , Zhou Pengxiang , Zhai Suodi TITLE=Application of a Physiologically Based Pharmacokinetic Model to Characterize Time-dependent Metabolism of Voriconazole in Children and Support Dose Optimization JOURNAL=Frontiers in Pharmacology VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.636097 DOI=10.3389/fphar.2021.636097 ISSN=1663-9812 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.