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

基于生理学的药代动力学模型 药代动力学 伏立康唑 药理学 CYP3A4型 曲线下面积 医学 药效学 人口 治疗药物监测 化学 细胞色素P450 内科学 抗真菌 新陈代谢 环境卫生 皮肤病科
作者
Yahui Zhang,Sixuan Zhao,Chuhui Wang,Pengxiang Zhou,Suodi Zhai
出处
期刊:Frontiers in Pharmacology [Frontiers Media]
卷期号:12 被引量:7
标识
DOI:10.3389/fphar.2021.636097
摘要

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 (C max ). 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 ( f AUC 24h /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 C max 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 C max 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.

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