Predictive Performance of Physiologically Based Pharmacokinetic (PBPK) Modeling of Drugs Extensively Metabolized by Major Cytochrome P450s in Children.

Abstract

The accuracy of physiologically based pharmacokinetic (PBPK) model prediction in children, especially those younger than 2 years old, has not been systematically evaluated. The aim of this study was to characterize the pediatric predictive performance of the PBPK approach for 10 drugs extensively metabolized by CYP1A2 (theophylline), CYP2C8 (desloratidine, montelukast), CYP2C9 (diclofenac), CYP2C19 (esomeprazole, lansoprazole), CYP2D6 (tramadol), and CYP3A4 (itraconazole, ondansetron, sufentanil). Model performance in children was evaluated by comparing simulated plasma concentration-time profiles with observed clinical results for each drug and age group. PBPK models reasonably predicted the pharmacokinetics of desloratadine, diclofenac, itraconazole, lansoprazole, montelukast, ondansetron, sufentanil, theophylline, and tramadol across all age groups. Collectively, 58 out of 67 predictions were within 2-fold and 43 out of 67 predictions within 1.5-fold of observed values. Developed PBPK models can reasonably predict exposure in children age 1 month and older for an array of predominantly CYP metabolized drugs.