Is the GFR-based scaling approach adequate for predicting pediatric renal clearance of drugs with passive tubular reabsorption? Insights from PBPK modeling

Abstract

Empirical maturation models (e.g., Johnson and Rhodin models) for glomerular filtration rate (GFR) are commonly used as scaling factors for predicting pediatric renal clearance, but their predictive performance for drugs featured with tubular reabsorption is poorly understood. This study investigated the adequacy of GFR-based scaling models for predicting pediatric renal clearance in drugs with passive tubular reabsorption by comparing with a mechanistic kidney model (Mech-KiM) that encompasses the physiological processes of glomerular filtration, tubular secretion, and reabsorption. The analysis utilized hypothetical drugs with varying fractions of tubular reabsorption (F_reabs), alongside the model drug metronidazole, which has a F_reabs of 96%. Our simulations showed that when F_reabs is ≤70%, the discrepancies between the GFR-based scaling methods and the Mech-KiM model in predicting pediatric renal clearance were generally within a twofold range throughout childhood. However, for drugs with substantial tubular reabsorption (e.g., F_reabs > 70%), discrepancies greater than twofold were observed between the GFR-based scaling methods and the Mech-KiM model in predicting renal clearance for young children. In neonates, the differences ranged from 5- to 10-fold when the adult F_reabs was 95%. Pediatric physiologically based pharmacokinetic (PBPK) modeling of metronidazole revealed that using a GFR-based scaling method (Johnson model) significantly overestimated drug concentrations in children under 2 months, whereas utilizing the Mech-KiM model for renal clearance predictions yielded estimates closely aligned with observed concentrations. Our study demonstrates that using GFR-based scaling models to predict pediatric renal clearance might be inadequate for drugs with extensive passive tubular reabsorption (e.g., F_reabs > 70%).

FIGURE 1

The ratio of renal clearance predicted by the Mech‐KiM model to those predicted by the GFR‐based scaling model (Johnson model) in children of different ages. Panel (a): Virtual drug in adults with a f _u of 0.9; panel (b): Virtual drug in adults with a f _u of 0.5; panel (c): Virtual drug in adults with a f _u of 0.1.

FIGURE 2

Maturation profiles of glomerular filtration rate (GFR) and bidirectional passive diffusion clearance (CL_PD) for tubular reabsorption in children relative to adult levels. GFR was predcited based on the Johnson and Rhodin models, and CL_PD was predicted by the Mech‐KiM model.

FIGURE 3

Observed versus predicted plasma concentration‐time profiles based on Pediatric Model I (panels a, c) and Pediatric Model II (panels b, d) for Rubenson et al. (panels a, b) and Jager et al. (panels c, d) studies. The orange dots represent the mean observations. The blue and gray lines represent the predicted mean and the 90% prediction interval of simulated plasma concentration‐time profiles by Pediatric Model I and Pediatric Model II.

FIGURE 4

Observed versus predicted plasma concentration‐time profiles by Pediatric Model II of metronidazole in pediatrics following different intravenous dosing regimens of metronidazole in Cohen et al. study. The orange dots represent individual‐level observations. The blue and gray lines represent the predicted mean and 90% prediction interval of simulated plasma concentration‐time profiles by Pediatric Model I. Literature data sources are presented in Table S3.