Physiologically based pharmacokinetic models in the prediction of oral drug exposure over the entire pediatric age range-sotalol as a model drug

Abstract

In recent years, the increased interest in pediatric research has enforced the role of physiologically based pharmacokinetic (PBPK) models in pediatric drug development. However, an existing lack of published examples contributes to some uncertainties about the reliability of their predictions of oral drug exposure. Developing and validating pediatric PBPK models for oral drug application shall enrich our knowledge about their limitations and lead to a better use of the generated data. This study was conducted to investigate how whole-body PBPK models describe the oral pharmacokinetics of sotalol over the entire pediatric age. Two leading software tools for whole-body PBPK modeling: Simcyp® (Simcyp Ltd, Sheffield, UK) and PK-SIM® (Bayer Technology Services GmbH, Leverkusen, Germany), were used. Each PBPK model was first validated in adults before scaling to children. Model input parameters were collected from the literature and clinical data for 80 children were used to compare predicted and observed values. The results obtained by both models were comparable and gave an adequate description of sotalol pharmacokinetics in adults and in almost all pediatric age groups. Only in neonates, the mean ratio(Obs/Pred) for any PK parameter exceeded a twofold error range, 2.56 (95% confidence interval (CI), 2.10-3.49) and 2.15 (95% CI, 1.77-2.99) for area under the plasma concentration-time curve from the first to the last concentration point and maximal concentration (Cmax) using SIMCYP® and 2.37 (95% CI, 1.76-3.25) for time to reach Cmax using PK-SIM®. The two PBPK models evaluated in this study reflected properly the age-related pharmacokinetic changes and predicted adequately the oral sotalol exposure in children of different ages, except in neonates.

Fig. 1

The height and/or weight (dots) of each of the 80 children (boys, n = 54 (right); girls, n = 26 (left)); the observed population originally exposed to sotalol. In addition, lines show pediatric age- and gender-specific percentiles (3rd, 10th, 50th, 90th, and 97th), which represent the normal values of a German representative population (61). Insets show the demographics of the segment from birth to the end of the first year to highlight the values of newborns and infants

Fig. 2

Schematic workflow of the developed PBPK models

Fig. 3

Comparison of predicted (lines; mean, 5–95th percentiles, min/max) and mean observed (dots; ±SD) concentrations of IV and oral sotalol after various dosing in both Caucasians (a, b) and Asians (c, d). Simulations were performed using software 1 (SIMCYP®, left column, filled circles) and 2 (PK-SIM®, right column, empty circles). Observed data are obtained from Refs. (26,28,32,35)

Fig. 4

Goodness of fit plots for simulations of adult data by both sotalol PBPK models. a Predicted vs. observed concentrations plot, b–e predicted vs. observed AUC_last, C _max, t _max, and k _e plots. Results are obtained by using software 1 (SIMCYP®, left column, filled circles) and software 2 (PK-SIM®, right column, empty circles). Line, line of unity; dashed lines, twofold error range; MDPE median percentage error (95% CI), MDAPE median absolute percentage error (95% CI)

Fig. 5

Comparison of predicted (lines; median, 5–95th percentiles) vs. individual observed (symbols) plasma concentrations in six representative pediatric patients from adolescents (a) to neonates (f), after various dosing of oral sotalol. Predictions were made using software 1 (Simcyp®, left, filled circles) and 2 (PK-SIM®, right, empty circles). Observed data are taken from Refs. (37)

Fig. 6

Comparison between the observed and predicted values of a the area under the plasma concentration-time curve (AUC _last), b maximum concentration (C _max), c time of the maximum concentration (t _max), and d the elimination-rate constant (k _e) in adults oral studies and in children. Results are presented as mean ratios in each age group (symbols—circles for software 1 results, squares for software 2 results) with a 95% confidence interval (horizontal lines)

Fig. 7

Median predicted vs. individual observed concentration plots for 80 pediatric patients stratified in 6 pediatric age groups from a adolescents to f neonates. Results are obtained by using software 1 (SIMCYP®, left column, filled circles) and 2 (PK-SIM®, right column, empty circles). Line, line of unity; dashed lines, twofold error range; MDPE median percentage error (95% CI), MDAPE median absolute percentage error (95% CI)