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.

Optimizing the Clinical Use of Carvedilol in Liver Cirrhosis Using a Physiologically Based Pharmacokinetic Modeling Approach

“…After the calculations of the PK parameters, an observed/predicted ratio (ratio (Obs/Pred) ) was generated and calculated ratios within a two-fold error range was considered appropriate in the model evaluation, which is similar to the practice reported in other PBPK-model-based studies [8,9,[34][35][36]. Finally, the unbound and total (bound and unbound) AUC's for carvedilol in healthy and cirrhosis (CP-A-C) populations were reported as mean values along with 95 % confidence intervals (CI) and were presented graphically as boxplots.…”

Neonatal medicines research: challenges and opportunities

“…To illustrate this, we would like to refer to a very recently published paper on PBPK-based modeling using both software packages mentioned to predict oral drug exposure over the entire pediatric age range. Using sotalol as a model drug, both PBPK software packages evaluated reflected properly the age-related PK changes and predicted adequately the oral sotalol exposure in children of different ages, except in neonates where an above twofold error was observed [67]. These differences were likely explained by controversies and knowledge gaps on neonatal development of the gastrointestinal tract and functions [68].…”

“…This is at present also reflected in the fact that the most commonly used PBPK modeling tools (i.c. Symcyp, PK-Sim) do not yet contain robust information on preterm neonates [54,67]. This includes, but is not limited to the physiological parameters driving oral absorption throughout early infancy.…”

Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

“…The literature contains several examples of PBPK models assessing phenotype, sex, age, and disease effects on absorption [7,8,58–61,50,17]. All the above examples paving the way towards reaching the ultimate goal of personalized or individualized medicine [62].…”