Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4
Marion Bouillon-Pichault, Vincent Jullien, Caroline Bazzoli, Gérard Pons, Michel Tod
Objectives: The pharmacokinetics of drugs in children is different from those in adults, because of growth and maturation. It is commonly accepted that clinical investigations with children are difficult, in particular because of recruitment difficulties. Metabolic pathways have maturation patterns that change from one another. The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochromes P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, whils taking into account age- and weight-related changes.
Methods: A linear monocompartmental model with first-order aborption was used successively with three residual error models and previously published pharmacokinetics parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases". The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse samplimg databases". We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modelled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values.
Results: The established optimal design comprised four age ranges: 0.008 years old (i.e. around three days), 0.192 years old (i.e. around three months), 1.325 years old and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance end distribution volume and less than 18% for ka), whereas the maturation parameters were unbiased but less precise (MPE<6% and RMSE<37%).
Conclusions: Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However , it requires that very early ages be included in studies, which may present an obstacle to the used of this approach. First-pass effect, alternative elimination routes and combined elimination pathways should also be investigated.