Paediatric drug development: are population models predictive of pharmacokinetics across paediatric populations?

Area of Science:

• Pharmacology
• Clinical Pharmacology
• Drug Development

Background:

• Accurate dose selection is critical in pediatric drug development.
• Model-based approaches are increasingly used for predicting drug exposure.
• Paediatric populations exhibit significant pharmacokinetic variability due to developmental changes.

Purpose of the Study:

• To evaluate the predictive accuracy of a model-based approach for selecting drug doses in pediatric populations during early clinical development.
• To assess the generalizability of pharmacokinetic models across different pediatric age groups (infants, toddlers, and children).

Main Methods:

• Abacavir was used as a model drug, with pharmacokinetic (PK) data analyzed separately for infants/toddlers and children.
• Two independent PK models were developed: a two-compartment model for younger children and a one-compartment model for older children.
• Systemic exposure (AUC) was simulated, and models were used to predict drug exposure in populations different from those used for model building.

Main Results:

• Both developed PK models accurately described drug exposure within their respective populations.
• Neither model successfully predicted drug exposure in the other pediatric population.
• In infants, estimated AUC was 7.03 µg ml⁻¹h, but predicted AUC was 5.75 µg ml⁻¹h; in children, estimated AUC was 6.96 µg ml⁻¹h, and predicted AUC was 6.45 µg ml⁻¹h.

Conclusions:

• The assumption of consistent relationships between PK parameters and demographic factors across pediatric age groups may be invalid.
• While modeling accurately characterizes PK within a specific population, extrapolating these estimates to different age groups has limited value.
• Developmental growth significantly impacts drug disposition, necessitating age-specific modeling or careful consideration of extrapolation limitations.