Methods: This study explored key study design factors that could impact the precision of pediatric pharmacokinetics (PK) estimation. A virtual pediatric population was constructed, incorporating diverse body weight distribution sourced from the U.S. Centers for Disease Control and Prevention (CDC) growth charts. These generated weights were aggregated based on age ranges (2–5, 6–11, 12–17, and 2–17 y.o.), and different sample sizes were randomly selected to simulate PK concentrations over an approximately 5 half-lives period for a hypothetical monoclonal antibody. Throughout the simulations, the “true” allometric scaling exponents for the apparent volume of distribution and apparent clearance were consistently assumed to be 1.0 and 0.75, respectively, consistent with physiological and pharmacological knowledge for monoclonal antibodies. The impact of various pediatric study design factors on the model estimates of allometric exponents was then investigated by assuming the generated PK data as observed, with unknown PK parameters and allometric scaling exponent values. The data were subsequently fitted with population PK models, and estimated parameters were compared to “true” values to assess precision. Precision in estimated allometric exponents served as a marker for evaluating how effectively data from various study designs can inform the pediatric PK estimation. Results: Generally, estimates of allometric scaling exponents were more accurate with a larger sample size, proper PK sampling scheme, inclusion of densely sampled adult data, and a broader range of age. Conclusions: Considering the limitations in designing most pediatric studies, these findings support recent regulatory recommendations that standard allometric exponents should be considered in pediatric PK analysis for monoclonal antibodies in general.
Danso et al. (Thu,) studied this question.