Predicting pediatric age-matched weight and body mass index

Area of Science:

• Pharmacokinetics and Pharmacodynamics
• Pediatric Drug Development
• Biostatistics

Background:

• Allometric scaling based on body weight is the standard for pediatric dose selection.
• Existing methods require accurate age-matched weight data for pediatric populations.
• Interindividual variability in pediatric weight necessitates robust simulation methods.

Purpose of the Study:

• To develop an empirical function for simulating age-matched weight and body mass index in pediatric populations.
• To evaluate the suitability of the Center for Disease Control (CDC) dataset for pediatric drug development.
• To demonstrate the utility of the developed function in predicting drug concentration-time profiles.

Main Methods:

• Utilized polynomial functions (up to fifth order) to model pediatric weight and BMI data from CDC and WHO.
• Incorporated a constant coefficient to account for interindividual variability in weight.
• Applied the simulated age-matched weights to a population pharmacokinetic model for tenofovir.

Main Results:

• A polynomial function accurately described pediatric weight and BMI data with coefficients of variation within 17%.
• CDC simulated weights for children aged 0-5 years showed acceptable overlap with WHO confidence boundaries.
• The prediction intervals for tenofovir concentration-time profiles were similar using weights simulated from either CDC or WHO datasets.

Conclusions:

• The developed empirical function provides a reliable method for simulating pediatric weight and BMI.
• The CDC dataset is a viable substitute for the WHO dataset in pediatric drug development.
• This approach simplifies and broadly applies to pediatric dose adjustments using allometry.