Balanced designs in longitudinal population pharmacokinetic studies

Area of Science:

• Pharmacometrics
• Clinical Pharmacology
• Statistical Modeling

Background:

• Longitudinal population pharmacokinetic (PopPK) studies are essential for understanding drug behavior in diverse populations.
• Accurate estimation of pharmacokinetic parameters and their variability is critical for effective drug development and dosing strategies.
• Determining the optimal sample size is a key challenge in designing efficient PopPK studies.

Purpose of the Study:

• To determine the required sample size for accurate and precise estimation of population pharmacokinetic parameters.
• To evaluate the impact of intersubject variability on sample size requirements in a longitudinal PopPK study.
• To provide a framework for sample size estimation in PopPK studies with a balanced sampling design.

Main Methods:

• A simulation study using a balanced design and a two-compartment pharmacokinetic model.
• Varied intersubject variability (coefficient of variation, CV) from 30% to 100% with fixed residual variability (15%).
• Analyzed sample sizes from 30 to 1,000 subjects using NONMEM, generating 100 replicates per condition.

Main Results:

• A sample size of 30 subjects is adequate for parameter estimation when intersubject variability (CV) is ≤75% (except for clearance, Cl, where it's adequate up to 100% CV).
• Estimating intersubject variability requires a sample size of 80 subjects for CV ≤60%.
• Positively biased residual variability estimates occurred at CV ≥60%, suggesting caution in interpreting these results.

Conclusions:

• Sample size requirements in longitudinal PopPK studies are influenced by intersubject variability.
• A sample size of 30-80 subjects may be sufficient under moderate variability conditions.
• High intersubject variability (≥60%) necessitates careful interpretation of residual variability estimates.