ABSTRACT
Nonlinear mixed models are important tools for analyzing repeated measures data. In particular, these models are used for population pharmacokinetic analyses for estimating population pharmacokinetic parameters. As more clinical studies are performed for the advancement of treatment of pediatric patients, methodology is needed for comparing results from pharmacokinetic studies in pediatric patients and adult control groups. These pediatric studies introduce complexities to the design and analysis, including how analysis of sparse data affects the limitations of model selection. A case study is presented demonstrating that good communication with regulatory agencies and appropriate selection of analysis models are integral parts of completing population analyses for timely approval and labeling of drugs for treating pediatric patients.
Notes
aSummary statistics of empirical Bayesian estimates of individual effects.
aSummary statistics of empirical Bayesian estimates of individual effects.