On some "disadvantages" of the population approach.
In a seminal article on population pharmacokinetic modeling, researchers demonstrated how means and variances of pharmacokinetic parameters for a patient population could be inferred from sparse data collected under conditions of routine patient care. But they also identified 4 potential concerns about their methodology: unobserved confounding variables may bias the inferences; conditions under which data are collected may lead to inaccuracies of reporting or recording; correlations among important predictor variables may reduce statistical efficiency; and costs cannot be controlled by principles of study design. Experiences are reviewed that relate to these potential disadvantages. A method is presented for diagnosing the possible presence of confounding. A model is constructed and applied that captures the influences of data inaccuracies. An example of selecting from among correlated covariates is summarized. Finally, a methodology for optimal study design is reviewed and applied to an example.
Nedelman
Jerry R
JR
Novartis Pharmaceuticals, One Health Plaza, East Hanover, NJ 07936, USA. jerry.nedelman@pharma.novartis.com
D000818:Animals; D006801:Humans; D008954:Models, Biological; D010599:Pharmacokinetics; D013997:Time Factors