Impact of model misspecification at design (and/or) estimation step in population pharmacokinetic studies.
The aim of this work is to quantitatively assess the impact of structural model misspecifications on the estimates of mean and interindividual variability of clearance in the context of population approaches. This assessment is conducted from simulated datasets. Our results show that impact magnitude of model misspecification on the estimates depends on the step at which it occurs (design optimization and/or estimation), on the hyperparameter of interest, and on the estimation method. Bias and precision might be affected differently as well as powers of model discrimination tests. Some practical guidelines for reducing impact of model misspecifications are also suggested.
Merlé
Yann
Y
INSERM et Départment de Pharmacologie Clinique, Faculté de Médecine Cochin-Port Royal, Université Paris V, Paris, France. yann.merle@cochin.univ-paris5.fr
Aouimer
Azzedine
A
Tod
Michel
M
D006801:Humans; D015233:Models, Statistical; D010599:Pharmacokinetics