Assumption testing in population pharmacokinetic models: illustrated with an analysis of moxonidine data from congestive heart failure patients.
Deriving a population pharmacokinetic model from real data is always associated with numerous assumptions. Violations of these assumptions, especially if undetected, may lead to inappropriate conclusions being made from the analysis. Routinely, only a few of the assumptions are explicitly stated and justified in the reporting of a population model. Here, we attempt to be exhaustive in the presentation of the assumptions made in the course of an analysis of moxonidine pharmacokinetics. The different ways that assumptions were justified, through experience, graphical examination, or additional modeling, are outlined. Models for relaxing assumptions regarding the covariate and statistical submodels, not previously reported in the area of population pharmacokinetic modeling, are also described.
Karlsson
M O
MO
Department of Pharmacy, Uppsala University, Sweden.
Jonsson
E N
EN
Wiltse
C G
CG
Wade
J R
JR
D000328:Adult; D000368:Aged; D004311:Double-Blind Method; D005260:Female; D006333:Heart Failure / Q000188:drug therapy / Q000378:metabolism*; D006801:Humans; D007093:Imidazoles / Q000493:pharmacokinetics* / Q000627:therapeutic use; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D015233:Models, Statistical; D013997:Time Factors
D007093:Imidazoles; C043482:moxonidine