J.R. Wade, PhD(1,2), S.L. Beal PhD(2) and N.C. Sambol, PharmD(2)
(1)Division of Pharmacokinetics, Uppsala University, BMC, Box 580, Uppsala, S-751 23, Sweden.; (2) Depts. of Laboratory Medicine and Pharmacy, University of California, San Francisco, CA 94143, USA.
The influence of the choice of pharmacokinetic model on subsequent determination of covariate relationships in population pharmacokinetic analysis was studied using both simulated and real data sets. Data analysis was done using the program NONMEM. Data were simulated using a two compartment model in which a simple categorical covariate acted on clearance (CL), but at late sample times, so that preferential selection of the two compartment model should have been impossible. Initially, on the basis of a difference in the objective function value, the two compartment model was virtually always preferentially selected. Only when the complexity of the one compartment model was increased in terms of the covariate and statistical models was the difference in objective function value between the one and two compartment models negligible. Two real data sets in which the two compartment model was not preferentially selected, more complex covariate relationships were supported with the one compartment model than with the two compartment model. Thus, the choice of structural model can be affected as much by the choice of the covariate model as can the choice of covariate model be affected by the choice of the structural model; the two choices are interestingly intertwined. A suggestion on how to proceed when building population pharmacokinetic models will be given.
Reference: PAGE 3 (1994) Abstr 869 [www.page-meeting.org/?abstract=869]
Poster: oral presentation