Comparison of two types of population pharmacokinetic model structures of paclitaxel
2008 (English)In: European Journal of Pharmaceutical Sciences, ISSN 0928-0987, Vol. 33, no 2, 128-137 p.Article in journal (Refereed) Published
Two main types of model structures have been proposed for the pharmacokinetics of paclitaxel; an empirical model structure based on total plasma concentrations of paclitaxel, and a mechanism-based model structure derived from both total and unbound paclitaxel concentrations and concentrations of the formulation vehicle Cremophor EL. The purpose was to compare the two pharmacokinetic model structures when only total paclitaxel concentrations are available. To support the mechanism-based model structure with Cremophor EL concentrations, in silico concentrations were obtained from simulations of a pharmacokinetic model available in the literature. Local algebraic observability was tested on both model structures; the mechanism-based model structure was found, with high probability, not to be algebraically observable if total paclitaxel concentration is considered to be the only model output, and if no kind of prior information is used. Sensitivity analysis was performed to reveal which parameter should be fixed in order to make it locally observable. Parameter estimation was then performed on both model structures using nonlinear mixed effects and data from a clinical study. The estimated mechanism-based model turned out to have a somewhat better fit to data than the corresponding empirical model, , where AIC is the Akaike Information Criterion. Hold-out validation was performed on three patients, but did not favour any of the models. In conclusion, since the mechanism-based model structure behaved at least as good as the empirical model structure, it is suggested that the former model structure should be used since it offers a more accurate description of the disposition.
Place, publisher, year, edition, pages
2008. Vol. 33, no 2, 128-137 p.
Paclitaxel, Model structure, Observability, NONMEM, Simulation
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-12762DOI: 10.1016/j.ejps.2007.10.005OAI: oai:DiVA.org:liu-12762DiVA: diva2:17001