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Comparison of two types of population pharmacokinetic model structures of paclitaxel
Linköping University, Department of Computer and Information Science, PELAB - Programming Environment Laboratory. Linköping University, The Institute of Technology.
Linköping University, Department of Medicine and Health Sciences, Clinical Pharmacology . Linköping University, Faculty of Health Sciences.
2008 (English)In: European Journal of Pharmaceutical Sciences, ISSN 0928-0987, Vol. 33, no 2, 128-137 p.Article in journal (Refereed) Published
Abstract [en]

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.
Keyword [en]
Paclitaxel, Model structure, Observability, NONMEM, Simulation
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-12762DOI: 10.1016/j.ejps.2007.10.005OAI: diva2:17001
Available from: 2007-11-16 Created: 2007-11-16 Last updated: 2009-04-27
In thesis
1. Towards Individualized Drug Dosage - General Methods and Case Studies
Open this publication in new window or tab >>Towards Individualized Drug Dosage - General Methods and Case Studies
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Progress in individualized drug treatment is of increasing importance, promising to avoid much human suffering and reducing medical treatment costs for society. The strategy is to maximize the therapeutic effects and minimize the negative side effects of a drug on individual or group basis. To reach the goal, interactions between the human body and different drugs must be further clarified, for instance by using mathematical models. Whether clinical studies or laboratory experiments are used as primary sources of information, greatly

influences the possibilities of obtaining data. This must be considered both prior and during model development and different strategies must be used. The character of the data may also restrict the level of complexity for the models, thus limiting their usage as tools for individualized treatment.

In this thesis work two case studies have been made, each with the aim to develop a model for a specific human-drug interaction. The first case study concerns treatment of inflammatory bowel disease with thiopurines, whereas the second is about treatment of ovarian cancer with paclitaxel. Although both case studies make use of similar amounts of experimental data, model development depends considerably on prior knowledge about the systems, the character of the data and the choice of modelling tools. All these factors are presented for

each of the case studies along with current results. Further, a system for classifying different but related models is also proposed with the intention that an increased understanding will contribute to advancement in individualized drug dosage.

Place, publisher, year, edition, pages
Institutionen för datavetenskap, 2007. 53 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1332
drug dosage, population pharmacokinetics, biochemical modelling, identifiability, parameter estimation
National Category
Bioinformatics (Computational Biology)
urn:nbn:se:liu:diva-10251 (URN)978-91-85895-82-3 (ISBN)
2007-12-06, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Report code: LiU-Tek-Lic-2007:41.Available from: 2007-11-16 Created: 2007-11-16 Last updated: 2014-10-08

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