Identification of an anticancerous drug model in brain tissues using AdomianAlienor methods

Purpose In this paper, nonlinear compartment modelling is used to study drug transport of anticancerous substance across brain tissues. The aim of the work is to identify the pharmacokinetic parameters of the model created. Designmethodologyapproach A combination of the Adomian decomposition method...

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Veröffentlicht in:Kybernetes 2005-08, Vol.34 (7/8), p.1187-1199
Hauptverfasser: Zaidi, Z., Manseur, S., Cherruault, Y., Meulemans, A.
Format: Artikel
Sprache:eng
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Zusammenfassung:Purpose In this paper, nonlinear compartment modelling is used to study drug transport of anticancerous substance across brain tissues. The aim of the work is to identify the pharmacokinetic parameters of the model created. Designmethodologyapproach A combination of the Adomian decomposition method and the Alienor reducing transformation method were used to solve the identification problem as if it were a classical onedimensional minimization problem. Findings The numerical results using this methodology have shown that local therapeutic method should be preferred, when it comes to evaluate the rate of healthy cellscancerous cells, especially when, somehow, the drug transition into the tumour is speeded up. The combination method of Adomian and Alienor proved a successful strategy, and could take into account many of the pharmacokinetic parameters as necessary and use wellknown algorithms. Research limitationsimplications It is believed that this modest work can be considered as preliminary steps for improving local drug administration. Practical implications The study has shown that pharmacokineticpharmacodynamic modelling can help to understand the drug behaviour in such complex media and hence avoid the most threatening side effects by predicting the toxicity threshold of a drug and therefore minimize the therapeutic index. Originalityvalue Shows the powerful tools of Adomian and Alienor techniques that can be applied successfully in biomedical applications.
ISSN:0368-492X
DOI:10.1108/03684920510605966