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PKAIN: An artificial immune network for parameter optimization in pharmacokinetics

PKAIN: An artificial immune network for parameter optimization in pharmacokinetics

Liu, L., Lai, C.-H., Zhou, S.-D., Xie, F. and Lu, H.-W. (2009) PKAIN: An artificial immune network for parameter optimization in pharmacokinetics. In: WIT Transactions on Biomedicine and Health. Modelling in Medicine and Biology VIII. WIT Press, Southampton, UK, pp. 277-285. ISBN 978-1-84564-183-2 ISSN 1743-3525 (doi:10.2495/BIO090261)

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Abstract

The PKAIN algorithm is an artificial immune network, which has been designed to optimize parameters of linear pharmacokinetic models in our previous work. In this paper, the algorithm is modified to optimise parameters of nonlinear pharmacokinetic models. To evaluate parameters, the numerical inverse Laplace method is adopted to calculate drug concentrations of the dynamic system. The initial solutions of pharmacokinetic parameters are generated randomly by the PKAIN algorithm in a given solution space. Memory cells to be used in the search of global optimal parameters are generated. The optimal mechanism of the algorithm is based on artificial immune network principles and simplex mutation. In addition, a distributed version of the PKAIN algorithm is proposed to improve its efficiency.

Item Type: Conference Proceedings
Title of Proceedings: WIT Transactions on Biomedicine and Health. Modelling in Medicine and Biology VIII
Additional Information: [1] Published in: WIT Transactions on Biomedicine and Health, Volume 13, 2009 - 8th International Conference on Modelling in Medicine and Biology. Crete, Greece. 26-28 May 2009.
Uncontrolled Keywords: pharmacokinetic model, distributed computing, artificial immune network, numerical inverse Laplace, simplex
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Related URLs:
Last Modified: 14 Oct 2016 09:19
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/7785

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