MURAL - Maynooth University Research Archive Library



    Adaptive Approach for Modelling Variability in Pharmacokinetics.


    Weiße, Andrea Y. and Horenko, Illia and Huisinga, Wilhelm (2006) Adaptive Approach for Modelling Variability in Pharmacokinetics. In: Computational Life Sciences II Second International Symposium, CompLife 2006 Cambridge, UK, September 27-29, 2006. Proceedings. Lecture Notes in Computer Science (LNCS), 4216/2006 . Springer Berlin / Heidelberg, pp. 194-204. ISBN 978-3-540-45767-1

    [img] Download (308kB)
    Official URL: http://www.springerlink.com/content/duv5732v135767...


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    We present an improved adaptive approach for studying systems of ODEs affected by parameter variability and state space uncertainty. Our approach is based on a reformulation of the ODE problem as a transport problem of a probability density describing the evolution of the ensemble of systems in time. The resulting multidimensional problem is solved by representing the probability density w.r.t. an adaptively chosen Galerkin ansatz space of Gaussian distributions. Due to our improvements in adaptivity control, we substantially improved the overall performance of the original algorithm and moreover inherited the theoretical property that the number of Gaussian distribution stays constant for linear ODEs to the numerical scheme. We illustrate the approach in application to dynamical systems describing the pharmacokinetics of drugs and xenobiotics, where variability in physiological parameters is important to be considered.

    Item Type: Book Section
    Additional Information: The original publication is available at http://www.springerlink.com/content/duv5732v13576770/fulltext.pdf
    Keywords: Pharmacokinetics; ODE problem; Gaussian densities; CompLife 2006; LNCS; Hamilton Institute.
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Science and Engineering > Mathematics and Statistics
    Item ID: 1790
    Identification Number: https://doi.org/10.1007/11875741_19
    Depositing User: Hamilton Editor
    Date Deposited: 18 Jan 2010 15:01
    Publisher: Springer Berlin / Heidelberg
    Refereed: Yes
    URI:

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year