Mathematical modelling of transporter kinetics

Membrane transport proteins have recently been discovered to be ubiquitously expressed in the human body and of paramount importance in cellular uptake. Since all pharmaceutical compounds must pass through numerous cell membranes to travel and be absorbed by their target cells in order to achieve th...

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Bibliographic Details
Main Author: Grandjean, Thomas R. B.
Published: University of Warwick 2013
Subjects:
620
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.606165
Description
Summary:Membrane transport proteins have recently been discovered to be ubiquitously expressed in the human body and of paramount importance in cellular uptake. Since all pharmaceutical compounds must pass through numerous cell membranes to travel and be absorbed by their target cells in order to achieve their desired therapeutic effects, transporters have attracted a lot of attention as a research field. As an emerging focus area, the precise mechanism of action of many of these transporters remains to be fully elucidated. In order to gain a detailed insight into these processes it is proposed to carry out mechanistic modelling of the pharmacokinetics of transporters. This thesis details the models developed to further our understanding of carrier mediated transport. The current knowledge on cellular uptake and efflux are discussed and mathematical models are developed for two prominent transporters. Structural identifiability and indistinguishability analyses are performed on all the models developed using a variety of methods to investigate the applicability of each method. Model fits gave very good agreement with in vitro data provided by AstraZeneca across a variety of experimental scenarios and different species. Mechanistic models for in vivo applications are also developed and found to characterise hepatic uptake in rat accurately. Recommendations for further work to fully validate the models developed so that they can perform robust, predictive simulations are proposed. The research in this thesis demonstrates that mechanistic modelling of complex biological processes allows for greater understanding of such systems.