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Title: Modelling endocrine regulation of glycaemic control in animal models of diabetes
Author: Watson, Edmund M.
ISNI:       0000 0004 5366 0141
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2014
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This thesis is concerned with mathematical modelling of the glucose-insulin homeostatic system, with the specific aim of mathematically modelling diabetes and diabetes-like conditions in animals. Existing models were examined and critiqued in this thesis. Additionally, structural identifiability analysis of the most widely-used model in the field, the Minimal Model, was performed using Taylor series and similarity transformation approaches. It was shown under certain assumptions that it was theoretically possible to obtain a unique set of parameters for the model from only measuring glucose. C-peptide deconvolution was performed using the WinNonLin algorithm and Maximum Entropy technique implemented in MATLAB. This was used to calculate insulin secretion, the percentage of insulin appearing in the periphery and insulin clearance rate. This was then further developed to model insulin appearance and clearance based on hepatic blood flow changes. A short-term model of the glucose-insulin and C-peptide system was initially formulated using a PID controller concept and later refined to reduce the number of model parameters. Structural identifiability analysis was performed using the Lie symmetries approach, followed by parameter estimation on rat and mice data from IVGTTs, OGTTs and hyperglycaemic clamps and sensitivity analysis. This short-term model was integrated into a long-term model to analyse Zucker and ZDF rat data to create a single model to cater for both short- and long-term dynamics. Finally, a software tool was developed to allow non-mathematical scientists to use and access the benefits of the model.
Supervisor: Not available Sponsor: AstraZeneca (Firm)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QL Zoology ; RC Internal medicine