Developing and validating a new comprehensive glucose-insulin pharmacokinetics and pharmacodynamics model

Type 2 diabetes has reached epidemic proportions worldwide. The resulting increase in chronic and costly diabetes related complications has potentially catastrophic implications for healthcare systems, and economics and societies as a whole. One of the key pathological factors leading to type 2 diab...

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Bibliographic Details
Main Author: Ummu Kulthum, Jamaludin
Format: Thesis
Language:English
Published: 2013
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/7733/
http://umpir.ump.edu.my/id/eprint/7733/
http://umpir.ump.edu.my/id/eprint/7733/1/UMMU_KULTHUM_JAMALUDIN.PDF
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Summary:Type 2 diabetes has reached epidemic proportions worldwide. The resulting increase in chronic and costly diabetes related complications has potentially catastrophic implications for healthcare systems, and economics and societies as a whole. One of the key pathological factors leading to type 2 diabetes is insulin resistance (IR), which is the reduced or impaired ability of the body to make use of available insulin to maintain safe glucose concentrations in the bloodstream. It is essential to understand the physiology of glucose and insulin when investigating the underlying factors contributing to chronic diseases such as diabetes and cardiovascular disease. For many years, clinicians and researchers have been working to develop and use model-based methods to increase understanding and aid therapeutic decision support. However, the majority of practicable tests cannot yield more than basic metrics that allow only a threshold-based assessment of the underlying disorder. This thesis gives an overview on several dynamic model-based methodologies with different clinical applications in assessing glycaemia via measuring effects of treatment or medication on insulin sensitivity. Other tests are clinically focused, designed to screen populations and diagnose or detect the risk of developing diabetes. Thus, it is very important to observe sensitivity metrics in various clinical and research settings.