Title : Mathematical Modelling of Glucose Dynamics: A Systems Biology Approach for Food and Drug Intervention
Abstract:
Type-II diabetes is one of the most prevalent lifestyle diseases in the world, and the number of diabetic patients is rising quickly. It is crucial to consider how lifestyle factors like eating habits, exercise routines, stress levels, and others affect glucose-insulin dynamics and determine whether a person will develop diabetes or not. To examine the dynamics of glucose, we have developed a mathematical model to study the dynamics of glucose. In order to describe the emergence of the disease, the parameters were grouped to produce both perfect adaptation and non-adaptive situations in which the concentrations of glucose and insulin may reach a new steady state following the perturbation. The model was bench marked with the clinical samples of Oral Glucose tolerance test (OGTT) data of over 200 individuals. A scoring system was formed with the area under the curve, peak glucose value, and extent to reach homeostasis. Parameter sensitivity analysis were performed to analyse the most impacting parameters. The model was then simulated with the sensitive parameters to observe how an individual subject might shift from a healthy to a diabetic state using the scoring system. The model was simulated with the parameters to create virtual population studies were conducted over 8000 individuals which resembles the actual global statistics data of healthy and diseased states. The pharmacokinetics of metformin and gliclazide were linked in the model in order to evaluate the impact of the medications. The model could be able to shift the diabetic population to a healthy population in accordance with clinical data. The model.
The model can tailor a diet based on the individual response to match the glycaemic index desired by a certain person to control glucose dynamics. The model can be employed to optimize the disease treatment plan and customise the dose based on the response of the patient.
Keywords: OGTT, simulation, Type-II diabetes, Mathematical model, glycaemic index
