Modeling and Control of the Cobelli Model as a Personalized Prescriptive Tool for Diabetes Treatment
Abstract
Mathematical models of glucose and insulin dynamics within the body allow for a more quantified approach in medicine prescription as well as a deeper understanding of the discrete operations of diabetes. Cobelli et. al. developed a mathematical model of glucose and insulin interactions that illustrate the dynamics from ingestion to absorption within the body. The FDA has approved this model to be a substitute for animal trials in preclinical testing due to its physiological accuracy. A physiological accurate model allows for the use of control theory to investigate applications as a personalized prescription tool. This research developed a clinically-relevant, personalized algorithm for a diabetic patient that prescribes doses of oral medications, secretagogues andor sensitizing agents, and inject insulin, slow or fast acting, based on their measured blood glucose levels. The research expanded upon Cobellis mathematical model to include the four different medications and their effects on the body at a physiological level. A cost function was also developed to be utilized with Model Predictive Control MPC to adequately choose medications for future dosing based on physiological accuracy and convenience. A proof of concept demonstrated the possibility of the use of MPC for three medication inputs to control glucose levels. This work provided a framework for data verification once clinical data is obtained.
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