Individualized multiple-day simulation model of type 1 diabetic patient decision-making for developing, testing and optimizing insulin therapies driven by glucose sensors

Abstract

A mathematical model of type 1 diabetes (T1D) patient decision-making can be used to simulate, in silico, realistic glucose/insulin dynamics, for several days, in a variety of subjects who take therapeutic actions (e.g. insulin dosing) driven by either self-monitoring blood glucose (SMBG) or continuous glucose monitoring (CGM). The decision-making (DM) model can simulate real-life situations and everyday patient behaviors. Accurate submodels of SMBG and CGM measurement errors are incorporated in the comprehensive DM model. The DM model accounts for common errors the patients are used to doing in their diabetes management, such as miscalculations of meal carbohydrate content, early/delayed insulin administrations and missed insulin boluses. The DM model can be used to assess in silico if/when CGM can safely substitute SMBG in T1D management, to develop and test guidelines for CGM driven insulin dosing, to optimize and individualize off-line insulin therapies and to develop and test decision support systems.

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