Automatic Bolus and Adaptive Basal Algorithm for the Artificial Pancreatic β-Cell

Abstract

The current basal and bolus insulin pump therapy is dependent on user intervention; because of its open-loop nature, the therapy does not accommodate insulin variability and unmeasured meal disturbances. To conquer these challenges, an automatic bolus and adaptive basal (ABAB) therapy is proposed to regulate glucose levels for people with type 1 diabetes mellitus. The basal insulin profile is adjusted by the proposed algorithm every 30 min based on interstitial glucose level and its rate of change. An automated bolus is suggested by the system if a meal is detected or a hyperglycemia event occurs. A conservative insulin bolus is administered, the size of which is determined based on glucose prediction and the subject-specific correction factor. One hour later, the algorithm checks whether another bolus is needed. To prevent overdelivery, insulin-on-board is used as a safety constraint. The ABAB therapy was compared with the optimal open-loop therapy and missed-bolus scenario on 100 adult subjects from the Food and Drug Administration-accepted University of Virginia/Padova Metabolic Simulator. The ABAB therapy presented superior performance according to the control-variability grid analysis. In addition, the ABAB therapy shows excellent robustness to insulin sensitivity rise: the hypoglycemia percentage was only 3.3% even when insulin sensitivity was increased by 20%. Independent of user intervention, the ABAB therapy is a good candidate for the first generation of an artificial pancreas. The proposed therapy shows excellent robustness to insulin dosing mismatches.