We developed a novel blood glucose control system, using a model predictive
method, to achieve optimal control of the blood glucose level in severely
diabetic or pancreatectomized patients. This system is designed to predict
glucose level changes in advance, considering delayed response time and the
administered doses of insulin. This method is also designed to calculate t
he most appropriate insulin infusion rate by considering differences in ind
ividual response to insulin. In this study, we compared our system with a c
onventional proportional and differential controller (PD controller) to det
ermine whether the new system could regulate the glucose level efficiently
in pancreatectomized dogs. The model predictive control method resulted in
a significant reduction of mean insulin infusion rate compared with the con
ventional PD controller (0.71 mU/kg per min vs. 1.81 mU/kg per min, p = 0.0
005), when the glucose level in both methods reached the planned target lev
el (100 mg/dl). The new system also tended to have a reduced mean glucose i
nfusion rate for compensating for overshooting of the glucose level compare
d with the PD controller (0.7 mg/kg per min vs. 1.1 mg/kg per min, p = 0.16
). These results indicate that the new system should be a useful tool for r
egulating the glucose level in severely diabetic patients.