Intraoperative glycemic control, particularly in cardiac surgical patients, remains challenging. Patients with impaired insulin sensitivity and/or secretion (i.e., type 1 diabetes mellitus) often manifest extremely labile blood glucose measurements during periods of stress and inflammation. Most current insulin infusion protocols are developed based on clinical experiences and consensus among a local group of physicians. Recent advances in human glucose metabolism modeling have established a computer model that invokes algorithms representing many of the pathways involved in glucose dysregulation for patients with diabetes. In this study, we used an FDA approved glucose metabolism model to evaluate an existing institutional intraoperative insulin infusion protocol via closedloop simulation on the virtual diabetic population that comes with the computer model. A comparison of simulated responses to actual retrospective clinical data from 57 type 1 diabetic patients undergoing cardiac surgery managed by the institutional protocol was performed. We then designed a proportional-derivative controller that overcomes the weaknesses exhibited by our old protocol while preserving its strengths. In-silico evaluation results show that our proportional-derivative controller more effectively manages intraoperative hyperglycemia while simultaneously reducing hypoglycemia and glycemic variability. By performing insilico simulation on intraoperative glucose and insulin responses, robust and seemingly efficacious algorithms can be generated that warrant prospective evaluation in human subjects.