GIM, simulation software of meal glucose-insulin model

Abstract

Background: A simulation model of the glucose-insulin system in normal life conditions can be very useful in diabetes research, e.g., testing insulin infusion algorithms and decision support systems and assessing glucose sensor performance and patient and student training. A new meal simulation model has been proposed that incorporates state-of-the-art quantitative knowledge on glucose metabolism and its control by insulin at both organ/tissue and whole-body levels. This article presents the interactive simulation software GIM (glucose insulin model), which implements this model.

Methods: The model is implemented in MATLAB, version 7.0.1, and is designed with a windows interface that allows the user to easily simulate a 24-hour daily life of a normal, type 2, or type 1 diabetic subject. A Simulink version is also available. Three meals a day are considered. Both open- and closed-loop controls are available for simulating a type 1 diabetic subject.

Results: Software options are described in detail. Case studies are presented to illustrate the potential of the software, e.g., compare a normal subject vs an insulin-resistant subject or open-loop vs closed-loop insulin infusion in type 1 diabetes treatment.

Conclusions: User-friendly software that implements a state-of-the-art physiological model of the glucose-insulin system during a meal has been presented. The GIM graphical interface makes its use extremely easy for investigators without specific expertise in modeling.

Keywords: artificial pancreas; diabetes; glucose homeostasis; glucose sensors; insulin infusion system; modeling; physiological control.

Figure 1.

Scheme of the glucose–insulin control system. Continuous lines denote fluxes of material and dashed lines control signals. In addition to plasma glucose and insulin concentration measurements, glucose fluxes (i.e., meal rate of appearance, production, utilization, and renal extraction) and insulin fluxes (i.e., secretion and degradation) are also shown (see text).

Figure 2.

The dialog box allows the user to select the status of the subject: Normal, Type 2 Diabetic, or Type 1 Diabetic.

Figure 3.

Normal (top) and Type 2 Diabetic (bottom) windows. Each window is divided into three sections that allow the user to set basal values of glucose concentration, insulin concentration, and glucose production (glucose clearance is calculated and displayed in the proper square); to enter values of body weight and main metabolic indices, such as peripheral and hepatic insulin sensitivity, static, and dynamic beta-cell responsivity to glucose (as percentage of normal values); and to define the time of the three meals and the amount of glucose ingested. The window also shows buttons to start simulation, save the simulated profiles, or run a new subject.

Figure 4.

Simulation results of a normal subject. Glucose and insulin concentrations, glucose production, glucose utilization, meal rate of appearance, and insulin secretion rate are obtained with settings of Figure 3 (top).

Figure 5.

The Save Profiles window allows one to name the .mat file containing the saved solutions and to place it in the desired folder.

Figure 6.

The Type1 Diabetic window is divided into four sections that allow the user to set basal values of glucose concentration, insulin concentration, and glucose production (glucose clearance is calculated and displayed in the proper square); to enter values of body weight and main metabolic indices, such as peripheral and hepatic insulin sensitivity (as percentage of normal values); to select if the subject is controlled in a open (left) or closed loop with a PID controller (right); and to define the time of the three meals, the amount of glucose ingested, and, in case of open-loop control, the insulin dose injected before each meal. The window also shows buttons to start simulation, save the simulated profiles, or run a new subject.

Figure 7.

Simulation results of a normal subject vs an insulin-resistant subject. Glucose and insulin concentrations, glucose production, glucose utilization, meal rate of appearance, and insulin secretion rate obtained with settings of Figure 3 (top)(blue line) are superimposed on those obtained with the same setting but 70% lower insulin sensitivity indices (red line).

Figure 8.

Simulation results of a type 1 diabetic subject controlled in an open loop. Glucose and insulin concentrations, glucose production, glucose utilization, meal rate of appearance, and insulin appearance obtained with settings of Figure 6 (left) (blue line) are superimposed on those obtained in the same subject who forgot to inject insulin before lunch (red line).

Figure 9.

Simulation results of a type 1 diabetic subject controlled in a closed loop with a PID controller. Glucose and insulin concentrations, glucose production, glucose utilization, meal rate of appearance, and insulin infusion are obtained with settings of Figure 6 (right). Hypoglycemia (red) and hyperglycemia (green line) thresholds are also displayed.