Modeling glucose–insulin dynamics to evaluate healthy and diseased population characteristics in type 2 diabetes mellitus

Developing successful treatments for type 2 diabetes mellitus (T2DM) requires an understanding of the interplay between insulin and glucose. Despite progress in mathematical modeling, gaps remain in understanding key physiological transitions from healthy to diabetic states. To identify the primary variables influencing plasma glucose (PG) levels and state transitions in type 2 diabetes using the Dalla Man (DM) model. The glucose–insulin response over a 7-hour period after consuming 25 grams of glucose was modeled using the DM model. We performed population-based research, sensitivity analyses, and evaluations of beginning circumstances using a virtual group of 6000 people that reflected real population distributions (68% healthy, 14% pre-diabetes, and 18% diabetic). Sensitivity study revealed that while insulin-independent glucose utilization (Vm0) has a minor effect on PG levels, basal insulin secretion (m6) and endogenous glucose production (kp1) have a large impact. A baseline glucose level of more than 125 mg/dL indicated that a person had diabetes. The accuracy of the model was confirmed by findings from population-based studies that closely matched clinical data. The key parameters (m6 and kp1) that affect the development of type 2 diabetes are identified using the DM model, which effectively depicts the glucose–insulin dynamics. This demonstrates the model's value in T2DM research and treatment development.