Abstract Continuous glucose monitoring (CGM) is widely used in type 1 diabetes management. Although less common in type 2 diabetes (T2D), its application is increasing, especially among patients with T2D on insulin therapy. CGM provides detailed, continuous glucose data that reveal daily glycemic fluctuations and help mitigate hyper- and hypoglycemic episodes. However, missing information on meal size and timing complicates the interpretation of data. To address these challenges, we propose a pharmacometric modeling approach that describes blood glucose profiles in patients with T2D receiving basal insulin in the absence of exact meal inputs. In this study, 73 individuals with T2D receiving insulin glargine plus oral antidiabetic medications (OAMs) underwent CGM assessments at four visits (Visit 3 on OAMs alone; Visits 13, 16, 20 on OAMs + insulin). Building upon the existing Integrated Glucose-Insulin (IGI) model, we incorporated a population meal model and an insulin glargine pharmacokinetic model, creating a comprehensive "meal–IGI–insulin" framework. The model identified three daily meal intakes, modeled as the sum of a surge function and a maximum bioavailable glucose amount of 7.83 g/hour. The model evaluation indicated adequate performance in predicting fasting blood glucose and HbA1c, though some discrepancies arose in forecasting hypoglycemic events. The developed modeling framework can facilitate prospective simulations of diverse meal patterns and insulin regimens, potentially accelerating antidiabetic drug development, simplify closed-loop automated insulin delivery algorithms, and optimize clinical strategies for patients with T2D. Graphical Abstract
Kunina et al. (Wed,) studied this question.