Ricerc@Sapienza

Despite the availability of an array of insulin formulations with different time action profiles and several treatment algorithms, the majority of patients with Type 2 Diabetes Mellitus (T2DM) on insulin therapy fails to achieve targeted glycosylated hemoglobin (HbA1c) levels.

Primary care providers, that in most country treat the majority of T2DM subjects, and patients are often reluctant in making the necessary transition from oral agents to insulin and once started to insulin dosage uptritation to achieve glycemic targets. These factors lead subjects at risk for diabetes complications.

Different clinical trials and metanalysis investigating basal insulin therapy together with the use of different treatment algorithms, either directed by the clinic/physician or by the patients themselves have consistently shown substantial improvements in glycemic control as indicated by reductions in HbA1c values together with a low number of hypoglycemic episodes.

Thus there appears to be an apparent gap between international guideline recommendations, the results of clinical trials, and real-life clinical practice as far as basal insulin initiation and treatment optimization in T2DM¿including titration algorithms¿is concerned.

In the era of personalized medicine, Continuous Glucose Monitoring (CGM) devices are showing that even in the context of T2DM, and particularly for those on insulin therapy, we face different glycemic profiles.

An option in this context is to develop a set of computational models (Virtual Patients, VPs) for T2DM subjects on basal bolus insulin therapy, clinically validate such models using CGM data and then use VPs (in lieu of real patients) within an In-Silico Clinical Trial (ISCT) aiming at assessing safety and efficacy of personalized insulin dose adjustment and frequency of adaptation (e.g., in order to achieve agreed therapeutic target) strategies.