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ABSTRACT Aims Achieving optimal glycaemic control remains a burden for many people with diabetes on intensive insulin treatment. The MELISSA trial aims to clinically validate the artificial intelligence (AI)‐based MELISSA system to support people with Type 1 diabetes on multiple daily insulin injections (MDI) with personalised insulin dose recommendations and an innovative approach for automatic carbohydrate estimation. In addition, feasibility will be explored in people with Type 2 diabetes. Materials and Methods The MELISSA trial is a 22‐week European multicentre, prospective randomised open‐label blinded endpoint trial including people with Type 1 ( n = 278) and an exploratory cohort of people with Type 2 diabetes ( n = 50) on MDI. The MELISSA system consists of two AI‐driven features: an adaptive basal‐bolus advisor (ABBA), which can be supported by an automated dietary assessment system, goFOOD TM . ABBA provides personalised suggestions for basal insulin and mealtime insulin doses, while goFOOD TM converts food images into carbohydrate content estimations. After the initialisation period (Weeks 0–6), participants will be randomised 1:1 to either the MELISSA system or the continuation of usual care. Results The primary endpoint is the between‐group change in percentage of time spent in the target range (3.9–10.0 mmol/L 70–180 mg/dL) from baseline to study end. Secondary outcomes include additional glycaemic metrics, patient‐reported‐outcomes, and safety information. The trial was approved by the Sponsor's Medical Ethics Research Committee (NL‐009099). Conclusion The MELISSA system will potentially improve glycaemic control and quality of life in people with Type 1 diabetes on MDI. The trial outcomes will provide necessary input for obtaining Conformité Européenne certification (class IIb) for the MELISSA system.
Brok et al. (Tue,) studied this question.