Automated Insulin Delivery for Type 1 Diabetes

(NOMAD Trial)

Automated insulin delivery (AID) systems are the current gold standard for the management of type 1 diabetes (T1D), improving glycemic control, reducing hypoglycemia, and decreasing treatment burden. Although both commercial AID (C-AID) and open-source AID (OS-AID) systems have demonstrated significant clinical benefits, direct randomized comparisons between these systems remain scarce. Moreover, an important limitation of currently available AID systems is their reliance on user-initiated meal announcements and carbohydrate counting, which remain major contributors to postprandial dysglycemia and treatment burden. While emerging evidence suggests that AID systems may partially compensate for missed meal announcements, their comparative performance under these challenging real-world conditions is unknown.

The NOMAD study is an international, multicenter, open-label, randomized, non-inferiority crossover trial designed to compare an open-source AID system with commercially available AID systems (including Tandem Control-IQ and Omnipod 5) in adults with type 1 diabetes currently using an open-source AID system. The study specifically evaluates glycemic outcomes following standardized unannounced meal challenges performed under free-living conditions.

A total of 33 participants will be enrolled and complete two 4-week intervention periods, each consisting of a 2-week run-in phase followed by a 2-week data collection phase, with crossover between treatment arms. Participants will continue using their own Dexcom G6 or Dexcom G7 continuous glucose monitoring system throughout the study.

The primary outcome is the percentage of time spent in the target glucose range (3.9-10.0 mmol/L) during the 4 hours following standardized unannounced meal challenges. Secondary outcomes include additional CGM metrics (time above and below range, glucose variability, mean glucose, and GMI), insulin delivery characteristics, and patient-reported outcomes evaluating treatment satisfaction, usability, and diabetes-related burden.