Trial results for the Automated Insulin Delivery as Adaptive NETwork (AIDANET) system in Type 1 Diabetes were posted on 2025-08-14, showing a mean continuous glucose monitor (CGM) reduction of -6.8 miligrams per deciliter (Standard Deviation 15.1) for participants in the Usual Care→AIDANET crossover group.
Background
Type 1 Diabetes (T1D) is an autoimmune condition requiring lifelong insulin therapy and diligent glucose monitoring to maintain blood sugar levels within a healthy range. Managing T1D can be complex and burdensome, often involving multiple daily insulin injections or an insulin pump, alongside frequent blood glucose checks or continuous glucose monitoring (CGM). Automated insulin delivery (AID) systems, also known as artificial pancreas systems, aim to reduce this burden by automating insulin delivery based on CGM readings. These systems are designed to improve glycemic control, reduce the risk of hypoglycemia and hyperglycemia, and enhance the quality of life for individuals with T1D.
Trial design
This completed study, identified as Phase NA, was a randomized 1:1 crossover trial that enrolled 8 adult participants with Type 1 Diabetes. The trial's primary objective was to demonstrate the feasibility and safety of a new, smaller network version of the Automated Insulin Delivery as Adaptive NETwork (AIDANET) system, used in a full closed-loop (FCL) configuration. The study compared the AIDANET system used at home with participants' usual care routines.
Key results
The trial reported several key measurements related to glucose control:
- For the outcome “Change in the Mean Continuous Glucose Monitor (CGM) Between the Week of the Usual Care Observational Period and the Week of AIDANET At-Home.”:
- In the group transitioning from Usual Care to AIDANET, the mean change was -6.8 (Standard Deviation 15.1) miligrams per deciliter.
- In the group transitioning from AIDANET to Usual Care, the mean change was -2.1 (Standard Deviation 20.7) miligrams per deciliter.
- For the outcome “Difference in Percent Time-in-range”:
- In the group transitioning from Usual Care to AIDANET, the mean difference was 1.55 (Standard Deviation 4.34) percentage of time-in-range.
- In the group transitioning from AIDANET to Usual Care, the mean difference was 2.76 (Standard Deviation 10.6) percentage of time-in-range.
- For the outcome “Difference in Percent Time-below-range”:
- In the group transitioning from Usual Care to AIDANET, the mean difference was 0.93 (Standard Deviation 2.10) percentage of time-below-range.
- In the group transitioning from AIDANET to Usual Care, the mean difference was 0.06 (Standard Deviation 0.45) percentage of time-below-range.
- For the outcome “Difference in Percent Time-in-tight-range”:
- In the group transitioning from Usual Care to AIDANET, the mean difference was 1.69 (Standard Deviation 10.71) percentage of time-in-tight-range.
- In the group transitioning from AIDANET to Usual Care, the mean difference was 4.01 (Standard Deviation 7.19) percentage of time-in-tight-range.
What this means
The results from this small feasibility study suggest that the AIDANET system may offer improvements in glycemic control for adults with Type 1 Diabetes. The observed reduction in mean CGM levels and the increases in time-in-range and time-in-tight-range, alongside a decrease in time-below-range, indicate a favorable impact on glucose management. While these findings are from a limited number of participants and primarily address feasibility and safety, they point towards the potential benefits of the AIDANET system in helping individuals with T1D achieve better and safer glucose control in a home setting. Further research with larger cohorts would be needed to confirm these preliminary observations and establish broader clinical efficacy.
Source
The information regarding these trial results was obtained from ClinicalTrials.gov, a public database of clinical studies. The results for the study NCT06633965, titled "Safety and Feasibility Testing of a Smaller Network Version of AIDANET", were posted on 2025-08-14 on clinicaltrials.gov.