Limitations and Potential of Automated Insulin Delivery Devices in Type 1 Diabetes

Automated insulin delivery (AID) systems, such as the artificial pancreas developed by University of Virginia Health, could provide significant benefit to patients with type 1 diabetes (T1D) if they become fully automated.1

According to a review of the technology published by the University of Virginia Health System, the artificial pancreas and other AID systems have already helped millions of patients with T1D manage their blood sugar and improve overall healthcare. However, the authors noted several limitations which remain to be worked out.1

“These automated insulin delivery devices have significantly helped people with type 1 diabetes manage their blood sugars and yet challenges still remain – people still need to remember to give insulin for meals as well as carbohydrate counts,” Sue Brown, MD, an endocrinologist and researcher at the University of Virginia Center for Diabetes and Technology and co-author of the technology review, said in a statement. “These newer approaches can help alleviate those requirements and we are hopeful that we can make insulin management even easier for people with type 1 diabetes.”1

The first listed limitation is the hybrid nature of current “automated” AID systems, which typically require patients to enter carbohydrate content before beginning a meal. Meal protein content does have a dose-dependent effect, and fat content can increase insulin resistance, as well as causing late hyperglycemia and early hypoglycemia. The majority of AID systems do not account for meal composition into insulin dosing models.2

To this end, the authors encourage future work to combine strategies such as simplifying carbohydrate entry, developing more ultra rapid-acting insulin formulation, and creating meal detection algorithms integrated with meal composition models and adjunctive therapies.2

Another mentioned limitation involves the common activity/exercise mode in many AID devices. Again, these require users to initiate the program well before beginning exercise. Current clinical guidelines on exercise in AID systems encourage the use of higher temporary targets in advance of exercise; however, these and other hypoglycemia mitigation techniques are not frequently used among individuals with T1D who exercise regularly.2

Given the high likelihood of activity-induced hyperglycemia after intensive exercise, resistance training, or competition stress, authors note the necessity for more AID systems to develop management strategies for this condition. Some proof-of-concept AID devices can accurately distinguish between certain forms of exercise and alter insulin delivery automatically – however, the need for improving glucose time-in-range outcomes during and following exercise is another major limitation for AID.2

The researchers also highlighted the need for accessibility and simplification of these technologies, suggesting the utilization of advancements in artificial intelligence to streamline the mechanics behind insulin monitoring and delivery.1

“While AID has revolutionized diabetes care, most patients using insulin do not yet have access to such technology,” Marc Breton, PhD, associate professor of research at the UVA Center for Diabetes Technology and co-author of the review, said in a statement. “Simplifying the use of these systems will greatly improve access. UVA is at the forefront of another revolution: the use of artificial intelligence and data science at the very core of medical devices.”1

References

1. University of Virginia Health System. AI, full automation could expand artificial pancreas to more diabetes patients. Eurekalert! August 19, 2025. Accessed September 10, 2025. https://www.eurekalert.org/news-releases/1095082

2. Jacobs PG, Levy CJ, Brown SA, et al. Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems. J Diabetes Sci Technol. 2025;19(4):937-949. doi:10.1177/19322968251338754