Table of Contents
November 04, 2026
3 min read
Key takeaways:
Of people with diabetes using the twiist automated insulin delivery system, 64% achieved a time in range of 70% or higher.
Time in range was similar between type 1 and type 2 diabetes subgroups.
Most people with type 1 or type 2 diabetes achieved target continuous glucose monitoring metrics while using the twiist automated insulin delivery system, according to real-world data.
In an analysis of 4,000 people with type 1 or type 2 diabetes using twiist (Sequel Med Tech), researchers found that most users were able to achieve a time in range with glucose of 70 mg/dL to 180 mg/dL of at least 70% and a time below range with glucose less than 70 mg/dL of lower than 4%. The data, which were published in Diabetes Technology & Therapeutics, were similar to what was observed in a multicenter trial published in Diabetes Care enrolling adults with type 2 diabetes treated with insulin, according to Viral Shah, MD, professor of medicine in the division of endocrinology and metabolism and director of diabetes clinical research at Indiana University Center for Diabetes and Metabolic Diseases.
Most people with type 1 or type 2 diabetes using the twiist automated insulin delivery system achieved a target time in range of 70% or greater. Image: Adobe Stock
“The message is simple and clear — automated insulin delivery use in people with any type of diabetes on insulin therapy, either basal or multiple daily injections, improves glycemic outcomes,” Shah told Healio.
Shah and colleagues obtained data from 4,000 children and adults with type 1 or type 2 diabetes who used twiist for at least 2 weeks from April 29, 2025, to April 29, 2026 (mean age, 41 years; 57% female).
Glycemic outcomes
Viral Shah
The study group spent 97.7% of time in closed-loop mode while using the system. The overall time in range was 73.5% and the mean overnight time in range was 77.9%, according to the researchers. Among users, 64% had a time in range above 70%, 86% had a time below range with glucose less than 70 mg/dL of less than 4%, and 97% achieved a time well below range with glucose less than 54 mg/dL of less than 1%. Of the study group, 52% had a time in range of more than 70% plus a time below range of less than 4%. Mean glucose was 150.2 mg/dL and mean coefficient of variation was 34%.
Time in range and time above range with glucose of more than 250 mg/dL were similar between people with type 1 diabetes and those with type 2 diabetes. Shah said these data dispel the theory that automated insulin delivery may only benefit people with type 1 diabetes.
“I think it’s time to consider automated insulin delivery for all people with diabetes on insulin therapy, regardless of type of diabetes and other clinical characteristics,” Shah said.
Subgroup analysis
Mean time in range was within target range for all age groups except children and adolescents younger than 18 years. Glycemic outcomes were better for adults aged 65 years and older compared with people younger than 65 years. Across all age groups, at least 96% of participants had a time well below range of less than 1%.
When participants were stratified by baseline HbA1c, participants with an HbA1c of more than 8% had a 46.2% increase in time in range from before automated insulin delivery use compared with use of the system. Those with an HbA1c of 7% to 8% had a 21.7% increase in time in range, and people with a baseline HbA1c of less than 7% had an 8.7% improvement.
With data showing that automated insulin delivery can benefit a wide range of people with diabetes, the healthcare community needs to pivot toward getting more people to use the systems, Shah said.
“Many people with type 1 diabetes are not on an automated insulin delivery system and a large majority of people with type 2 diabetes are cared for in primary care settings, where use of CGM and automated insulin delivery is very low,” Shah said. “We need to educate and provide resources to our healthcare professionals so that they can implement the science in practice.”
For more information:
Viral N. Shah, MD, can be reached at shahvi@iu.edu.
Sources/Disclosures
Source:
Shah VN, et al. Diabetes Technol Ther. 2026;doi:10.1177/15209156261492055.
Reference:
Disclosures:
Shah reports advising or consulting for Abbott, Biomea Fusion, Dexcom, Eli Lilly, Insulet, Medtronic, Novo Nordisk, Roche, Sanofi, Sequel Med Tech, Tandem Diabetes Care and T1D Scout; and receiving research grants paid to his institution from Breakthrough T1D, the Cystic Fibrosis Foundation, DEKA Research, Dexcom, Enable Bioscience, Lilly, Medtronic and Zucara Therapeutics. Please see the study for all other authors’ relevant financial disclosures.
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