Diabetes technology

First in Human Feasibility Study: Automated Insulin Delivery Utilizing a Self-Adapting Algorithm in Adults With Type 1 and Type 2 Diabetes

J Diabetes Sci TechnolPublished Single-arm feasibility study

Authors' conclusion

A closed-loop algorithm that adjusts its own parameters and requires no meal announcement was feasible in a cohort of adults with type 1 and type 2 diabetes. Clinical benefits were most apparent with the fully adapted algorithm.

Study context

Population
Adults with T1D and T2D using a novel self-adapting closed-loop system that does not require carbohydrate announcementenrolled
Participants
32 vs 10
Comparison
Self-adapting closed-loop system without carbohydrate announcement (12 weeks) vs usual insulin therapy run-in (baseline)
  • T1Dn = 32
  • T2Dn = 10
Outcome
TIR (% CGM readings 70-180 mg/dL), baseline vs intervention period
Follow-up
12 weeks
Methodological detailsfirst in human, 14-day run-in with blinded continuous glucose monitor (CGM), Algorithm adjusted its own parameters after 4, 6, 8, and 10 weeks of use
  • First in human
  • 14-day run-in with blinded CGM
  • Algorithm adjusted its own parameters after 4, 6, 8, and 10 weeks of use

Main finding

As reported in the abstract

TIR (% CGM readings 70-180 mg/dL), baseline vs intervention period · 12 weeks T1D mean 55.9% · T2D mean 51.5%

Baseline

Further findings

Median daily insulin delivered by manual bolus · consistent with no meal announcement

Time in range (TIR) following the fourth algorithm adaptation

Median TIR following the fourth algorithm adaptation
65%

Safety

Median

OutcomeT1DT2D
Time <70 mg/dL during intervention period1.1%0.0%

Serious adverse events

Serious adverse events
4
Worsening retinopathy
1
Severe hypoglycemia following a period of paused automation
1
Hospitalizations unrelated to the device
2

Original publication

First in Human Feasibility Study: Automated Insulin Delivery Utilizing a Self-Adapting Algorithm in Adults With Type 1 and Type 2 Diabetes. J Diabetes Sci Technol. Published 3 July 2025. doi:10.1177/19322968251349528

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