Effectiveness of Artificial-Intelligence (AI) Bolus Priming Added to an Existing Fully Automated Control Algorithm (AIDANET)

Part of paid clinical trials in Charlottesville, Virginia.

Sponsor
Sue Brown
Study ID
NCT07517770
Status
Not Yet Recruiting

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Conditions

  • Type 1 Diabetes Mellitis

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Hybrid Closed Loop (HCL) x 2 weeks — DEVICE
    During the HCL session, participants will be using their own HCL systems for 2-weeks.
  • AIDANET x 2 weeks — DEVICE
    Participant will use the AIDANET algorithm on the Mobi system with the standard Bolus Priming System (BPS) automated bolus that does not require announcement of meals.
  • AIDANET AI x 4 weeks — DEVICE
    Participant will use the AIDANET algorithm with the addition of the Bolus Priming (BP) based on AI learning of meal patterns.

Study Details

Bolus Priming (BP) based on Artificial Intelligence (AI) learning of meal patterns, added to our established Automated insulin delivery as Adaptive Network (AIDANET) algorithm and running on iPhone Diabetes Assistant (iDiAs) phone wirelessly connected to Tandem Mobi insulin pump and Dexcom Continuous Glucose Monitor (CGM).

Key Dates

Start date
May 1, 2026
Status verified
Apr 2026
Primary completion
Apr 30, 2027
Completion
Apr 30, 2027

Study Design

Enrollment
50 participants (estimated)
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT

Arms

  • Experimental: GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AI
    Group A participants will continue to use their home HCL system for 2 weeks, then switch to AIDANET for two weeks, and the switch to AIDANET AI for another 4 weeks.
  • Experimental: GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCL
    Group B participants will begin with 4 weeks of AIDANET AI, then switch to AIDANET for 2 weeks and then revert to their home HCL systems for the last 2 weeks of the study

Primary Outcome Measure

Time in Range (TIR) 70-180 mg/dL for 2-week free-living at home periods on AIDANET vs AIDANET AI. [ Time Frame: two weeks ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
University of Virginia Center for Diabetes TechnologyCharlottesvilleVirginia22903
Sue Brown, MD
[email protected]
4349820602
Boris Kovatchev, PhD (SUB_INVESTIGATOR)
Marc Breton, PhD (SUB_INVESTIGATOR)
Anas El Fathi, PhD (SUB_INVESTIGATOR)
Kimberly Driscoll, PhD (SUB_INVESTIGATOR)
Samina Afreen, MD (SUB_INVESTIGATOR)
Mark DeBoer, MD (SUB_INVESTIGATOR)
Meryem Karagoz, PhD (SUB_INVESTIGATOR)

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By research site
University of Virginia Center for Diabetes Technology· Charlottesville, VA

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