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

ConditionType 1 Diabetes Mellitis

Trial statusNot yet recruiting

Trial phaseNot applicable

Trial typeInterventional

Biological sexAll

Age18+

SponsorSue Brown

About this trial

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).

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Age ≥18.0 years old at time of consent

Clinical diagnosis, based on investigator assessment, of Type 1 Diabetes (T1D) for at least one year.

Currently using an automated insulin delivery (AID) system.

Willingness to switch to use a commercially approved personal insulin (e.g., lispro or aspart, or biosimilar approved products) within the study pump as directed by the study team.

Disqualifiers

Plans to start a new non-insulin glucose-lowering agent (e.g., Glucagon-like peptide-1 (GLP-1) receptor agonists, Symlin, DPP-4 inhibitors, sulfonylureas). Participants may be on a stable dose of such an agent for at least the past month.

Current use of an sodium-glucose transport protein 2 (SGLT-2) or SGLT-1/2 inhibitor due to risk of euglycemic diabetic ketoacidosis (DKA).

Hemophilia or any other bleeding disorder.

History of severe hypoglycemic events with seizure or loss of consciousness in the last 12 months.

Trial design

Design model

Crossover

Treatments tested in this trial

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.

Treatment groups

50 Participants

are divided into 2 treatment groups

Group A: GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AIExperimental treatment 3 interventions

Group B: GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCLExperimental treatment 3 interventions

Trial outcomes

Primary outcomes

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

The last two weeks of the 4-week AIDANET AI session will be used for analysis, comparing standard Ambulatory Glucose Profile metrics across AIDANET vs AIDANET AI, with primary outcome TIR (70-180 mg/dL) during the day.

Time frame

two weeks

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Sue Brown

Lead sponsor

University of Virginia

Sponsor institution

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

Collaborator

Tandem Diabetes Care, Inc.

Collaborator

Source ClinicalTrials.gov

This trial is not recruiting at the moment. You can still explore other options: