Type 1 Diabetes MellitisAIDANET AINCT07517770
Effectiveness of Artificial-Intelligence (AI) Bolus Priming Added to an Existing Fully Automated Control Algorithm (AIDANET)
A study testing Hybrid Closed Loop (HCL) x 2 weeks, AIDANET x 2 weeks and AIDANET AI x 4 weeks in people with Type 1 Diabetes Mellitis, run by Sue Brown at 1 site in United States.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Type 1 Diabetes Mellitis
- What is being tested?
- Hybrid Closed Loop (HCL) x 2 weeks, AIDANET x 2 weeks and AIDANET AI x 4 weeks
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteUnited States
- Study dates
- 1 May 2026to 30 Apr 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
- Has one or more supportive companions knowledgeable about emergency procedures for severe hypoglycemia and able to contact emergency services and study staff that either live with participant or located within approximately 30 minutes of participant and able to locate participant in the event of an emergency.
- Participant not currently known to be pregnant or breastfeeding.
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- If participant can become pregnant, they must agree to use a form of contraception to prevent pregnancy while a participant in the study. A negative serum or urine pregnancy test will be required for all females of childbearing potential. Participants who become pregnant will be discontinued from the study. Also, participants who during the study develop and express the intention to become pregnant within the timespan of the study will be discontinued.
- Willingness to use the study AIDANET system (CGM, insulin pump, and phone) during the study period.
- Willingness not to start any new non-insulin glucose-lowering agent during the course of the trial.
- Willingness to participate in all study procedures.
- Access to internet at home and willingness to upload data during the study as needed.
- Investigator has confidence that the participant can successfully operate all study devices and is capable of adhering to the protocol.
- Participant is proficient in reading and writing English.
Who cannot join
- 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.
- History of DKA event in the last 12 months.
- Unstable Stage 4 chronic renal disease or currently on peritoneal or hemodialysis.
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- Currently being treated for adrenal insufficiency.
- Currently being treated for a seizure disorder.
- Hypothyroidism or hyperthyroidism that is not adequately treated.
- Use of oral or injectable steroids at the time of enrollment or within the last 2 weeks.
- Planned surgery during the study period that results in prolonged disconnection from study devices.
- Known ongoing adhesive intolerance that is not well managed.
- A condition, which in the opinion of the investigator or designee, would put the participant or study at risk.
- Participation in another interventional trial at the time of enrollment.
- Participant with a direct supervisor involved in the conduct of the trial.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site
University of Virginia Center for Diabetes Technology
Charlottesville, Virginia, 22903
Sue Brown, MD, 4349820602, sab2f@uvahealth.org
Boris Kovatchev, PhD
About this study
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).
Read the detailed description
A randomized cross-over trial assessing glycemic control on AIDANET equipped with its standard bolus vs AIDANET AI. A secondary comparison of AIDANET AI vs a current commercial Hybrid Closed Loop (HCL) system is planned as well.
Following enrollment and screening, participants will be randomized 1:1 to two 8-week sequences: Group A participants will continue to use their home Hybrid closed loop (HCL) system for 2 weeks, then switch to AIDANET for two weeks, and the switch to AIDANET AI for another 4 weeks. 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 (Figure 1). The last two weeks of the 4-week AIDANET AI session will be used for analysis, comparing standard Ambulatory Glucose Profile (AGP) metrics across AIDANET vs AIDANET AI, with primary outcome Time in Range (TIR) (70-180 mg/dL) during the day. Secondary analyses will compare AIDANET AI 2-week AGP to HCL AGP metrics. Both analyses use randomized crossover design.
- Conditions
- Type 1 Diabetes Mellitis
- Being tested
- Hybrid Closed Loop (HCL) x 2 weeks, AIDANET x 2 weeks, AIDANET AI x 4 weeks
- Keywords
- Type 1 Diabetes (T1D), Artificial-Intelligence (AI), Hybrid Closed Loop (HCL), Fully Closed Loop (FCL), Mobi insulin pump, iPhone Diabetes Assistant (iDiAs), Automated insulin delivery as Adaptive Network (AIDANET) algorithm, Bolus Priming System (BPS), Mobi Research App (MRA)
- Medical subject headings
- Diabetes Mellitus, Type 1
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Hybrid Closed Loop (HCL) x 2 weeksDevice
During the HCL session, participants will be using their own HCL systems for 2-weeks.
AIDANET x 2 weeksDevice
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 weeksDevice
Participant will use the AIDANET algorithm with the addition of the Bolus Priming (BP) based on AI learning of meal patterns.
| Study group | Role | What they receive |
|---|---|---|
| GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AI | Experimental | 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. Receives: Device: Hybrid Closed Loop (HCL) x 2 weeks; Device: AIDANET x 2 weeks; Device: AIDANET AI x 4 weeks |
| GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCL | Experimental | 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 Receives: Device: Hybrid Closed Loop (HCL) x 2 weeks; Device: AIDANET x 2 weeks; Device: AIDANET AI x 4 weeks |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: two weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Apr 2026
- Study start1 May 2026 (estimated)
- Primary completion30 Apr 2027 (estimated)
- Study completion30 Apr 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Type 1 Diabetes MellitisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- None (open label)
- Enrolment
- 50 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Sue Brown
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Tandem Diabetes Care, Inc.
- Responsible party
- Sponsor-investigator, Sue Brown, University of Virginia
- Investigators
- Sue Brown, MD, Principal investigator, University of Virginia Center for Diabetes Technology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07517770
- Sponsor's protocol ID
- 303428
- Other IDs
- R01DK133148
- Acronym
- AIDANET AI
- Status last verified
- Apr 2026
- First submitted
- 30 Mar 2026
- Last updated
- 8 Apr 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 8 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effectiveness of Artificial-Intelligence (AI) Bolus Priming Added to an Existing Fully Automated Control Algorithm (AIDANET)
- ClinicalTrials.gov ID
- NCT07517770
- Acronym / sponsor ID
- AIDANET AI / 303428
- Conditions
- Type 1 Diabetes Mellitis
- Keywords
- Type 1 Diabetes (T1D), Artificial-Intelligence (AI), Hybrid Closed Loop (HCL), Fully Closed Loop (FCL), Mobi insulin pump, iPhone Diabetes Assistant (iDiAs), Automated insulin delivery as Adaptive Network (AIDANET) algorithm, Bolus Priming System (BPS)
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 50 participants (estimated)
- Lead sponsor
- Sue BrownUniversity, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Tandem Diabetes Care, Inc.
- Study start
- 1 May 2026 (estimated)
- Primary completion
- 30 Apr 2027 (estimated)
- Study completion
- 30 Apr 2027 (estimated)
- First posted
- 8 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
Detailed description
A randomized cross-over trial assessing glycemic control on AIDANET equipped with its standard bolus vs AIDANET AI. A secondary comparison of AIDANET AI vs a current commercial Hybrid Closed Loop (HCL) system is planned as well.
Following enrollment and screening, participants will be randomized 1:1 to two 8-week sequences: Group A participants will continue to use their home Hybrid closed loop (HCL) system for 2 weeks, then switch to AIDANET for two weeks, and the switch to AIDANET AI for another 4 weeks. 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 (Figure 1). The last two weeks of the 4-week AIDANET AI session will be used for analysis, comparing standard Ambulatory Glucose Profile (AGP) metrics across AIDANET vs AIDANET AI, with primary outcome Time in Range (TIR) (70-180 mg/dL) during the day. Secondary analyses will compare AIDANET AI 2-week AGP to HCL AGP metrics. Both analyses use randomized crossover design.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AI | Experimental | Device: Hybrid Closed Loop (HCL) x 2 weeks, Device: AIDANET x 2 weeks, Device: AIDANET AI x 4 weeksGroup 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. |
| GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCL | Experimental | Device: Hybrid Closed Loop (HCL) x 2 weeks, Device: AIDANET x 2 weeks, Device: AIDANET AI x 4 weeksGroup 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 |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (13 listed)
- 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.
- Has one or more supportive companions knowledgeable about emergency procedures for severe hypoglycemia and able to contact emergency services and study staff that either live with participant or located within approximately 30 minutes of participant and able to locate participant in the event of an emergency.
Key exclusion criteria (15 listed)
- 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.
- History of DKA event in the last 12 months.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Hybrid Closed Loop (HCL) x 2 weeksDuring the HCL session, participants will be using their own HCL systems for 2-weeks. | Device | GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AI, GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCL |
| AIDANET x 2 weeksParticipant 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. | Device | GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AI, GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCL |
| AIDANET AI x 4 weeksParticipant will use the AIDANET algorithm with the addition of the Bolus Priming (BP) based on AI learning of meal patterns. | Device | GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AI, GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCL |
Primary outcome
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
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Apr 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Sue Brown, MD principal investigator
University of Virginia Center for Diabetes Technology
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Hybrid Closed Loop (HCL) x 2 weeks, AIDANET x 2 weeks and AIDANET AI x 4 weeks in people with Type 1 Diabetes Mellitis, run by Sue Brown at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 13 inclusion and 15 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 8 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Carlene Alix (434-249-8961, UAX8YX@uvahealth.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the 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). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Apr 2026.