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Safety and Feasibility of a Machine-Learning Bolus Priming Added to Existing Control Algorithm

Safety and Feasibility of a Machine-Learning Bolus Priming Added to Existing Control Algorithm

Status
Completed
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06728059
Acronym
AIDANET+BPS_RL
Enrollment
19
Registered
2024-12-11
Start date
2025-02-05
Completion date
2025-05-14
Last updated
2026-05-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Type 1 Diabetes

Keywords

Type 1 Diabetes, Automated insulin delivery as Adaptive Network (AIDANET), Diabetes Assistant (DiAs), Fully Closed-Loop, Bolus Priming System (BPS), Remote Learning (RL), Continuous Glucose Monitor (CGM)

Brief summary

A randomized crossover trial assessing glycemic control using Reinforcement Learning trained Bolus Priming System (BPS\_RL) added to the the Automated Insulin Delivery as Adaptive NETwork (AIDANET algorithm) compared to the original AIDANET algorithm.

Detailed description

After receiving training on the study equipment, participants will use the AIDANET system at home for 7 days/6 nights to establish a baseline and initialize the control algorithm. Participants will then be studied at a hotel session for 3 days/2 nights. Participants will transition to home use of AIDANET+ BPS\_RL for 7 days/6 nights.

Interventions

DEVICEAutomated Insulin Delivery Adaptive NETwork (AIDANET)

Group A participants will use the AIDANET system at home for 7 days/6 nights. They will continue use of AIDANET system for 18 hours during the hotel session and then use AIDANET+BPS\_RL for 18 hours during the hotel session.

DEVICEAIDANET+ BPS_RL→AIDANET

Group B participant will use the AIDANET+BPS\_RL system for 18 hours during the hotel session and will then use AIDANET system for 18 hours during the hotel session. They will continue to use AIDANET+BPS\_RL system at home for 7 days/6 night and then use the AIDANET system at home for 7 days/6 nights.

Sponsors

Sue Brown
Lead SponsorOTHER
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
CollaboratorNIH
DexCom, Inc.
CollaboratorINDUSTRY

Study design

Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT
Masking
NONE

Intervention model description

This is a research study about the UVA Automated Insulin Delivery System known as Adaptive NETwork (AIDANET). This system consists of a Reinforcement Learning trained Bolus Priming System (BPS\_RL) added to the AIDANET algorithm and running on Diabetes Assistant (DiAs) phone wirelessly connected to Tandem t:AP insulin pump and Dexcom Continuous Glucose Monitor (CGM). One part of the algorithm, called the Bolus Priming System (BPS), gives insulin automatically to help keep blood sugar levels in a healthy range. In this study, the Bolus Priming System is being tested in a new way. This system uses a type of smart learning called reinforcement learning (RL), which helps the algorithm make better choices about how much insulin to give. The new version of the system looks at blood sugar and insulin levels over the past 3 days to find patterns and give a better insulin dose before meals. This should provide an improvement over the old system, which only uses the last 30 minutes of data.

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

1. Age ≥18.0 years old at time of consent 2. Clinical diagnosis, based on investigator assessment, of Type 1 Diabetes for at least one year. 3. Having used an AID system equipped with Dexcom G6 or G7 CGM within the last three months (does not need to be continuous use if CGM was unavailable for instance). 4. Currently using insulin for at least six months. 5. 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. 6. Has one or more supportive companions knowledgeable about emergency procedures for severe hypoglycemia and able to contact emergency services and study staff that either lives with participant or located within approximately 30 minutes of participant and able to locate participant in the event of an emergency. 7. Participant not currently known to be pregnant or breastfeeding. 8. If participant capable of becoming pregnant, must agree to use a form of contraception to prevent pregnancy while a participant in the study (e.g. hormonal contraception, abstinence from heterosexual intercourse). 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. 9. Willingness to use the study AIDANET system (CGM, pump, and phone) during the study period. 10. Willingness not to start any new non-insulin glucose-lowering agent during the course of the trial. 11. Willingness to participate in all study procedures including the house/hotel sessions. 12. Access to internet at home and willingness to upload data during the study as needed. 13. Investigator has confidence that the participant can successfully operate all study devices and is capable of adhering to the protocol. 14. Participant is proficient in reading and writing English.

Exclusion criteria

1. Plans to start a new non-insulin glucose-lowering agent (e.g., 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. 2. Current use of an SGLT-2 or SGLT-1/2 inhibitor due to risk of euglycemic DKA. 3. Hemophilia or any other bleeding disorder. 4. History of severe hypoglycemic events with seizure or loss of consciousness in the last 12 months. 5. History of DKA event in the last 12 months. 6. Stage 4 chronic renal disease or currently on peritoneal or hemodialysis. 7. Currently being treated for adrenal insufficiency. 8. Currently being treated for a seizure disorder. 9. Hypothyroidism or hyperthyroidism that is not adequately treated. 10. Use of oral or injectable steroids at the time of enrollment or within the last 4 weeks. 11. Planned surgery during the study period. 12. Known ongoing adhesive intolerance that is not well managed. 13. A condition, which in the opinion of the investigator or designee, would put the participant or study at risk. 14. Participation in another interventional trial at the time of enrollment. 15. Participant with a direct supervisor involved in the conduct of the trial.

Design outcomes

Primary

MeasureTime frameDescription
CGM-measured Time in Range (TIR, 70-180 mg/dL) During the 18-hour Hotel Sessions.36 hours total (18 hours for Group A and 18 hours for Group B)CGM-measured time in range (TIR, 70-180 mg/dL) during the 18-hour hotel sessions on AIDANET or AIDANET+BPS\_RL. The time periods begin at 6 PM and end at noon on the next day, thereby covering two meals - dinner and breakfast.

Secondary

MeasureTime frameDescription
CGM-measured Time Below Range <70mg/dL During Hotel Session18 hoursCGM-measured Time below range \<70mg/dL during the 18-hour hotel session on AIDANET or AIDANET+BPS\_RL
CGM-measured Time in Range (70-180 mg/dL) for At-home7 daysCGM-measured Time in range (70-180 mg/dL) for at-home sessions using AIDANET
CGM-measured Time Below Range 70 mg/dL for At-home1 weekCGM-measured Time below range 70 mg/dL for at-home sessions using AIDANET or AIDANET BPS-RL

Countries

United States

Contacts

PRINCIPAL_INVESTIGATORSue Brown, MD

University of Virginia

Participant flow

Recruitment details

Three participants were determined to be ineligible. One withdrew before randomization.

Baseline characteristics

Characteristic
Age, Categorical
<=18 years
0 Participants
Age, Categorical
>=65 years
1 Participants
Age, Categorical
Between 18 and 65 years
14 Participants
Age, Continuous44.1 Years
STANDARD_DEVIATION 11.8
Ethnicity (NIH/OMB)
Hispanic or Latino
1 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
8 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants
Race (NIH/OMB)
Asian
0 Participants
Race (NIH/OMB)
Black or African American
1 Participants
Race (NIH/OMB)
More than one race
0 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants
Race (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
White
7 Participants
Region of Enrollment
United States
7 Participants
Sex: Female, Male
Female
4 Participants
Sex: Female, Male
Male
4 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 150 / 15
other
Total, other adverse events
0 / 150 / 15
serious
Total, serious adverse events
0 / 150 / 15

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: May 29, 2026