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Neural-net Artificial Pancreas (NAP)

Adaptive Motif-Based Control (AMBC): Pilot 1 - Neural Net Implementation of Automated Insulin Delivery

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05876273
Acronym
NAP
Enrollment
15
Registered
2023-05-25
Start date
2023-05-30
Completion date
2023-09-10
Last updated
2024-07-31

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

Conditions

Type1 Diabetes

Keywords

Artificial Pancreas (AP), Diabetes Mellitus, Type 1, Insulin Pump, Continuous Glucose Monitor (CGM), Model Predictive Control (MPC), Automated Insulin Delivery (AID), Adaptive Motif-based Control (AMBC)

Brief summary

This study is intended to assess a Neural-net Artificial Pancreas (NAP) implementation of an established AP controller - the University of Virginia Model Predictive Control Algorithm (UMPC). The health outcomes achieved on NAP will be compared to the health outcomes achieved on UMPC in a randomized crossover design. The investigators will consent up to 20 participants, ages ≥18.0, with a goal of completing 15 participants.

Detailed description

The study will follow a randomized cross-over design assessing glycemic control on a Neural-net Artificial Pancreas (NAP), compared to the previously tested University of Virginia Model Predictive Control (UMPC) algorithm, in a supervised hotel setting: The study will involve Tandem t:slim X2 Control-IQ (CIQ) users who will continue to use their CIQ systems, except during the hotel sessions, which will use the DiAs prototyping platform, connected to a Tandem t:AP research pump and a Dexcom G6 sensor, and implementing NAP or UMPC. The study sensor will be the same sensor used by CIQ - it will be disconnected from CIQ and connected to DiAs. Following enrollment, one week of automated insulin delivery (AID) data will be downloaded from the participants' pumps or t:connect accounts and will be used to establish a baseline and initialize the control algorithms. Participants will be then studied at a local hotel for 20 hours, including an 18-hour experiment, randomly receiving either NAP or UMPC. Participants will then receive the opposite intervention either sequentially during the same hotel stay, or in a second hotel stay up to 28 days following the first hotel stay. During these 18-hour hotel sessions participants will be followed to compare blood glucose control on NAP vs. UMPC. The study meals and activities will be kept the same between study sessions. The investigators will analyze non-inferiority of NAP compared to UMPC, but this pilot feasibility study is not powered to formally test noninferiority. The primary outcome is percent time in range (TIR) (70 to 180 mg/dL) on NAP vs UMPC. Secondary outcomes include frequency of hypoglycemia (time below range = TBR) and hyperglycemia (time above range = TAR), as well as other safety and control metrics.

Interventions

DEVICENeural-net Artificial Pancreas

NAP is a neural-net implementation of the previously tested UMPC algorithm (below).

DEVICEUniversity of Virginia Model Predictive Control

A previously tested artificial pancreas control algorithm, based on a differential-equation model of the human metabolic system in diabetes.

Sponsors

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
CollaboratorNIH
University of Virginia
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT
Masking
NONE

Intervention model description

Randomized crossover: Participants will be randomized to two groups differing by the order of controller use: Group A: NAP, followed by UMPC; Group B: UMPC, followed by NAP.

Eligibility

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

Inclusion criteria

1. Age ≥18.0 at time of consent. 2. Clinical diagnosis, based on investigator assessment, of type 1 diabetes for at least one year. 3. Currently using insulin for at least six months. 4. Currently using the Control-IQ automated insulin delivery system for at least one mont. 5. Hemoglobin A1c of ≤9%. 6. Using insulin parameters such as insulin to carb ratio and correction factor consistently in order to dose insulin for meals or corrections. 7. Access to internet and willingness to upload data during the study as needed. 8. If female of childbearing potential and sexually active, 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 within 24 hours prior to initiating the experimental algorithms. 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 University of Virginia Diabetes Assistant system throughout study session. 10. Willingness to use personal Lispro (Humalog) or aspart (Novolog) during the study session. 11. Willingness not to start any new non-insulin glucose-lowering agent during the course of the trial (including Sodium-glucose cotransporter-2 inhibitors, metformin/biguanides, glucagon-like peptide-1 receptor agonists, Pramlintide, Dipeptidyl peptidase-4 inhibitors, Sulfonylureas and nutraceuticals). 12. Willingness to reschedule the hotel portion of the study if placed on systemic steroids (e.g. intravenous injection, intramuscular injection, intra-articular or oral routes). 13. An understanding and willingness to follow the protocol and signed informed consent.

Exclusion criteria

1. History of Diabetic Ketoacidosis (DKA) in the 12 months prior to enrollment. 2. Severe hypoglycemia resulting in seizure or loss of consciousness in the 12 months prior to enrollment. 3. Currently pregnant or intent to become pregnant during the trial. 4. Currently breastfeeding. 5. Currently being treated for a seizure disorder. 6. Treatment with Meglitinides/Sulfonylureas at the time of hotel study. 7. Use of metformin/biguanides, glucagon-like peptide-1 agonists, Pramlintide, Dipeptidyl peptidase-4 inhibitors, Sodium-glucose cotransporter-2 inhibitors, or nutraceuticals intended for glycemic control with a change in dose in the past month. 8. History of significant cardiac arrhythmia (except for benign premature atrial contractions and benign premature ventricular contractions which are permitted or previous ablation of arrhythmia without recurrence which may be permitted) or active cardiovascular disease. 9. A known medical condition that in the judgment of the investigator might interfere with the completion of the protocol such as the following examples: 1. Inpatient psychiatric treatment in the past 6 months. 2. Presence of a known adrenal disorder. 3. Uncontrolled thyroid disease. 10. A known medical condition that in the judgment of the investigator might interfere with the completion of the protocol.

Design outcomes

Primary

MeasureTime frameDescription
Percent of Time-in-Range (TIR) on NAP Versus UMPC.36 hours (two 18-hour experiments)The primary outcome is percent of time in 70 to 180 mg/dL range on NAP vs UMPC.

Secondary

MeasureTime frameDescription
Percent of Time in Hyperglycemia.36 hours (two 18-hour experiments)Percent CGM readings above 180 mg/dL.
Percent of Time in Hypoglycemia.36 hours (two 18-hour experiments)Percent CGM readings below 70 mg/dL.
System Functionality36 hours (two 18-hour experiments)The investigator will observe, record, and tabulate any system malfunctions requiring study team intervention.
Participant Feedback36 hours (two 18-hour experiments)The investigator will obtain qualitative feedback form the participants regarding system functionality.

Countries

United States

Participant flow

Recruitment details

This study is intended to assess a Neural-net Artificial Pancreas (NAP) implementation of an established AP controller - the University of Virginia Model Predictive Control Algorithm (UMPC). The health outcomes achieved on NAP will be compared to the health outcomes achieved on UMPC in a randomized crossover design. The investigators will consent up to 20 participants, ages ≥18.0, with a goal of completing 15 participants.

Participants by arm

ArmCount
All Participants
Participants completed two consecutive 20-hour hotel sessions, receiving in random order either NAP or UMPC
15
Total15

Baseline characteristics

CharacteristicAll Participants
Age, Categorical
<=18 years
0 Participants
Age, Categorical
>=65 years
2 Participants
Age, Categorical
Between 18 and 65 years
13 Participants
Age, Continuous47.9 years
Ethnicity (NIH/OMB)
Hispanic or Latino
0 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
15 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants
Percent Time in Range (70-180 mg/dL)69.3 Percent of time between 70-180 mg/dl
STANDARD_DEVIATION 13.4
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants
Race (NIH/OMB)
Asian
0 Participants
Race (NIH/OMB)
Black or African American
2 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
13 Participants
Region of Enrollment
United States
15 participants
Sex: Female, Male
Female
10 Participants
Sex: Female, Male
Male
5 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 80 / 7
other
Total, other adverse events
0 / 80 / 7
serious
Total, serious adverse events
0 / 80 / 7

Outcome results

Primary

Percent of Time-in-Range (TIR) on NAP Versus UMPC.

The primary outcome is percent of time in 70 to 180 mg/dL range on NAP vs UMPC.

Time frame: 36 hours (two 18-hour experiments)

ArmMeasureGroupValue (MEAN)Dispersion
Overall StudyPercent of Time-in-Range (TIR) on NAP Versus UMPC.Time in Range (NAP)86.08 Percent of time between 70-180 mg/dlStandard Deviation 6.5
Overall StudyPercent of Time-in-Range (TIR) on NAP Versus UMPC.Time in Range (UMPC)87.25 Percent of time between 70-180 mg/dlStandard Deviation 12.9
p-value: 0.2GLM with Repeated Measures
Secondary

Participant Feedback

The investigator will obtain qualitative feedback form the participants regarding system functionality.

Time frame: 36 hours (two 18-hour experiments)

Population: Data were not collected

Secondary

Percent of Time in Hyperglycemia.

Percent CGM readings above 180 mg/dL.

Time frame: 36 hours (two 18-hour experiments)

ArmMeasureGroupValue (MEAN)Dispersion
Overall StudyPercent of Time in Hyperglycemia.Percent CGM readings above 180 mg/dL (NAP)11.93 Percent of time above 180 mg/dlStandard Deviation 6.4
Overall StudyPercent of Time in Hyperglycemia.Percent CGM readings above 180 mg/dL (UMPC)10.96 Percent of time above 180 mg/dlStandard Deviation 13.1
Secondary

Percent of Time in Hypoglycemia.

Percent CGM readings below 70 mg/dL.

Time frame: 36 hours (two 18-hour experiments)

ArmMeasureGroupValue (MEAN)Dispersion
Overall StudyPercent of Time in Hypoglycemia.Percent CGM readings below 70 mg/dL (NAP)1.88 Percent of time below 70 mg/dlStandard Deviation 2.25
Overall StudyPercent of Time in Hypoglycemia.Percent CGM readings below 70 mg/dL (UMPC)1.79 Percent of time below 70 mg/dlStandard Deviation 2.1
Secondary

System Functionality

The investigator will observe, record, and tabulate any system malfunctions requiring study team intervention.

Time frame: 36 hours (two 18-hour experiments)

ArmMeasureValue (NUMBER)
Overall StudySystem Functionality0 Number of reportable device malfunctions

Source: ClinicalTrials.gov · Data processed: Feb 7, 2026