Neural-net Artificial Pancreas (NAP) (NAP)
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ClinicalTrials.gov Identifier: NCT05876273 |
Recruitment Status :
Not yet recruiting
First Posted : May 25, 2023
Last Update Posted : May 25, 2023
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Condition or disease | Intervention/treatment | Phase |
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Type1 Diabetes | Device: Neural-net Artificial Pancreas Device: University of Virginia Model Predictive Control | Not Applicable |
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.
Study Type : | Interventional (Clinical Trial) |
Estimated Enrollment : | 15 participants |
Allocation: | Randomized |
Intervention Model: | Crossover Assignment |
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. |
Masking: | None (Open Label) |
Primary Purpose: | Treatment |
Official Title: | Adaptive Motif-Based Control (AMBC): Pilot 1 - Neural Net Implementation of Automated Insulin Delivery |
Estimated Study Start Date : | May 2023 |
Estimated Primary Completion Date : | September 2023 |
Estimated Study Completion Date : | September 2023 |
Arm | Intervention/treatment |
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Experimental: NAP first, then UMPC
Participants will use the Neural Net Artificial Pancreas (NAP) algorithm for 18 hours. Then switch to the University of Virginia Model-Predictive Control (UMPC) for 18 hours.
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Device: Neural-net Artificial Pancreas
NAP is a neural-net implementation of the previously tested UMPC algorithm (below).
Other Name: NAP Device: University 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.
Other Name: UMPC |
Experimental: UMPC first, then NAP
Participants will use the UMPC for 18 hours, then switch to NAP for 18 hours.
|
Device: Neural-net Artificial Pancreas
NAP is a neural-net implementation of the previously tested UMPC algorithm (below).
Other Name: NAP Device: University 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.
Other Name: UMPC |
- Percent of Time-in-Range (TIR) on NAP versus UMPC. [ Time Frame: 36 hours (two 18-hour experiments) ]The primary outcome is percent of time in 70 to 180 mg/dL range on NAP vs UMPC.
- Percent of Time in Hyperglycemia. [ Time Frame: 36 hours (two 18-hour experiments) ]Percent CGM readings above 180 mg/dL.
- Percent of Time in Hypoglycemia. [ Time Frame: 36 hours (two 18-hour experiments) ]Percent CGM readings below 70 mg/dL.
- System Functionality [ Time Frame: 36 hours (two 18-hour experiments) ]The investigator will observe, record, and tabulate any system malfunctions requiring study team intervention.
- Participant Feedback [ Time Frame: 36 hours (two 18-hour experiments) ]The investigator will obtain qualitative feedback form the participants regarding system functionality.
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.
Ages Eligible for Study: | 18 Years and older (Adult, Older Adult) |
Sexes Eligible for Study: | All |
Accepts Healthy Volunteers: | No |
Inclusion Criteria:
- Age ≥18.0 at time of consent.
- Clinical diagnosis, based on investigator assessment, of type 1 diabetes for at least one year.
- Currently using insulin for at least six months.
- Currently using the Control-IQ automated insulin delivery system for at least one mont.
- Hemoglobin A1c of ≤9%.
- Using insulin parameters such as insulin to carb ratio and correction factor consistently in order to dose insulin for meals or corrections.
- Access to internet and willingness to upload data during the study as needed.
- 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.
- Willingness to use the University of Virginia Diabetes Assistant system throughout study session.
- Willingness to use personal Lispro (Humalog) or aspart (Novolog) during the study session.
- 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).
- 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).
- An understanding and willingness to follow the protocol and signed informed consent.
Exclusion Criteria:
- History of Diabetic Ketoacidosis (DKA) in the 12 months prior to enrollment.
- Severe hypoglycemia resulting in seizure or loss of consciousness in the 12 months prior to enrollment.
- Currently pregnant or intent to become pregnant during the trial.
- Currently breastfeeding.
- Currently being treated for a seizure disorder.
- Treatment with Meglitinides/Sulfonylureas at the time of hotel study.
- 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.
- 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.
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A known medical condition that in the judgment of the investigator might interfere with the completion of the protocol such as the following examples:
- Inpatient psychiatric treatment in the past 6 months.
- Presence of a known adrenal disorder.
- Uncontrolled thyroid disease.
- A known medical condition that in the judgment of the investigator might interfere with the completion of the protocol.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05876273
Contact: Morgan R Fuller | 434-242-9379 | mf2nu@uvahealth.org | |
Contact: Emma Emory, RN | 434-327-0725 | ee9m@uvahealth.org |
United States, Virginia | |
University of Virginia Center for Diabetes Technology | |
Charlottesville, Virginia, United States, 22903 | |
Contact: Boris P Kovatchev, PhD 434-924-5592 bpk2u@virginia.edu | |
Sub-Investigator: Patricio H Colmegna, PhD | |
Principal Investigator: Sue A Brown, MD | |
Sub-Investigator: Alberto F Castillo, PhD |
Study Director: | Boris P Kovatchev, PhD | University of Virginia Center for Diabetes Technology | |
Principal Investigator: | Sue A Brown, MD | University of Virginia Center for Diabetes Technology |
Responsible Party: | Boris Kovatchev, PhD, Principal Investigator, University of Virginia |
ClinicalTrials.gov Identifier: | NCT05876273 |
Other Study ID Numbers: |
230058 R01DK133148 ( U.S. NIH Grant/Contract ) |
First Posted: | May 25, 2023 Key Record Dates |
Last Update Posted: | May 25, 2023 |
Last Verified: | May 2023 |
Individual Participant Data (IPD) Sharing Statement: | |
Plan to Share IPD: | Yes |
Plan Description: | Will follow the NIH Data Sharing Policy and Implementation Guidance on sharing research resources for research purposes to qualified individuals in the scientific community. |
Supporting Materials: |
Study Protocol Statistical Analysis Plan (SAP) Informed Consent Form (ICF) |
Time Frame: | Generally, data will be made available after the primary publications of each study. |
Access Criteria: | The Data Sharing Agreements will be formulated by the study team. |
Studies a U.S. FDA-regulated Drug Product: | No |
Studies a U.S. FDA-regulated Device Product: | Yes |
Device Product Not Approved or Cleared by U.S. FDA: | Yes |
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) |
Diabetes Mellitus, Type 1 Diabetes Mellitus Glucose Metabolism Disorders Metabolic Diseases Endocrine System Diseases |
Autoimmune Diseases Immune System Diseases Pancrelipase Gastrointestinal Agents |