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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
Sponsor:
Collaborator:
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Information provided by (Responsible Party):
Boris Kovatchev, PhD, University of Virginia

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.

Condition or disease Intervention/treatment Phase
Type1 Diabetes Device: Neural-net Artificial Pancreas Device: University of Virginia Model Predictive Control Not Applicable

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.

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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

Resource links provided by the National Library of Medicine


Arm Intervention/treatment
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.
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




Primary Outcome Measures :
  1. 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.


Secondary Outcome Measures :
  1. Percent of Time in Hyperglycemia. [ Time Frame: 36 hours (two 18-hour experiments) ]
    Percent CGM readings above 180 mg/dL.

  2. Percent of Time in Hypoglycemia. [ Time Frame: 36 hours (two 18-hour experiments) ]
    Percent CGM readings below 70 mg/dL.

  3. System Functionality [ Time Frame: 36 hours (two 18-hour experiments) ]
    The investigator will observe, record, and tabulate any system malfunctions requiring study team intervention.

  4. Participant Feedback [ Time Frame: 36 hours (two 18-hour experiments) ]
    The investigator will obtain qualitative feedback form the participants regarding system functionality.



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

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.

Information from the National Library of Medicine

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


Contacts
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Contact: Morgan R Fuller 434-242-9379 mf2nu@uvahealth.org
Contact: Emma Emory, RN 434-327-0725 ee9m@uvahealth.org

Locations
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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         
Sponsors and Collaborators
University of Virginia
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Investigators
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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
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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.

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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
Keywords provided by Boris Kovatchev, PhD, University of Virginia:
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)
Additional relevant MeSH terms:
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Diabetes Mellitus, Type 1
Diabetes Mellitus
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases
Autoimmune Diseases
Immune System Diseases
Pancrelipase
Gastrointestinal Agents