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Multiple Model Probabilistic Predictive Control (MMPPC) Outpatient Clinical Protocol (NCT02769884)

University of Colorado, Denver
Stanford University
Mount Sinai Hospital, New York
This study trials a prototype artificial pancreas system that consists of a Roche insulin pump, a Dexcom continuous glucose monitor (CGM), and an experiential MMPPC (multiple model probabilistic predictive control) algorithm housed on an android cell phone. The system doses insulin based on CGM sensor glucose levels and the experimental algorithm. The aim of this clinical study is to determine the efficacy of the MMPPC controller in adolescents and adults with type 1 diabetes in a hotel setting.
  • Device: MMPPC algorithm artificial pancreas
    An artificial pancreas system using the MMPPC algorithm, Roche insulin pump, and Dexcom CGM
    Ages eligible for Study
    15 Years to 55 Years
    Genders eligible for Study
    All
    Accepts Healthy Volunteers
    No
    This study trials a prototype artificial pancreas system that consists of a Roche insulin pump, a Dexcom continuous glucose monitor (CGM), and an experiential MMPPC (multiple model probabilistic predictive control) algorithm housed on an android cell phone. The system doses insulin based on CGM sensor glucose levels and the experimental algorithm. The algorithm runs through a glucose control platform called the DiAs (Diabetes Assistant)

    The aim of this study is to determine the safety and feasibility of the MMPPC controller in adults and adolescents with type 1 diabetes testing the use of predefined tuning parameters to provide adaptability to patient. We will assess the safety of the system with both unannounced meals, and meals using a meal announcement with a premeal insulin bolus based on the subject's estimated carbohydrate content of the meal
    Status:
    completed
    Type:
    Interventional
    Phase:
    Start:
    30 June, 2016
    Updated:
    25 January, 2018
    Participants:
    10
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