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| Name | Class |
|---|---|
| University of California, Santa Barbara | OTHER |
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The goal of this proposed study is to compare use of a PID (Proportional-Integral-Derivative) controller versus an MPC (Model Predictive Control) controller algorithm in an artificial pancreas system, all other components and study design being equal. The study design, power calculation and endpoints were developed based on the results of an initial feasibility study (ClinicalTrials.gov Identifier: NCT01987206) that has already been completed.
This randomized crossover study consists of an evaluation of either type of control algorithm (MPC or PID) as a part of the Artificial Pancreas (AP) device during two periods of 27.5-hour closed-loop control in a minimally supervised setting (outpatient research area at the William Sansum Diabetes Center, Santa Barbara, CA) separated by a minimum of 5 days and a maximum of 2 weeks. The 27.5-hour period includes: 2 announced meals (dinner and breakfast of 65g and 50g CHO respectively) preceded with a dose of rapid-acting insulin equivalent to 100% bolus based on each subject's Insulin to Carbohydrate (I:C) ratio and 1 unannounced meal (lunch of 65g carbohydrates, same meal content as dinner); complete night from 12:00 am to 7:00 am. The goal is to demonstrate that the AP device is able to maintain the subject blood glucose within a safe range at all times.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Open-Loop Care | No Intervention | The subjects Open-Loop Care for the 24-hour period prior to each study sessions assessed for time in the target range 70-180 mg/dL, and frequency of hypoglycemia and hyperglycemia as assessed by CGM. | |
| PID algorithm with HMS | Experimental | Subjects will be treated with closed-loop care for 27.5h using a proportional-integral-derivative (PID) control algorithm, incorporating a personalized model of glucose-insulin dynamics. The health monitoring system (HMS) predicts impending hypoglycemia, and will be used in both experimental arms as an important safety feature of the device. |
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| MPC algorithm with HMS | Experimental | Subjects will be treated with closed-loop care for 27.5h using a model predictive control (MPC) control algorithm with HMS, using the identical model as in the first experimental arm. The health monitoring system (HMS) predicts impending hypoglycemia, and will be used in both experimental arms as an important safety feature of the device. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| PID control algorithm | Device |
| ||
| MPC control algorithm |
| Measure | Description | Time Frame |
|---|---|---|
| Time spent in safe blood glucose range | The percentage of time spent in safe blood glucose range of 70-180 mg/dl, comparing MPC, PID and the 24-hour period of Open-Loop Care just prior to each study session. More time spent inside the desired range will be considered successful. | 27.5-hours |
| Measure | Description | Time Frame |
|---|---|---|
| Glucose level extremes and need for outside intervention | The secondary endpoint measures glucose extremes (the time spent in the hypoglycemic range <70 mg/dl, time spent in the hyperglycemic range >180 mg/dl) and the need for outside intervention to prevent hypoglycemia or hyperglycemia comparing MPC, PID and the 24-hour period of Open-Loop Care just prior to each study session. Interventions would be insulin injections or oral carbohydrates given to the subject by the physician, as well as alerts from the health monitoring system. No need for physician intervention will be considered a successful outcome. |
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Inclusion Criteria:
Exclusion Criteria:
Hematocrit < 30% or >55% A1C > 10% Abnormal liver or renal function (Transaminase >2 times the upper limit of normal, Creatinine> 1.5 mg/dL) Labs drawn at screening visit or within one month prior to screening (for other purposes) will suffice for enrollment purposes related to hematocrit
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| Name | Affiliation | Role |
|---|---|---|
| Jordan E Pinsker, MD | Sansum Diabetes Research Institute | Principal Investigator |
| Eyal Dassau, PhD | University of California, Santa Barbara | Principal Investigator |
| Francis J Doyle III, PhD | University of California, Santa Barbara | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| William Sansum Diabetes Center | Santa Barbara | California | 93105 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27289127 | Result | Pinsker JE, Lee JB, Dassau E, Seborg DE, Bradley PK, Gondhalekar R, Bevier WC, Huyett L, Zisser HC, Doyle FJ 3rd. Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas. Diabetes Care. 2016 Jul;39(7):1135-42. doi: 10.2337/dc15-2344. Epub 2016 Jun 11. |
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| Type | Date | Date Unknown |
|---|---|---|
| Release | Oct 18, 2017 | |
| Reset | Nov 17, 2017 |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Oct 18, 2017 | Nov 17, 2017 |
| ID | Term |
|---|---|
| D003922 | Diabetes Mellitus, Type 1 |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| Device |
|
| 27.5-hours |
| D004700 | Endocrine System Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |