A Study to Evaluate a Multiple Model Probabilistic Predictive Controller (MMPPC) for Closed Loop Insulin Delivery
- Conditions
- Type 1 Diabetes Mellitus
- Interventions
- Device: Multiple Model Predictive Controller
- Registration Number
- NCT01492062
- Lead Sponsor
- Stanford University
- Brief Summary
You are invited to participate in a research study for the development of an artificial pancreas. An artificial pancreas uses a program which takes information from a continuous blood glucose monitor and uses that information to tell an insulin infusion pump how much insulin to deliver. The primary purpose of this study is to gain experience with insulin delivery algorithms or programs program (algorithm) provides the best regulation of glucose levels so that there are no severe low blood glucose reactions and blood glucose levels are generally between 70 to 180 mg/dl.
- Detailed Description
You are invited to participate in a research study for the development of an artificial pancreas. An artificial pancreas uses a program which takes information from a continuous blood glucose monitor and uses that information to tell an insulin infusion pump how much insulin to deliver. The primary purpose of this study is to gain experience with insulin delivery algorithms or programs program (algorithm) provides the best regulation of glucose levels so that there are no severe low blood glucose reactions and blood glucose levels are generally between 70 to 180 mg/dl. If the system is working properly, you would not need to enter the amount of food you were eating, give an insulin bolus, or change your basal rates while wearing the device. You would need to periodically check to be sure the continuous glucose sensor was functioning properly and you would need to respond to alarms that might occur if your blood glucose was too high, too low, or the glucose sensor or pump were not working well. In addition to this the investigators will also gain experience with insulin delivery algorithms to minimize the number of glucose readings which are above or below target. It is our intention to modify the algorithms during these studies.
In this study the investigators plan to use a commercially available insulin infusion pump (OmniPod) to deliver lispro (Humalog) insulin. The investigators will use Navigator continuous glucose sensors both to monitor glucose levels (sensor 1) and provide the glucose concentration for the closed loop algorithm (sensor 2). The signal from the second Navigator will be sent by serial cable to a computer which will be at the patient's bedside. A control algorithm will reside on the computer, and the amount of insulin to be delivered will be transmitted to the OmniPod Personal Device Manager which will then send a radiofrequency (rf) signal to the Omnipod pump residing on the subject. A health care provider will be in attendance and monitoring discrete blood glucose levels (YSI, GlucoScout, or HemoCue measurements) at least every 30 minutes. While the Navigator and Omnipod are commercially available they will be used in this study as part of an investigational system while you are in the hospital, an investigational system is one that is not approved for use by the FDA.
Recruitment & Eligibility
- Status
- WITHDRAWN
- Sex
- All
- Target Recruitment
- Not specified
Eligibility
To be eligible for the study, all subjects must meet the following criteria:
- Clinical diagnosis of type 1 diabetes and using daily insulin therapy for at least one year. The diagnosis of type 1 diabetes is based on the investigator's judgment; Cpeptide level and antibody determinations are not needed.
- Age 21 years to less than 45.0 years
- Subject has used a downloadable insulin pump for at least 3 months
- Subject understands the study protocol and agrees to comply with it
- Informed Consent Form signed
- A Personal Home computer with internet access (must have access to a PC for uploading, not a Mac).
Exclusion
Subjects who meet any of the following criteria are not eligible for the study:
-
The presence of a significant medical disorder that in the judgment of the investigator will affect the wearing of the sensors or the completion of any aspect of the protocol.
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The presence of any of the following diseases:
- Asthma if treated with systemic or inhaled corticosteroids in the last 6 months
- Cystic fibrosis
- Other major illness that in the judgment of the investigator might interfere with the completion of the protocol Adequately treated thyroid disease and celiac disease do not exclude subjects from enrollment
-
Inpatient psychiatric treatment in the past 6 months
-
Current use of oral/inhaled glucocorticoids or other medications, which in the judgment of the investigator would be a contraindication to participation in the study.
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Pregnancy, breast feeding, or intention of becoming pregnant in the next 2 months.
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Weight less than 26 kg
-
Renal failure or peritoneal dialysis
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History of heart disease
-
The use of beta-blockers
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History of cerebrovascular disease, or non-hypoglycemic seizures, or intolerance of glucagon treatment.
-
History of a hypoglycemic seizure within 6 months of enrollment.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description closed-loop control Multiple Model Predictive Controller Multiple Model Predictive Controller
- Primary Outcome Measures
Name Time Method Test the feasibility of using MMPPC controller for closed loop insulin delivery in a monitored inpatient clinical research environment. 36 Hour Admission Safety: 1) No reference glucose values \<50 mg/dl, and no more than 30 minutes with reference glucose values between 50-60 mg/dl per day based on linear interpolation between values 3) No reference glucose value \>250 mg/dl outside of the 3 hours following a meal.
- Secondary Outcome Measures
Name Time Method Efficacy 30 hour admission The percent of time spent between 70 mg/dl and 180 mg/dl, mean and standard deviation of measurements.
Trial Locations
- Locations (2)
CTRU located in Blake Wilbur
🇺🇸Stanford, California, United States
Stanford University School of Medicine
🇺🇸Stanford, California, United States