Early Feasibility Study 2 of Outpatient Control-to-Range - Testing System Efficacy
An unblinded, randomized, cross-over design with each patient participating in two 40-hour outpatient admissions: (a) Experimental involving automated Control-to-Range (CTR) and (b) Control using Continuous Glucose Monitor (CGM)- augmented insulin pump treatment outside of a hospital based clinical research center. The principal goal is to validate a smart phone-based control-to-range (CTR) system for ambulatory use and to estimate the effect of CTR vs. sensor-augmented pump therapy, thereby providing justification for further larger home-based trials of CTR.
|Study Design:||Allocation: Randomized
Endpoint Classification: Safety/Efficacy Study
Intervention Model: Crossover Assignment
Masking: Open Label
Primary Purpose: Treatment
|Official Title:||Early Feasibility Study 2 of Outpatient Control-to-Range - Testing System Efficacy|
- Estimate the effect size of Control-to-Range (CTR) vs. Continuous Glucose Monitor (CGM)-augmented insulin pump treatment in an outpatient setting. [ Time Frame: 40 hours ] [ Designated as safety issue: Yes ]It is expected that compared to CGM-augmented insulin pump treatment, CTR will result in moderate effect size of approximately 0.4, in terms of reduction of the overnight risk for hypoglycemia as measured by the Low Blood Glucose Index computed from retrofitted CGM data. This effect is not expected to be statistically significant with the anticipated sample size but will be used to inform power analysis for the subsequent multi-center trial of CTR at home.
- Time spent in target range [ Time Frame: 40 hours ] [ Designated as safety issue: Yes ]CTR will improve (non-significantly at the projected sample size of N=5 subjects/site) the time spent within the target range of 80-140 mg/dl overnight (computed from retrofitted CGM data) and will reduce the extent of postprandial glucose excursions during the day. These data will provide justification and design support for a subsequent larger multi-center trial of CTR at home.
- Patient comfort with the Diabetes Assistant (DiAs) user interface [ Time Frame: 40 hours ] [ Designated as safety issue: No ]
- Reliability of DiAs remote monitoring [ Time Frame: 40 hours ] [ Designated as safety issue: No ]Assess the DiAs remote monitoring by medical personnel/technicians to confirm appropriate functioning outside of the hospital setting
- Reliability of inter-device connections between DiAs and the CGM and between DiAs and the insulin pump. [ Time Frame: 40 hours ] [ Designated as safety issue: Yes ]Assess the functioning of the connections between DiAs, the continuous glucose sensor, and the insulin pump.
|Study Start Date:||October 2012|
|Estimated Study Completion Date:||April 2013|
|Estimated Primary Completion Date:||April 2013 (Final data collection date for primary outcome measure)|
Experimental: Experimental Involving Automated CTR
Closed-Loop Control: Insulin delivery will be controlled by the Diabetes Assistant (DiAs) system running in Control to Range (CTR) or in Safety Only mode. The subject will interact with the system through its Graphic User Interface (GUI). Subjects will not be allowed to administer correction boluses between meals and snacks as the DiAs will automatically be adjusting insulin to correct for hyperglycemia. The total doses recommended by the DiAs prior to meals and snacks includes the correction dose and Insulin on Board (IOB) calculated by the system.
Device: Diabetes Assistant (DiAs)
A medical platform that uses a smart-phone to connect to a continuous glucose sensor to insulin pump and run closed-loop control. The cell phone runs the Control to Range and is connected to work with the insulin pump and continuous glucose monitor to help keep the blood sugar in a desired range (80-180 mg/dL during the day) and help avoid hypoglycemia during the night.
No Intervention: CGM-Augmented Insulin Pump Treatment
Open Loop Control: Insulin delivery will be controlled by the Diabetes Assistant (DiAs) system running in open-loop mode. The subject will interact with the system through its Graphic User Interface (GUI). Subjects will be permitted to administer correction boluses at any time during the Control Admission, whether or not they are eating a scheduled meal or snack. DiAs will be initialized with the subject's typical insulin pump settings. The subject will be reminded that all treatment decisions should be based on fingerstick values and not on continuous glucose monitor (CGM) values.
The overall objective of this project is to sequentially test, validate, obtain regulatory approval for, and deploy at home, a closed-loop Control-to-Range (CTR) system for optimal blood glucose (BG) regulation in people with type 1 diabetes. The CTR system is comprised of two algorithmic layers: a Safety Supervision Module (SSM) and Insulin on Board Tracking and Safety Module (ITSM), and an automated Range Correction Module (RCM). Both modules will receive continuous glucose monitoring (CGM) and insulin delivery data. The SSM and ITSM will monitor the safety of the subject's continuous subcutaneous insulin infusion pump (CSII) to prevent hypoglycemia. The RCM will be responsible for optimizing BG control and mitigating postprandial hyperglycemic excursions through series of insulin boluses. To run CTR, we will use our wearable artificial pancreas platform, known as DiAs (Diabetes Assistant), which consists of a smart phone running CTR and connected to standard insulin delivery and CGM devices.
|Contact: Daniel R. Chernavvsky, M.D., CRCemail@example.com|
|Contact: Mary C. Oliveri, M.S., CCRPfirstname.lastname@example.org|
|United States, California|
|Sansum Diabetes Research Institute||Recruiting|
|Santa Barbara, California, United States, 93105|
|Contact: Howard Zisser, M.D. 805-682-7640 ext 255 email@example.com|
|Contact: Wendy Bevier, Ph.D. 805.682.7640 ext 207 firstname.lastname@example.org|
|Sub-Investigator: Eyal Dassau, Ph.D.|
|United States, Virginia|
|University of Virginia||Recruiting|
|Charlottesville, Virginia, United States, 22908|
|Contact: Boris P. Kovatchev, Ph.D. 434-924-5592 email@example.com|
|Sub-Investigator: Marc D. Breton, Ph.D.|
|Sub-Investigator: Stacey M. Anderson, M.D.|
|Sub-Investigator: Sue A. Brown, M.D.|
|Sub-Investigator: Patrick Keith-Hynes, Ph.D.|
|Sub-Investigator: Colleen Karvetski, Ph.D.|
|Sub-Investigator: Stephen Patek, Ph.D.|
|Principal Investigator:||Boris P. Kovatchev, Ph.D.||University of Virginia|