A probabilistic closed-loop artificial pancreas to handle unannounced meals

Rensselaer Polytechnic Institute, Troy NY

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Abstract

DESCRIPTION (provided by applicant): Type 1 diabetes is a condition caused by destruction of the pancreas' ability to produce insulin. This results in lifelong insulin requirement. This condition is treated with insulin injections or by a pump that pumps insulin continuously through a small plastic tube that sits under the skin. Currently, insulin doses need to be worked out by the patient depending on their finger-stick blood glucose level and the sugar content in their food. The development of an artificial pancreas that can manage all of this automatically by measuring glucose levels and working out how much insulin to give, would greatly change the treatment of diabetes. The aim of this study is to further develop an artificial pancreas system which we have developed and studied in a small group of patients. Our initial results were encouraging and we were able to control glucose levels within an acceptable level during the day and night. Our system will consist of an insulin pump, glucose sensor and smartphone with a calculator, which determines how much insulin to give by a special formula. Through this study, we hope to make the system better by adding an accelerometer that can measure how active a patient is. The system can then change insulin delivery depending on activity levels. It will also be able to tell when you are sleeping and adjust insulin for this. Our system will be designed so that the patient does not have to tell us about meals or exercise. This is a true, automatic, artificial pancreas for both day and night time. We will incorporate special formulas and information that we know already about, such as timing of meals and exercise, to improve the performance of the system. In this study, we will initially test the system in a group of 20 patients in hospital with type 1 diabetes to see how well the system can work in managing glucose levels. We will use the results to make further improvements to our system. When the system is working well, we will continue testing the system in another group of 20 patients over 4 days in a hotel setting with remote monitoring. Towards the end of this program, we will test the system in a group of 12 patients using the system at home for 2 weeks with remote monitoring.