Cambridge Enterprise Limited

Abbott Diabetes Care Inc.

Roman Hovorka

Gary Alan Hayter

Erwin Satrya Budiman

Marc Barry Taub

Malgorzata E Wilinska

David B Dunger

A closed-loop system for insulin infusion overnight uses a model predictive control algorithm ('MPC'). Used with the MPC is a glucose measurement error model which was derived from actual glucose sensor error data. That sensor error data included both a sensor artifacts component, including dropouts, and a persistent error component, including calibration error, all of which was obtained experimentally from living subjects. The MPC algorithm advised on insulin infusion every fifteen minutes. Sensor glucose input to the MPC was obtained by combining model-calculated, noise-free interstitial glucose with experimentally-derived transient and persistent sensor artifacts associated with the FreeStyle Navigator&#xae; Continuous Glucose Monitor System ('FSN'). The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simulated overnight closed-loop control with the MPC algorithm using the glucose measurement error model suggesting that the continuous glucose monitoring technologies facilitate safe closed-loop insulin delivery.

Integrated closed-loop medication delivery with error model and safety check

A system and method for reducing the number of hypoglycemic alarms presented to a user is presented. The system and methods include use of model based state estimation and variable-delayed threshold values to balance the risk of not presenting an alarm caused by an actual hypoglycemic state with the presentation of alarms caused by artifacts in the signals produced by a continuous glucose monitor.

Methods for reducing false hypoglycemia alarm occurrence

Diabetes management apparatus comprising a sensor providing measurements of glucose level in a human or animal; an insulin pump for delivering a dose of insulin to said human or animal; and a processor. The processor is adapted to perform the following steps: receive said measurements of glucose level from said sensor; calculate a insulin dose to be delivered by said insulin pump based on said received measurement; assess the validity of the status of the apparatus; and send a command to said insulin pump to deliver said calculated insulin dose, dependent on said assessing step confirming that the status is valid. The insulin pump is configured to deliver a preset dose of insulin unless said processor sends a command to said insulin pump and wherein a said command sent to said insulin pump is valid only for a predetermined time interval so that if no further commands are sent to said insulin pump during said predetermined time interval, said insulin pump reverts to delivering said preset dose of insulin at the end of said predetermined time interval.

Substance monitoring and control in human or animal bodies

Apparatus for monitoring a substance in human or animal in real time, the apparatus comprising a sensor providing a time series of measurements of substance level, said measurements being indicative of an inferred level of said substance in a part of said human or animal and a processor which applies an interacting multiple model strategy to a system model to provide a combined estimate of the inferred substance level from the substance level measurements. The substance may be glucose. The apparatus may also be adapted to control said substance using said interacting multiple model strategy to a system model to provide a combined estimate of a dose to be applied.

A closed-loop method for insulin infusion overnight uses a model predictive control algorithm ('MPC'). Used with the MPC is a glucose measurement error model which was derived from actual glucose sensor error data. That sensor error data included both a sensor artifacts component, including dropouts, and a persistent error component, including calibration error, all of which was obtained experimentally from living subjects. The MPC algorithm advised on insulin infusion every fifteen minutes. Sensor glucose input to the MPC was obtained by combining model-calculated, noise-free interstitial glucose with experimentally-derived transient and persistent sensor artifacts associated with the FreeStyle Navigator&#xae; Continuous Glucose Monitor System ('FSN'). The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simulated overnight closed-loop control with the MPC algorithm using the glucose measurement error model suggesting that the continuous glucose monitoring technologies facilitate safe closed-loop insulin delivery.

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Cambridge, United Kingdom

Roman Hovorka