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

• US 9,402,953 B2
• Filed: 11/18/2013
• Issued: 08/02/2016
• Est. Priority Date: 03/31/2009
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories), Cambridge Enterprise Limited (University of Cambridge)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories), Cambridge Enterprise Limited (University of Cambridge)
• Inventors: Wilinska, Malgorzata E., Budiman, Erwin S., Hayter, Gary A., Taub, Marc B., Hovorka, Roman
• Primary Examiner(s): VU, QUYNH-NHU HOANG
• Application Number:
  US14/083,336
• Publication Number:
  US 20140081236A1
• Time in Patent Office: 988 Days
• Field of Search: 604 65- 66, 600/300, 600/316, 600/319, 600/347, 600/365
• US Class Current: 1/1
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61M 2005/14208 with a programmable infusion control system, characterised by the infusion program
• CPC Class Codes: A61M 2005/14292 Computer-based infusion planning or simulation of spatio-temporal infusate distribution
• CPC Class Codes: A61M 2005/14296 Pharmacokinetic models
• CPC Class Codes: A61M 2205/50 with microprocessors or computers
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2205/70 with testing or calibration facilities
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/142 Pressure infusion, e.g. using pumps
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 20/17 delivered via infusion or injection

Abstract

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® 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.

Claims

1. An integrated system for the delivery of medication to a patient, the system comprising:

a controller programmed to receive a sensor glucose measurement signal, to provide a delivery control signal to a medication delivery device as a function of the received sensor glucose measurement signal in accordance with a control model and a glucose measurement error model, and to adjust a value of the delivery control signal in accordance with safety checks, wherein the safety checks;

impose a maximum infusion rate related to a basal rate, the maximum infusion rate being dependent on a current sensor glucose level, time since a previous meal, and carbohydrate content of a meal; and

cap the medication infusion to a pre-programmed basal rate in response to an inference of an occlusion of the medication delivery device.

2. The integrated system for the delivery of medication of claim 1, wherein the controller is further programmed to:

shut off the delivery of medication at a predetermined low sensor glucose value;

or

reduce the delivery of medication when received sensor glucose measurement signals indicate that the patient'"'"'s glucose is decreasing.

3. The integrated system for the delivery of medication of claim 1, wherein the controller is further programmed to provide the delivery control signal also as a function of weight of a patient, a total daily medication dose, and a basal medication profile, and wherein:

the controller is also programmed to calculate from the control model an accepted value;

the controller is also programmed to calculate from the glucose measurement signal an inferred value;

the controller is also programmed to forecast a future plasma glucose level excursion based on the accepted value and inferred value; and

the controller is also programmed to adjust the delivery control signal in accordance with the forecast future plasma glucose level excursion.

4. The integrated system for the delivery of medication of claim 3, wherein the accepted value comprises a medication sensitivity of the patient, a glucose distribution volume, and a medication distribution volume.

5. The integrated system for the delivery of medication of claim 3, wherein the inferred value comprises glucose flux and a carbohydrate bioavailability.

6. The integrated system for the delivery of medication of claim 1, wherein the glucose measurement error model is associated with a function comprising calibration error of the glucose sensor.

7. The integrated system for the delivery of medication of claim 6, wherein the calibration error in the glucose measurement error model comprises the difference between a plasma glucose level and the sensor glucose level signal of the glucose sensor.

8. The integrated system for the delivery of medication of claim 7, wherein the controller is further programmed to recalibrate the system when the difference between the received sensor glucose level signal and a plasma glucose level exceeds a predetermined level.

9. The integrated system for the delivery of medication of claim 1, wherein the glucose measurement error model is associated with a glucose sensor dropout.

10. The integrated system for the delivery of medication of claim 1, wherein the glucose measurement error model is associated with actual glucose sensor measurement data.

11. The integrated system for the delivery of medication of claim 1, wherein the glucose measurement error model is associated with actual glucose sensor measurement data from a glucose sensor of the same type as the sensor of the system.

12. The integrated system for the delivery of medication of claim 1, wherein the control model comprises a model predictive controller that is programmed to provide the delivery control signal to the medication delivery device as a function of a model predictive control.

13. The integrated system for the delivery of medication of claim 1, wherein the glucose measurement error model is associated with actual glucose sensor error data, excluding sensor noise data.

14. The integrated system for the delivery of medication of claim 1, wherein the glucose measurement error model is associated with actual glucose sensor measurement data to the exclusion of randomly-generated variable data.

15. The integrated system for the delivery of medication of claim 1, wherein the glucose measurement error model is associated with a fixed time history of error data from actual use of a glucose sensor of the same type as the sensor of the system.

16. A method for delivering medication to a patient, the method comprising:

receiving a sensed glucose measurement signal and providing a delivery control signal as a function of the received sensed glucose measurement signal in accordance with a control model and a glucose measurement error model; and

adjusting a value of the delivery control signal in accordance with safety checks that cause;

the imposing of a maximum infusion rate related to a basal rate, the maximum infusion rate being dependent on a current sensor glucose level, time since a previous meal, and carbohydrate content of a meal; and

the capping of the medication infusion to a pre-programmed basal rate if a medication delivery device occlusion is inferred.

17. The method for delivering medication to a patient of claim 16, wherein the safety checks further cause at least one of:

the shutting off of medication delivery at a predetermined low sensor glucose value;

or

the reducing of the delivery of medication when received sensor glucose measurement signals indicate that the patient'"'"'s glucose is decreasing.

18. The method for delivering medication to a patient of claim 16, further comprising providing the delivery control signal also as a function of weight of a patient, a total daily medication dose, and a basal medication profile, and further comprising:

calculating an accepted value from the control model;

calculating an inferred value from the glucose measurement signal;

forecasting a future plasma glucose level excursion based on the accepted value and inferred value; and

adjusting the delivery control signal in accordance with the forecast future plasma glucose level excursion.

19. The method for delivering medication to a patient of claim 18, wherein calculating the accepted value further comprises calculating the accepted value also from a medication sensitivity of the patient, a glucose distribution volume, and a medication distribution volume.

20. The method for delivering medication to a patient of claim 18, wherein calculating the inferred value further comprises calculating the inferred value also from glucose flux and a carbohydrate bioavailability.

21. The method for delivering medication to a patient of claim 16, further comprising deriving the glucose measurement error model from calibration error of the glucose sensor.

22. The method for delivering medication to a patient of claim 21, wherein deriving the glucose measurement error model from calibration error comprises deriving the calibration error from the difference between a plasma glucose level and the sensor glucose level signal of the glucose sensor.

23. The method for delivering medication to a patient of claim 22, further comprising recalibrating when the difference between the received sensor glucose level signal and a plasma glucose level exceeds a predetermined level.

24. The method for delivering medication to a patient of claim 16, further comprising deriving the glucose measurement error model from a glucose sensor dropout.

25. The method for delivering medication to a patient of claim 16, further comprising deriving the glucose measurement error model solely from actual glucose sensor measurement data.

26. The method for delivering medication to a patient of claim 16, further comprising deriving the glucose measurement error model from actual glucose sensor measurement data from a glucose sensor of the same type as the sensor of the system.

27. The method for delivering medication to a patient of claim 16, wherein providing the delivery control signal as a function of the received sensed glucose measurement signal in accordance with a control model comprises predicting the glucose measurement and providing the delivery control signal as a function of predicted glucose.

28. The method for delivering medication to a patient of claim 16, further comprising deriving the glucose measurement error model solely from actual glucose sensor error data, excluding sensor noise data.

29. The method for delivering medication to a patient of claim 16, further comprising deriving the glucose measurement error model solely from actual glucose sensor measurement data to the exclusion of randomly-generated variable data.

30. The method for delivering medication to a patient of claim 16, further comprising deriving the glucose measurement error model solely from a fixed time history of error data from actual use of a glucose sensor of the same type as the sensor of the system.