Integrated delivery device for continuous glucose sensor

• US 8,926,585 B2
• Filed: 03/30/2012
• Issued: 01/06/2015
• Est. Priority Date: 02/26/2004
• Status: Expired due to Term

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Brauker, James H., Saint, Sean T., Kamath, Apurv U., Neale, Paul V., Simpson, Peter C., Mensinger, Michael Robert, Markovic, Dubravka, Tapsak, Mark A.
• Primary Examiner(s): Eisenberg, Rebecca E
• Application Number:
  US13/436,257
• Publication Number:
  US 20120186581A1
• Time in Patent Office: 1,012 Days
• Field of Search: 604 65- 67, 604503-504, 604/31, 702/19
• US Class Current: 604/503
• CPC Class Codes: A61B 2560/0443 Modular apparatus
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61B 5/14865 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61M 11/00 Sprayers or atomisers specially adapted for therapeutic purposes in general B05B; aerosol containers B65D83/14
• CPC Class Codes: A61M 15/0001 Details of inhalators; Constructional features thereof
• CPC Class Codes: A61M 2005/1726 the body parameters being measured at, or proximate to, the infusion site
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/3303 Using a biosensor
• CPC Class Codes: A61M 2205/502 User interfaces, e.g. screens or keyboards
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2230/201 Glucose concentration
• 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: A61M 5/31525 Dosing burettes, pipettes B01L3/02
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/63 for local operation

Abstract

Systems and methods for integrating a continuous glucose sensor, including a receiver, a medicament delivery device, and optionally a single point glucose monitor are provided. Manual integrations provide for a physical association between the devices wherein a user (for example, patient or doctor) manually selects the amount, type, and/or time of delivery. Semi-automated integration of the devices includes integrations wherein an operable connection between the integrated components aids the user (for example, patient or doctor) in selecting, inputting, calculating, or validating the amount, type, or time of medicament delivery of glucose values, for example, by transmitting data to another component and thereby reducing the amount of user input required. Automated integration between the devices includes integrations wherein an operable connection between the integrated components provides for full control of the system without required user interaction.

Claims

1. An integrated system for monitoring and treating diabetes, the system comprising:

a glucose sensor, wherein the glucose sensor measures glucose in a host for a period exceeding one hour, and outputs a data stream, including one or more sensor data points generated at predetermined intervals;

a receiver operably connected to the glucose sensor, wherein the receiver is configured to receive the data stream; and

a continuous medicament delivery device, wherein the delivery device is operably connected to the receiver, wherein at least one of the receiver or the medicament delivery device comprises programming that, when executed by a processor, automatically detects impending clinical risk based on the one or more sensor data points, wherein the continuous medicament delivery device is switched from a medicament delivery mode to a fail-safe mode responsive to the detection of impending clinical risk, and wherein the at least one of the receiver or the medicament delivery device further comprises programming that, when executed by a processor, requires the at least one of the receiver or the medicament delivery device to be at least one of validated or confirmed by a user interaction in response to a prompt on a user interface of at least one of the receiver or the medicament delivery device for delivery of a determined medicament therapy recommendation in the fail-safe mode.

2. The integrated system of claim 1, wherein the glucose sensor comprises an implantable glucose sensor.

3. The integrated system of claim 1, wherein the glucose sensor comprises a long-term subcutaneously implantable glucose sensor.

4. The integrated system of claim 1, wherein the medicament delivery device comprises a transdermal pump.

5. The integrated system of claim 1, wherein the medicament delivery device comprises a computer system associated with an implantable pump.

6. The integrated system of claim 1, wherein the medicament delivery device comprises an implantable pump.

7. The integrated system of claim 1, wherein the medicament delivery device is operably connected to the receiver by a wireless connection.

8. The integrated system of claim 1, wherein the medicament delivery device is operably connected by a wired connection.

9. The integrated system of claim 1, wherein the clinical risk is an identified danger or potential risk to the health of the host based on a measured or estimated glucose concentration value of the host.

10. The integrated system of claim 1, wherein the clinical risk is an identified danger or potential risk to the health of the host based on a measured or estimated rate of change of the glucose concentration of the host.

11. The integrated system of claim 1, wherein the clinical risk is an identified danger or potential risk to the health of the host based on an estimated or measured acceleration of the glucose concentration of the host.

12. The integrated system of claim 1, wherein the impending clinical risk is determined based on a discrepancy of a glucose value measured by a single point glucose monitor from sensor data of the continuous glucose sensor that could cause a risk to the patient if incorrect therapy is administered.

13. The integrated system of claim 1, further comprising programming that, when executed by a processor, learns a condition associated with the host by monitoring and patterning behaviors of the host over time, wherein detecting the impending clinical risk comprises determining whether the condition is met, and wherein the condition is selected from the group consisting of a medicament delivery time, a meal time, an exercise time and a sleep time.

14. The integrated system of claim 1, further comprising programming that, when executed by a processor, determines that glucose values based on the data stream indicate a trend in a first direction and determines a possibility to reverse the trend with a particular behavior, wherein the user is prompted to at least one of validate or confirm the at least one of the receiver or the medicament delivery device when the possibility is determined.

15. The integrated system of claim 1, further comprising programming that, when executed by a processor, uses a pattern recognition algorithm to quantify a metabolic profile of the host, and wherein the therapy recommendation is calculated based on the quantified metabolic profile.

16. The integrated system of claim 15, wherein the medicament delivery device is configured to administer both fast acting insulin and slow acting insulin, wherein the programming that, when executed by a processor, calculates amounts of both the slow acting insulin and the fast acting insulin to administer based on the metabolic profile, and wherein the therapy recommendation comprises the amounts of the slow acting insulin and the fast acting insulin.

17. The integrated system of claim 1, further comprising programming that, when executed by a processor, adaptively learns patterns of the host, and wherein the impending clinical risk is determined based on the learned patterns.

18. The integrated system of claim 1, further comprising programming that, when executed by a processor, determines a host'"'"'s metabolic response to medicament delivery using a pattern recognition algorithm, wherein the programming that, when executed by a processor, calculates the therapy recommendation, calculates the therapy recommendation based on the determined metabolic response.

19. The integrated system of claim 1, wherein the continuous medicament delivery device is configured to administer medicament therapy using a combination of bolus administration of medicament and basal administration of medicament.

20. The integrated system of claim 1, further comprising programming that, when executed by a processor, estimates glucose values of the host in the future using a prediction algorithm and wherein the programming that, when executed by a processor, automatically detects impending clinical risk is configured to detect impending clinical risk based on the estimated glucose values.

21. The integrated system of claim 20, wherein the prediction algorithm uses medicament delivery information received from the medicament delivery device to estimate the glucose values, and wherein the information comprises one or more of a medicament amount, a medicament type and a time of medicament delivery.

22. The integrated system of claim 1, further comprising programming that, when executed by a processor:

detects a condition,

sends instructions to administer a hypoglycemia treating medicament in response to detecting the condition,

monitors the glucose level of the host over a predetermined amount of time after the administration of the hypoglycemia treating medicament, and

triggers an alarm after the predetermined amount of time when the monitored glucose level over the predetermined time period does not indicate a changing trend away from the condition.

23. The integrated system of claim 22, wherein the condition is a hypoglycemic condition or a near-hypoglycemic condition.

24. The integrated system of claim 1, wherein the medicament delivery device comprises an insulin delivery device and a glucose or glucagon delivery device, wherein the insulin delivery device is in an automated mode unless a semi-automated mode is triggered responsive to the detection of an impending clinical risk, and wherein the glucose or glucagon delivery device is continuously in an automated mode so that user interaction is not required for administration of medicament using the glucose or glucagon delivery device.

25. The integrated system of claim 1, wherein the system is further configured to trigger an alarm responsive to the switching from the delivery mode to the fail-safe mode.

26. An integrated system for monitoring and treating diabetes, the system comprising:

a glucose sensor, wherein the glucose sensor measures glucose in a host for a period exceeding one hour, and outputs a data stream, including one or more sensor data points generated at predetermined intervals;

a receiver operably connected to the glucose sensor, wherein the receiver is configured to receive the data stream; and

a continuous medicament delivery device, wherein the delivery device is operably connected to the receiver, wherein at least one of the receiver or the medicament delivery device comprises programming that, when executed by a processor, automatically detects impending clinical risk, and programming that, when executed by a processor, operates the integrated system in a first mode unless a second mode is triggered,

wherein the programming that, when executed by a processor, operates the integrated system does not require user interaction for administration of medicament using the medicament device while in the first mode,

wherein the programming that, when executed by a processor, operates the integrated system requires user interaction for administration of medicament using the medicament device while in the second mode,

wherein the second mode is triggered responsive to the detection of the impending clinical risk, and

wherein the at least one of the receiver or the medicament delivery device further comprises programming that, when executed by a processor, requires the at least one of the receiver or the medicament delivery device to be at least one of validated or confirmed by a user interaction in response to a prompt on a user interface of at least one of the receiver or the medicament delivery device for administration of the medicament in the second mode.

27. The integrated system of claim 26, wherein the system is further configured to alarm the patient responsive to the switching from the first mode to the second mode.

28. The integrated system of claim 26, wherein the clinical risk is an identified danger or potential risk to the health of the host based on a measured or estimated glucose concentration value of the host.

29. The integrated system of claim 26, wherein the clinical risk is an identified danger or potential risk to the health of the host based on a measured or estimated rate of change of the glucose concentration of the host.

30. The integrated system of claim 26, wherein the clinical risk is an identified danger or potential risk to the health of the host based on an estimated or measured acceleration of the glucose concentration of the host.

31. The integrated system of claim 26, wherein the impending clinical risk is determined based on a discrepancy of a glucose value measured by a single point glucose monitor from sensor data of the continuous glucose sensor that could cause a risk to the patient if incorrect therapy is administered.

32. The integrated system of claim 26, further comprising programming that, when executed by a processor, adaptively learns patterns of the host, and wherein the impending clinical risk is determined based on the learned patterns.

33. The integrated system of claim 26, further comprising programming that, when executed by a processor, determines a host'"'"'s metabolic response to medicament delivery using a pattern recognition algorithm, wherein the programming that, when executed by a processor, calculates the therapy recommendation, calculates the therapy recommendation based on the determined metabolic response.

34. The integrated system of claim 26, wherein the continuous medicament delivery device is configured to administer medicament therapy using a combination of bolus administration of medicament and basal administration of medicament.

35. The integrated system of claim 26, further comprising programming that, when executed by a processor, estimates glucose values of the host in the future using a prediction algorithm and wherein the programming that, when executed by a processor, automatically detects impending clinical risk is configured to detect impending clinical risk based on the estimated glucose values.

36. An integrated system for monitoring and treating diabetes, the system comprising:

a glucose sensor, wherein the glucose sensor substantially continuously measures glucose in a host for a period exceeding one hour, and outputs a data stream, including one or more sensor data points;

a receiver operably connected to the glucose sensor, wherein the receiver is configured to receive the data stream; and

a medicament delivery device, wherein the delivery device is operably connected to the receiver,

wherein at least one of the receiver or the medicament delivery device automatically detect impending clinical risk and calculates a therapy recommendation responsive to the impending clinical risk,

wherein the at least one of the receiver or the medicament delivery device further require the at least one of the receiver or the medicament delivery device to be at least one of validated or confirmed by a user interaction in response to a prompt on a user interface of at least one of the receiver or the medicament delivery device for administration of the therapy recommendation,

wherein the integrated system operates in a fully-automated mode unless a semi-automated mode is triggered, wherein the semi-automated mode is triggered responsive to the detection of the impending clinical risk,

wherein the medicament device comprises bolus medicament delivery,

wherein, while in the fully-automated mode, the programming that, when executed by a processor, operates the integrated system does not require user interaction to administer medicament using the continuous medicament delivery and does not require user interaction to administer a bolus administration of medicament, and

wherein, while in the semi-automated mode, the programming that, when executed by a processor, operates the integrated system does not require user interaction to administer medicament using the continuous medicament delivery and requires user interaction to administer medicament a bolus administration of medicament.

37. The integrated system of claim 36, wherein the system is further configured to alarm the patient responsive to the switching from the fully-automated mode to the semi-automated mode.

38. The integrated system of claim 36, wherein the clinical risk is an identified danger or potential risk to the health of the host based on a measured or estimated glucose concentration value of the host.

39. The integrated system of claim 36, wherein the clinical risk is an identified danger or potential risk to the health of the host based on a measured or estimated rate of change of the glucose concentration of the host.

40. The integrated system of claim 36, wherein the clinical risk is an identified danger or potential risk to the health of the host based on an estimated or measured acceleration of the glucose concentration of the host.

41. The integrated system of claim 36, wherein the impending clinical risk is determined based on a discrepancy of a glucose value measured by a single point glucose monitor from sensor data of the continuous glucose sensor that could cause a risk to the patient if incorrect therapy is administered.

42. The integrated system of claim 36, further comprising programming that, when executed by a processor, adaptively learns patterns of the host, and wherein the impending clinical risk is determined based on the learned patterns.

43. The integrated system of claim 36, further comprising programming that, when executed by a processor, determines a host'"'"'s metabolic response to medicament delivery using a pattern recognition algorithm, wherein the programming that, when executed by a processor, calculates the therapy recommendation, calculates the therapy recommendation based on the determined metabolic response.

44. The integrated system of claim 36, wherein the continuous medicament delivery device is configured to administer medicament therapy using a combination of bolus administration of medicament and basal administration of medicament.

45. The integrated system of claim 36, further comprising programming that, when executed by a processor, estimates glucose values of the host in the future using a prediction algorithm and wherein the programming that, when executed by a processor, automatically detects impending clinical risk is configured to detect impending clinical risk based on the estimated glucose values.