MEASUREMENT DEVICES AND METHODS FOR MEASURING ANALYTE CONCENTRATION INCORPORATING TEMPERATURE AND PH CORRECTION

• US 20110224516A1
• Filed: 03/11/2011
• Published: 09/15/2011
• Est. Priority Date: 03/11/2010
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: GluMetrics, Inc.
• Inventors: Romey, Matthew A., Gamsey, Soya, Peyser, Thomas A.
• Granted Patent: US 8,473,222 B2
• Time in Patent Office: Days
• US Class Current: 600/317
• CPC Class Codes: A61B 2560/0247 for compensation or correction of the measured physiological value
• CPC Class Codes: A61B 2560/0252 using ambient temperature
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1459 invasive, e.g. introduced into the body by a catheter A61B5/1464 takes precedence
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: G01N 2021/6419 Excitation at two or more wavelengths
• CPC Class Codes: G01N 2021/6484 Optical fibres
• CPC Class Codes: G01N 2021/7793 Sensor comprising plural indicators
• CPC Class Codes: G01N 21/6428 Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes" in vivo A61B5/00; immunoassay G01N33/53
• CPC Class Codes: G01N 21/7703 using reagent-clad optical fibres or optical waveguides using measurement of total internal reflection or attenuated total reflection G01N21/552; optical fibres or waveguides per se G02B
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00

Abstract

Disclosed herein are methods of estimating an analyte concentration which include generating a signal indicative of the analyte concentration, generating a signal indicative of a temperature, generating a signal indicative of a pH, and transforming the signal indicative of the analyte concentration utilizing an equation of the form of a modified Michaelis-Menten equation depending on Michaelis-Menten parameters, wherein values of the Michaelis-Menten parameters are set based upon data which includes temperature and pH calibration parameters, the signal indicative of a temperature, and the signal indicative of a pH. Also disclosed herein are measurement devices which employ the aforementioned methods.

Claims

1. A method of estimating an analyte concentration in a physiologic fluid, comprising:

contacting an analyte sensing element with the fluid, wherein the analyte sensing element is configured to generate a signal indicative of the analyte concentration in the fluid;

detecting the signal indicative of the analyte concentration;

contacting a temperature sensing element with the fluid, wherein the temperature sensing element is configured to generate a signal indicative of a temperature of the fluid;

detecting the signal indicative of the temperature of the fluid; and

transforming the detected signal indicative of the analyte concentration utilizing a modified Michaelis-Menten equation comprising Michaelis-Menten parameters, wherein the Michaelis-Menten parameters are set based on data comprising;

temperature calibration data; and

the detected signal indicative of temperature.

2. The method of claim 1, wherein both the analyte sensing element and the temperature sensing element are incorporated within a single sensor.

3. The method of claim 1, wherein the temperature calibration data is generated by a temperature calibration method comprising:

providing at least three solutions of differing known analyte concentrations;

providing a first test analyte sensing element;

generating a first set of at least three signals using the first test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at a first temperature;

generating a second set of at least three signals using the first test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at a second temperature.

4. The method of claim 3, wherein the temperature calibration method further comprises:

determining values of each of a first, second, and third Michaelis-Menten parameter at the first temperature by an algorithm comprising fitting a modified Michaelis-Menten equation to a first fit dataset comprising the first set of at least three signals;

determining values of each of a first, second, and third Michaelis-Menten parameter at the second temperature by an algorithm comprising fitting a modified Michaelis-Menten equation to a second fit dataset comprising the second set of at least three signals;

selecting an equation relating the first, second, and third Michaelis-Menten parameters to temperature, the equation depending on a first set, second set, and third set of temperature calibration parameters respectively;

determining a value for each calibration parameter of the first, second, and third set of calibration parameters based on the value of the first, second, and third Michaelis-Menten parameters respectively at the first temperature; and

determining a value for each calibration parameter of the first, second, and third set of calibration parameters based on the value of the first, second, and third Michaelis-Menten parameters respectively at the second temperature.

5. The method of claim 4, wherein:

for the step of selecting an equation, equations linear in temperature are selected to relate the first, second, and third Michaelis-Menten parameters to temperature; and

each of the first, second, and third sets of temperature calibration parameters comprise a slope and an intercept relating temperature to the value of either the first, second, or third Michaelis-Menten parameter.

6. The method of claim 4, wherein the temperature calibration method further comprises:

providing a second test analyte sensing element;

generating a third set of at least three signals using the second test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at the first temperature;

generating a fourth set of at least three signals using the test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at the second temperature.

7. The method of claim 6, wherein generating values of each of a first, second, and third Michaelis-Menten parameter at the first temperature by an algorithm further comprises:

fitting a modified Michaelis-Menten equation to a third fit dataset comprising the third set of at least three signals;

averaging the results of fitting the third fit dataset with the results of fitting the first fit dataset; and

determining each of a first, second, and third Michaelis-Menten parameter at the second temperature by

fitting a modified Michaelis-Menten equation to a fourth fit dataset comprising the fourth set of at least three signals; and

averaging the results of fitting the fourth fit dataset with the results of fitting the second fit dataset.

8. The method of claim 1, wherein transforming the signal indicative of the analyte concentration utilizing an equation of the form of a modified Michaelis-Menten equation comprises at least one of the Michaelis-Menten parameters substituted with a calibration equation that depends on a set of one or more temperature calibration parameters and the signal indicative of the temperature.

9. The method of claim 8, wherein transforming the signal indicative of the analyte concentration utilizes an equation of the form of a modified Michaelis-Menten equation wherein:

the first Michaelis-Menten parameter has been substituted with a first calibration equation functionally depending on a first set of one or more temperature calibration parameters and the signal indicative of temperature;

the second Michaelis-Menten parameter has been substituted with a second calibration equation functionally depending on a second set of one or more temperature calibration parameters and the signal indicative of temperature; and

the third Michaelis-Menten parameter has been substituted with a third calibration equation functionally depending on a third set of one or more temperature calibration parameters and the signal indicative of temperature.

10. A method of estimating an analyte concentration in a physiologic fluid, comprising:

contacting an analyte sensing element with the fluid, wherein the analyte sensing element is configured to generate a signal indicative of the analyte concentration in the fluid;

detecting the signal indicative of the analyte concentration;

contacting a pH sensing element with the fluid, wherein the pH sensing element is configured to generate a signal indicative of a pH of the fluid;

detecting the signal indicative of the pH of the fluid; and

transforming the signal indicative of the analyte concentration utilizing a modified Michaelis-Menten equation comprising Michaelis-Menten parameters, wherein the Michaelis-Menten parameters are set based on data comprising;

pH calibration data; and

the detected signal indicative of pH.

11. The method of claim 10, wherein both the analyte sensing element and the pH sensing element are incorporated within a single sensor.

12. The method of claim 10, wherein the pH calibration data was generated by a pH calibration method comprising:

providing at least three solutions of differing known analyte concentrations;

providing a first test analyte sensing element;

selecting a first pH;

generating a first set of at least three signals using the first test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at the first pH;

selecting a second pH; and

generating a second set of at least three signals using the first test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at the second pH.

13. The method of claim 12, wherein the pH calibration method further comprises:

determining values of each of a first, second, and third Michaelis-Menten parameter at the first pH by an algorithm comprising fitting a modified Michaelis-Menten equation to a first fit dataset comprising the first set of at least three signals;

determining values of each of a first, second, and third Michaelis-Menten parameter at the second pH by an algorithm comprising fitting a modified Michaelis-Menten equation to a second fit dataset comprising the second set of at least three signals;

selecting an equation relating the first, second, and third Michaelis-Menten parameter to pH, the equation depending on a first, second, and third set of pH calibration parameters respectively;

setting a value for each calibration parameter of the first, second, and third set of calibration parameters based on the value of the first, second, and third Michaelis-Menten parameters respectively at the first pH and the value of the first, second, and third Michaelis-Menten parameters respectively at the second pH.

14. The method of claim 13, wherein:

a first equation linear in pH is selected to relate the first Michaelis-Menten parameter to pH;

a second equation linear in pH is selected to relate the second Michaelis-Menten parameter to pH; and

an equation is selected to relate the third Michaelis-Menten parameter to pH which comprises a fraction wherein the numerator is equal to an exponential function of an equation linear in the inverse of pH, and the denominator is equal to an exponential function of the same linear function in the inverse of pH evaluated at fixed pH.

15. The method of claim 13, wherein the pH calibration method further comprises:

providing a second test analyte sensing element;

generating a third set of at least three signals using the second test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at the first pH;

generating a fourth set of at least three signals using the test analyte sensing element, each signal indicative of the concentration of analyte in a different solution of the at least three solutions at the second pH.

16. The method of claim 15, wherein determining values of each of a first, second, and third Michaelis-Menten parameter at the first pH by an algorithm further comprises:

fitting a modified Michaelis-Menten equation to a third fit dataset comprising the third set of at least three signals; and

averaging the results of fitting the third fit dataset with the results of fitting the first fit dataset; and

wherein generating values of each of a first, second, and third Michaelis-Menten parameter at the second pH by

fitting a modified Michaelis-Menten equation to a fourth fit dataset comprising the fourth set of at least three signals; and

averaging the results of fitting the fourth fit dataset with the results of fitting the second fit dataset.

17. The method of claim 10, wherein transforming the signal indicative of the analyte concentration utilizing an equation of the form of a modified Michaelis-Menten equation comprises at least one of the Michaelis-Menten parameters substituted with a calibration equation that depends on a set of one or more pH calibration parameters and the signal indicative of pH.

18. The method of claim 17, wherein the step of transforming the signal indicative of the analyte concentration utilizes an equation of the form of a modified Michaelis-Menten equation wherein:

the first Michaelis-Menten parameter has been substituted with a first calibration equation functionally depending on a first set of one or more pH calibration parameters and the signal indicative of pH;

the second Michaelis-Menten parameter has been substituted with a second calibration equation functionally depending on a second set of one or more pH calibration parameters and the signal indicative of pH; and

the third Michaelis-Menten parameter has been substituted with a third calibration equation functionally depending on a third set of one or more pH calibration parameters and the signal indicative of pH.

19. A method of estimating an analyte concentration in a physiologic fluid comprising:

contacting an analyte sensor with the fluid, wherein the analyte sensor is configured to generate a signal indicative of the analyte concentration;

detecting the signal indicative of the analyte concentration;

contacting a temperature sensing element configured to generate a signal indicative of a temperature;

detecting the signal indicative of the temperature;

contacting a pH sensing element configured to generate a signal indicative of a pH;

detecting the signal indicative of the pH; and

transforming the signal indicative of the analyte concentration utilizing a modified Michaelis-Menten equation depending on Michaelis-Menten parameters, wherein the Michaelis-Menten parameters are set based on data comprising;

temperature and pH calibration data;

the detected signal indicative of temperature; and

the detected signal indicative of pH.

20. The method of claim 19, wherein the analyte sensing element, the temperature sensing element and the pH sensing element are incorporated within a single sensor.

21. The method of claim 19, wherein the signal indicative of the analyte concentration, the signal indicative of the temperature, and the signal indicative of the pH are each generated from a set of at least three signals each of which is indicative of the temperature, the pH, and the analyte concentration.

22. The method of claim 19, wherein the temperature and pH calibration parameters are determined by a calibration method, the calibration method comprising:

selecting a first test analyte sensing element;

selecting three differing concentrations of analyte;

selecting a first temperature and a second temperature, the second differing from the first;

selecting a first pH and a second pH, the second differing from the first;

computing values of each of a first, second, and third Michaelis-Menten parameter at the first temperature by an algorithm comprising fitting a modified Michaelis-Menten equation to at least three signals indicative of the three differing concentrations of analyte in solution at the first temperature, the at least three signals generated using the first test analyte sensing element;

computing values of each of a first, second, and third Michaelis-Menten parameter at the second temperature by an algorithm comprising fitting a modified Michaelis-Menten equation to at least three signals indicative of the three differing concentrations of analyte in solution at the second temperature, the at least three signals generated using the first test analyte sensing element;

computing values of each of a first, second, and third Michaelis-Menten parameter at the first pH by an algorithm comprising fitting a modified Michaelis-Menten equation to at least three signals indicative of the three differing concentrations of analyte in solution at the first pH, the at least three signals generated using the first test analyte sensing element;

computing values of each of a first, second, and third Michaelis-Menten parameter at the second pH by an algorithm comprising fitting a modified Michaelis-Menten equation to at least three signals indicative of the three differing concentrations of analyte in solution at the second pH, the at least three signals generated using the first test analyte sensing element;

selecting a first calibration equation relating the first Michaelis-Menten parameter to temperature and pH, the equation depending on a first set of the temperature and pH calibration parameters, and setting a value for each parameter based on the values of the first Michaelis-Menten parameter at the first temperature, the second temperature, the first pH, and the second pH;

selecting a second calibration equation relating the second Michaelis-Menten parameter to temperature and pH, the equation depending on a second set of the temperature and pH calibration parameters, and setting a value for each parameter based on the values of the second Michaelis-Menten parameter at the first temperature, the second temperature, the first pH, and the second pH; and

selecting a third calibration equation relating the third Michaelis-Menten parameter to temperature and pH, the equation depending on a third set of the temperature and pH calibration parameters, and setting a value for each parameter based on the values of the third Michaelis-Menten parameter at the first temperature, the second temperature, the first pH, and the second pH.

23. The method of claim 22, wherein:

the first calibration equation is the product of a first pH-independent function and a first temperature-independent function;

the second calibration equation is the product of a second pH-independent function and a second temperature-independent function; and

the third calibration equation is the product of a third pH-independent function and a third temperature-independent function.

24. The method of claim 23, wherein:

the first, second, and third pH-independent functions are linear in temperature;

the first, and second temperature-independent functions are linear in pH; and

the third temperature-independent function is a fraction wherein the numerator is equal to an exponential function of a function linear in the inverse of pH, and the denominator is equal to an exponential function of the same function linear in the inverse of pH evaluated at fixed pH.

25. The method of claim 24, wherein transforming the signal indicative of the analyte concentration utilizing an equation of the form of a modified Michaelis-Menten equation comprises at least one of the Michaelis-Menten parameters substituted with a calibration equation functionally that depends on a set of one or more temperature calibration parameters, pH calibration parameters, the signal indicative of the temperature, and the signal indicative of the pH.

26. The method of claim 25, wherein the step of transforming the signal indicative of the analyte concentration utilizes an equation of the form of a modified Michaelis-Menten equation wherein:

the first Michaelis-Menten parameter has been substituted with a first calibration equation functionally depending on a first set of temperature and pH calibration parameters, the signal indicative of the temperature, and the signal indicative of the pH;

the second Michaelis-Menten parameter has been substituted with a second calibration equation functionally depending on a second set of temperature and pH calibration parameters, the signal indicative of temperature, and the signal indicative of pH; and

the third Michaelis-Menten parameter has been substituted with a third calibration equation functionally depending on a third set of temperature and pH calibration parameters, the signal indicative of temperature, and the signal indicative of pH.

27. A measurement device for estimating an analyte concentration comprising:

an analyte sensing element configured to generate a first signal indicative of the analyte concentration;

a temperature sensing element configured to generate a second signal indicative of a temperature; and

a receiving and processing unit configured to transform the first signal utilizing a modified Michaelis-Menten equation depending on Michaelis-Menten parameters, wherein values of the Michaelis-Menten parameters are set based upon data comprising;

temperature calibration data; and

the second signal.

35. The measurement device of any of claim 27, 29, or 34, further comprising a sensor probe wherein the temperature sensor and the analyte sensor are co-located within a distal tip of the sensor probe.

28. A measurement device for estimating an analyte concentration comprising:

an analyte sensor configured to generate a first signal indicative of the analyte concentration;

a pH sensor configured to generate a second signal, the second signal indicative of a pH; and

a receiving and processing unit configured to transform the first signal utilizing a modified Michaelis-Menten equation depending on Michaelis-Menten parameters, wherein values of the Michaelis-Menten parameters are set based upon data comprising;

pH calibration data; and

the second signal.

29. The measurement device of claim 28, further comprising:

a temperature sensor configured to generate a third signal indicative of a temperature of the sample;

wherein values of the Michaelis-Menten parameters are set based upon data further comprising;

temperature data; and

the third signal.

30. The measurement device of any of claims 28-29, wherein the analyte sensor comprises:

at least one light source configured to generate light;

an indicator system comprising;

at least one type of fluorophore which emits a fluorescence having an intensity in response to light from the at least one light source; and

at least one type of binding moiety capable of binding the analyte, the at least one type of binding moiety operably coupled to the at least one type of fluorophore, such that when the sample contacts the at least one type of binding moiety the intensity is indicative of the concentration of the analyte; and

at least one detector configured to detect the intensity and generate a signal indicative of the analyte concentration of the sample in response to the intensity.

34. The measurement device of any of claim 30 or 33, wherein the indicator system further comprises an immobilizing medium configured to prevent some of the fluorophores and/or some of the binding moieties from freely diffusing through the sample.

31. A measurement device for estimating an analyte concentration of a sample, the measurement device comprising:

an analyte and pH sensor configured to generate;

a first signal indicative of the analyte concentration of the sample and a pH of the sample; and

a second signal indicative of the analyte concentration of the sample and the pH of the sample; and

a receiving and processing unit configured to transform a third signal utilizing an equation of the form of a modified Michaelis-Menten equation depending on Michaelis-Menten parameters, wherein the third signal is indicative of the analyte concentration and is generated based upon data comprising the first signal and the second signal, and wherein values of the Michaelis-Menten parameters are set based upon data comprising;

pH calibration data; and

a fourth signal, the fourth signal indicative of the pH and generated based upon data comprising the first signal and the second signal.

32. The measurement device of claim 31, further comprising:

a temperature sensor configured to generate a fifth signal, the fifth signal indicative of a temperature of the sample;

wherein the values of the Michaelis-Menten parameters are set based upon data further comprising temperature data and the fifth signal.

33. The measurement device of any of claim 31 or 32, wherein the analyte and pH sensor comprises:

at least one light source configured to generate light;

an indicator system comprising;

at least one type of fluorophore which emits a fluorescence having an intensity in response to light from the at least one light source; and

at least one type of binding moiety capable of binding the analyte, the at least one type of binding moiety operably coupled to the at least one type of fluorophore, such that when the sample contacts the at least one type of binding moiety the intensity is indicative of the concentration of the analyte and the pH; and

at least one detector configured to detect the intensity and generate a signal indicative of the analyte concentration of the sample and the pH of the sample in response to the intensity.