SYSTEM AND METHOD OF INCREASING SAMPLE THROUGHPUT

• US 20130046478A1
• Filed: 08/16/2011
• Published: 02/21/2013
• Est. Priority Date: 08/16/2011
• Status: Active Grant

• Current Assignee: Instrumentation Lab Co (Instrumentation Lab)
• Original Assignee: Instrumentation Lab Co (Instrumentation Lab)
• Inventors: Mansouri, Sohrab, Cervera, Jose Maria
• Granted Patent: US 8,560,251 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: C12Q 1/002 Electrode membranes
• CPC Class Codes: C12Q 1/006 for glucose
• CPC Class Codes: G01N 2035/00702 Curve-fitting; Parameter matching; Calibration constants
• CPC Class Codes: G01N 2035/0097 monitoring reactions as a function of time
• CPC Class Codes: G01N 27/327 Biochemical electrodes , e.g. electrical or mechanical details for in vitro measurements
• CPC Class Codes: G01N 33/48792 Data management, e.g. communication with processing unit for in vivo diagnostics A61B5/0002; transmission systems for measured values G08C
• CPC Class Codes: G01N 33/50 Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing measuring or testing processes involving enzymes or microorganisms, compositions or test papers therefor; processes for forming such compositions, condition responsive control in microbiological or enzymological processes C12Q
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis

Abstract

Technologies for increasing sample throughput by predicting the end point response time of a sensor for the analysis of an analyte in a sample are disclosed. In one aspect, a system includes a sensor that generates data signals associated with the measurement of an analyte within the sample. A processor records appropriate data points corresponding to the signals, converts them to a logarithmic function of time scale, and plots the converted data points. The processor then determines a curve that fits the plotted data points and determines a curve fitting equation for the curve. Once the equation is determined, the processor extrapolates an end point response of the sensor using the equation. A value, such as analyte concentration, is then calculated using the extrapolated end point response.

Claims

1. A system for increasing sample throughput, comprising:

a sensor configured to generate data signals in response to being exposed to an analyte within a sample; and

a processor configured to

record data points associated with the data signals,

select a series of data points corresponding to a portion of a kinetic region time range from the recorded data points,

convert the selected data points to a logarithmic function of time scale,

evaluate the converted data points,

determine a curve that fits the evaluate data points,

determine a curve fitting equation corresponding to the curve,

extrapolate an end point response of the sensor using the curve fitting equation, and

calculate, using the extrapolated end point response, a value corresponding to the analyte.

2. The system of claim 1, wherein the curve fitting equation is of the form s(t)=a*(log(t))̂

2+b*log(t)+c, wherein t represents time and a, b and c are fit parameters for a second order polynomial and are determined based on the initial sensor response.

3. The system of claim 1, wherein the data points are recorded at equal intervals.

4. The system of claim 1, wherein the kinetic region time range extends from a first time when the sensor is first exposed to the analyte to a second time when the data signals generated by the sensor are substantially similar to an actual end point response of the sensor.

5. The system of claim 4, wherein the portion of the kinetic region time range begins at approximately fifteen seconds after the sensor is exposed to the analyte.

6. The system of claim 4, wherein the portion of the kinetic region time range ends approximately thirty seconds after the sensor is exposed to the analyte.

7. The system of claim 1, wherein extrapolating an end point response of the sensor using the curve fitting equation comprises solving the curve fitting equation for a time when then the data signals generated by the sensor are substantially similar to an actual end point response of the sensor.

8. The system of claim 1, wherein the sensor is configured to have a diffusion controlled response.

9. The system of claim 1, wherein the processor is further configured to:

determine a concentration of the analyte using the calculated end point response; and

present the determined concentration of the analyte.

10. The system of claim 1, wherein the processor is further configured to validate the calculated value corresponding to the analyte.

11. The system of claim 10, wherein validating the calculated end point response comprises:

determining a coefficient of variation;

determining a coefficient of determination; and

determining whether the determined coefficient of variation and coefficient of determination are within acceptable limits

12. The system of claim 11, wherein the processor is further configured to:

determine a concentration of the analyte using the calculated end point response; and

upon determining that the determined coefficient of variation and coefficient of determination are within acceptable limits, present the determined concentration of the analyte without a flag; and

upon determining that at least one of the determined coefficient of variation and coefficient of determination is not within acceptable limits, present the determined concentration of the analyte with a flag.

13. The system of claim 1, further comprising:

presenting, as an output, the calculated value corresponding to the analyte.

14. A method for increasing sample throughput, comprising:

receiving, from a sensor, data signals generated in response to being exposed to an analyte within a sample;

recording data points associated with the data signals;

selecting a series of data points corresponding to a portion of a kinetic region time range from the recorded data points;

converting the selected data points to a logarithmic function of time scale;

plotting the converted data points;

determining a curve that fits the plotted data points;

determining a curve fitting equation corresponding to the curve;

extrapolating an end point response of the sensor using the curve fitting equation; and

calculating, using the extrapolated end point response, a value corresponding to the analyte.

15. The method of claim 14, wherein the curve fitting equation is of the form s(t)=a*(log(t))̂

2+b*log(t)+c, wherein t represents time and a, b and c are the fit parameters for second order polynomial and are determined based on the initial sensor response.

16. The method of claim 14, wherein selecting a series of data points corresponding to a portion of a kinetic region time range from the recorded data points comprises selecting data points that correspond to a time period beginning when the sensor is first exposed to the analyte and ending when the data signals generated by the sensor are substantially similar to an actual end point response of the sensor.

17. The method of claim 14, wherein selecting a series of data points corresponding to a portion of a kinetic region time range from the recorded data points comprises selecting data points that correspond to a time period beginning at about fifteen seconds after the sensor is exposed to the analyte and ending about thirty seconds after the sensor is exposed to the analyte.

18. The method of claim 14, wherein extrapolating an end point response of the sensor using the curve fitting equation comprises solving the curve fitting equation for a time when then the data signals generated by the sensor are substantially similar to an actual end point response of the sensor.

19. The method of claim 14, further comprising:

determining a concentration of the analyte using the calculated end point response; and

presenting the determined concentration of the analyte.

20. The method of claim 14, wherein the processor is further configured to validate the calculated value corresponding to the analyte by:

determining a coefficient of variation;

determining a coefficient of determination; and

determining whether the determined coefficient of variation and coefficient of determination are within acceptable limits.

21. A computer-readable storage medium having computer executable instructions stored thereon, which when executed by a computer, cause the computer to:

receive, from a sensor, data signals generated in response to being exposed to an analyte within a sample;

evaluate a curve defined by a second order quadratic equation that matches the data signals received from the sensor;

extrapolate an end point response of the sensor using the curve; and

calculate, using the extrapolated end point response, a value corresponding to the analyte.

22. The computer-readable storage medium of claim 21, wherein the curve fitting equation is of the form s(t)=a*(log(t))̂

2+b*log(t)+c, wherein t represents time and a, b and c are the fit parameters for second order polynomial and are determined based on the initial sensor response.

23. The computer-readable storage medium of claim 21, having further computer-executable instructions stored thereon, which when executed by the computer cause the computer to:

determine a concentration of the analyte using the calculated value corresponding to the analyte; and

present the determined concentration of the analyte.

24. The computer-readable storage medium of claim 21, having further computer-executable instructions stored thereon, which when executed by the computer cause the computer to:

validate the calculated value corresponding to the analyte by

determining a coefficient of variation;

determining a coefficient of determination; and

determining whether the determined coefficient of variation and coefficient of determination are within acceptable limits.