CALIBRATION SURFACE METHOD FOR DETERMINATION OF ANALYTE RATIOS

• US 20100049444A1
• Filed: 08/21/2008
• Published: 02/25/2010
• Est. Priority Date: 08/21/2008
• Status: Active Grant

• Current Assignee: Bio-Rad Laboratories Incorporated
• Original Assignee: Bio-Rad Laboratories Incorporated
• Inventors: Likuski, Robert, Walker, Roger, Lu, Yabin
• Granted Patent: US 8,260,556 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: G01N 33/721 Haemoglobin
• CPC Class Codes: G01N 33/723 Glycosylated haemoglobin

Abstract

The ratio of analytes is determined directly from the responses of the analytes using a conversion method. Individual analyte responses are obtained by using a selected measuring technique, and these individual responses are used as the independent variables in a conversion method. The dependent variable of conversion method is the desired analyte ratio. The resulting conversion method is then used to directly calculate the desired ratio of analytes as a function of the measured responses. No intermediate conversions, such as using a calibration curve to convert individual measured analyte responses to concentration values, are needed to obtain the desired ratio.

Claims

1. A method for determining one or more ratios of analytes in a sample, said method comprising:

measuring responses of two or more analytes in a sample using a selected measuring process to obtain two or more individual analyte responses;

selecting one or more conversion methods that define a ratio of analytes as a direct function of the individual analyte responses obtained using the selected measuring process; and

computing one or more ratio of analytes in the sample using the selected one or more conversion methods and using the individual analyte responses obtained using the selected measuring process.

2. The method of claim 1 wherein one of the ratio of analytes computed is related to the ratio of the concentrations of two analytes in the sample.

4. The method of claim 1 wherein the conversion method relates the individual analyte responses to the ratio of the analytes using a regression as part of the conversion method.

5. The method of claim 4 wherein the regression is a polynomial regression in which the variables are products of the analyte responses raised to integer powers.

6. The method of claim 4 wherein the individual analyte responses used in the conversion method undergo a transformation as a part of the conversion method.

7. The method of claim 6 wherein the transformation reduces the number of regression terms used in the regression model.

8. The method of claim 6 wherein the transformation facilitates a longer laboratory calibration interval.

9. The method of claim 6 wherein the transformation reduces the number of calibrations needed for a laboratory calibration.

10. The method of claim 6 wherein the transformation mathematically combines two of the individual analyte responses.

11. The method of claim 6 wherein the transformation is defined as

x₁=[(z₁−

a₁₂)^a11−

a₁₃]÷

[(z₂−

a₂₂)^a21−

a₂₃]

x₂=└

(z₂−

b₁₂)^b11−

b₁₃┘

÷

└

(z₁−

b₂₂)^b21−

b₂₃┘

wherein z₁ and z₂ are the measured analyte responses;

wherein x₁ and x₂ are transformed responses;

wherein a₁₁, a₁₂, a₁₃, a₂₁, a₂₂, and a₂₃ are coefficients that can be calibrated.

12. The method of claim 6 wherein the transformation uses one or more coefficients that are not determined on a regular user calibration schedule.

13. The method of claim 6 wherein the transformation uses one or more coefficients that are determined on a user lot schedule.

14. The method of claim 6 wherein the selected measuring process is HPLC.

15. The method of claim 6 wherein the selected measuring process is immunoassay.

16. The method of claim 6 wherein the selected measuring process is one of electrophoresis, capillary electrophoresis, spectrometry, chromatography, surface plasmon resonance.

17. The method of claim 6 wherein the one or more of the analytes are proteins, carbohydrates, or nucleic acids.

18. The method of claim 6 wherein the analytes are glycoproteins.

19. The method of claim 18 wherein one of the analytes is hemoglobin A1c.

20. The method of claim 6 wherein there are two analytes to be expressed as a analyte ratio and wherein the two analytes are a glycosylated form of hemoglobin and total hemoglobin.

3. The method of claim 3 wherein the relationship is the concentration of one analyte divided by the concentration of another analyte.

21. An apparatus for measuring the concentration ratio of two or more analytes, said apparatus comprising:

a measuring module capable of measuring the responses of analytes in a sample;

a memory to store the measured analyte responses from the measuring module;

a computer readable medium containing computer readable code having instructions for executing a conversion method that defines the analyte ratio of analytes as a direct function of the individual responses of the analytes obtained from the measuring module; and

a processor to execute the computer readable code on the computer readable medium in order to calculate the concentration ratio of analytes using the conversion method.

22. The apparatus of claim 21 wherein the measuring module uses a multi-plex immunoassay to measure the analytes responses.

23. A method for calculating a conversion method that defines the ratio of the analyte values of the analytes as a direct function of the individual responses of the analytes obtained from a measuring process, said method comprising:

selecting a statistically sufficient number of appropriate calibrators to be used to compute the conversion method, wherein said calibrators have a known ratio of the analytes;

selecting a measuring process to be used to measure the responses of the analytes in the calibrators;

measuring the responses of the analytes in the calibrators using the measuring process;

selecting a regression model to be used to calculate the conversion method; and

using the regression model to yield the conversion method wherein the regression model uses the responses of the analytes as the independent variables and the known analyte ratios as the dependent variable.

24. The method of claim 23 wherein the two analyte responses are transformed into the two independent variable of the regression model in a way to best reduce the pure variance and lack-of-fit variance of the desired analyte ratios.

25. A computer-readable medium comprising:

code for measuring the responses of the analytes in a sample using a selected measuring process;

code for selecting a conversion method that defines the ratio of analytes as a direct function of the individual responses of the analytes obtained from the selected measuring process; and

code for computing the ratio of the analytes of the sample using the selected conversion method and the measured analyte responses from the sample.