Method and apparatus for biosensor spectral shift detection

• US 7,217,574 B2
• Filed: 09/25/2002
• Issued: 05/15/2007
• Est. Priority Date: 10/30/2000
• Status: Expired due to Term

• Current Assignee: X-Body Incorporated (Bristol-Myers Squibb Company)
• Original Assignee: Sru Biosystems Incorporated
• Inventors: Li, Peter, Cunningham, Brian, Karl, William C., Pien, Homer, Puff, Derek
• Primary Examiner(s): Chin; Christopher L.
• Application Number:
  US10/253,846
• Publication Number:
  US 20030077660A1
• Time in Patent Office: 1,693 Days
• Field of Search: None
• US Class Current: 436/164
• CPC Class Codes: B01L 3/5085 for multiple samples, e.g. microtitration plates
• CPC Class Codes: G01J 3/02 Details
• CPC Class Codes: G01J 3/0218 using optical fibers
• CPC Class Codes: G01J 3/0224 using polarising or depolarising elements
• CPC Class Codes: G01J 3/1804 Plane gratings
• CPC Class Codes: G01J 3/42 Absorption spectrometry; Double beam spectrometry; Flicker spectrometry; Reflection spectrometry beam switching arrangements G01J3/08
• CPC Class Codes: G01N 2021/3196 Correlating located peaks in spectrum with reference data, e.g. fingerprint data
• CPC Class Codes: G01N 2021/7773 Reflection
• CPC Class Codes: G01N 21/253 for batch operation, i.e. multisample apparatus analytical automats G01N35/00
• CPC Class Codes: G01N 21/31 Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry G01N21/72 takes precedence
• CPC Class Codes: G01N 21/7743 the reagent-coated grating coupling light in or out of the waveguide
• CPC Class Codes: G01N 33/54373 involving physiochemical end-point determination, e.g. wave-guides, FETS, gratings
• CPC Class Codes: G02B 5/1809 with pitch less than or comparable to the wavelength
• CPC Class Codes: Y10S 436/805 Optical property

Abstract

Performing high-resolution determination of the relative shift of the spectral properties of a biosensor. The shift in the resonance peak of the biosensor is indicative of the amount of material bound to the surface of the biosensor. A preferred biosensor is a Guided Mode Resonant Filter Biosensor (GMRFB). In one aspect of the invention, curve fitting is used to determine the relative location of the spectrum of the unexposed biosensor with respect to those spectra that are altered (e.g., shifted) by the presence of materials bound to the surface of the biosensor. In an alternative embodiment, the cross correlation function is used to detect spectral peak offsets between a reference spectrum and a spectrum measured from an exposed biosensor. In yet another alternative, maximal likelihood estimation techniques are used to determine the spectral shift or offs.

Claims

1. A method for determining biosensor resonance peak offsets comprising the steps:

(i) determining a reference spectrum and a sample spectrum, the reference spectrum having a magnitude and a slope; and

,

(ii) determining a peak resonance offset in response to the slope of the reference spectrum.

2. The method of claim 1 wherein the step of determining a peak resonance offset comprises determining an offset that minimizes a criteria for a set of linear equations, wherein each linear ecluation represents the difference between an error term and the product of the slope with a phase shift update, Δ

θ

.

3. The method of claim 1 wherein the step of determining a peak resonance offset comprises determining reference band edges in response to the slope of the reference spectrum weighted by the signal amplitudes of the reference spectrum, determining sample band edges in response to the slope of the sample spectrum weighted by the signal amplitudes of the sample spectrum, and determining a relative change in band edges between the reference spectrum and the sample spectrum.

4. The method of claim 1 wherein the step of determining a peak resonance offset is performed by weighting the slope of the reference spectrum by the signal amplitudes of the reference spectrum.

5. The method of claim 1 wherein the roles of the reference spectrum and the sampled spectrum are reversed, and the estimation is performed in response to the slope of shifted versions of the sampled spectrum.

6. The method of claim 1, wherein the step of determining a peak resonance offset in response to the slope of the reference spectrum comprises the steps:

(a) determining an initial offset estimate;

(b) determining an offset update value;

(c) updating the initial offset estimate in response to the offset update value.

7. The method of claim 6 wherein steps (b) and (c) are repeated until a determined offset update value is below a predetermined threshold.

8. The method of claim 6 wherein the step of determining an initial offset value is performed by one of the following steps:

(a) determining an offset corresponding to a peak resonance value;

(b) determining an offset corresponding to a peak correlation value;

(c) determining an offset corresponding to a difference between measured band edges and reference band edges.

9. The method of claim 6 wherein the offset update value is responsive to the derivative of the reference spectrum.

10. The method of claim 6 wherein the offset update value is determined using a least squares criterion.

11. The method of claim 6 wherein the offset update value is determined using a criterion based on maximal likelihood estimation.

12. The method of claim 1 wherein the step of determining a peak resonance offset comprises performing an interative calculation to estimate spectral offset of the sample spectrum based on a maximal likelihood estimation, wherein each iteration is performed in response to the signal amplitude values of the reference spectrum and the sample spectrum and signal slope values of at least one of the reference spectrum and the measured spectrum.

13. The method of claim 12 wherein the iterative calculation is performed until the spectral offset estimate has converged.

14. The method of claim 12 wherein the iterative calculation uses signal values of one of the reference spectrum and the sample spectrum as estimates of noise values.