Method for enhancement in screening throughput

• US 6,763,322 B2
• Filed: 01/09/2002
• Issued: 07/13/2004
• Est. Priority Date: 01/09/2002
• Status: Expired due to Fees

• Current Assignee: Sabic Innovative Plastics IP BV (Government of Saudi Arabia)
• Original Assignee: General Electric Company
• Inventors: Shaffer, Ronald Eugene, Potyrailo, Radislav Alexandrovich
• Primary Examiner(s): Hoff, Marc S.
• Assistant Examiner(s): Barbee, Manuel L.
• Application Number:
  US10/040,420
• Publication Number:
  US 20030130823A1
• Time in Patent Office: 916 Days
• Field of Search: 702/19-32, 702/108, 702/109, 702/127, 702/176, 702/179, 702/182, 702/183, 702/184-191, 702/193, 702/194, 250/281, 250/282, 250/287, 250/339.09, 378/901, 378/4
• US Class Current: 702/189
• CPC Class Codes: G01J 3/28 Investigating the spectrum using colour filters G01J3/51
• CPC Class Codes: G01J 3/44 Raman spectrometry; Scattering spectrometry ; Fluorescence spectrometry
• CPC Class Codes: G01N 21/65 Raman scattering

Abstract

The present invention provides methods and an apparatus for the rapid analysis of data from imaging, spectroscopic, scanning probe, or sensor methods. By application of mathematical transform analysis such as wavelet transform algorithms to one or multi-order data sets obtained from individual samples or sample arrays, the analytical features of the data are preserved while undesired noise is removed, thereby reducing the integration time by more than 10-fold in subsequent measurements. The reduction in integration time enables the high-throughput measurement of combinatorial libraries and rapid dynamic processes, while still providing a signal-to-noise level suitable for a reliable measurement.

Claims

1. A method for reducing the time required for analyzing at least one sample for a parameter of interest which comprises:

selecting a pre-determined signal quality response function value;

selecting a pre-determined integration time T_a;

collecting analytical data from a sample with integration time T_a;

determining whether the analytical data collected from the sample with integration time T_a satisfies the pre-determined signal quality response function value prior to applying a screening rate accelerator toolbox;

applying the screening rate accelerator toolbox if the collected data does not satisfy the predetermined signal quality response function value.

said screening rate accelerator toolbox comprising mathematical transform analysis to the data, wherein the mathematical transform analysis is performed using conditions designed to achieve the pre-determined signal quality response function value comprising the value obtained when samples are analyzed without mathematical transform analysis using integration time T_b, wherein T_b is greater than T_a; and

analyzing the data processed by the screening rate accelerator toolbox for the parameter of interest.

2. The method of claim 1, wherein the mathematical transform analysis comprises multivariate analysis.

3. The method of claim 2, wherein the multivariate analysis comprises neural networks analysis, principal components analysis, partial least squares analysis, linear multivariate analysis, or nonlinear multivariate analysis.

4. The method of claim 1, wherein the mathematical transform analysis comprises discrete transform analysis.

5. The method of claim 1, wherein the mathematical transform analysis comprises continuous transform analysis.

6. The method of claim 1, wherein the mathematical analysis comprises time averaging analysis, smoothing analysis or Savitsky-Golay analysis.

7. The method of claim 1, wherein the mathematical transform analysis comprises Fourier transform, Gabor transform, or Hadamard transform.

8. The method of claim 1, wherein the mathematical transform analysis comprises wavelet transform.

9. The method of claim 8, wherein the wavelet transform analysis comprises a wavelet de-noising algorithm.

10. The method of claim 9, wherein the wavelet de-noising algorithm comprises wavelet filters.

11. The method of claim 9, wherein the wavelet de-noising algorithm comprises a threshold/shrinkage method.

12. The method of claim 1, wherein parameters of the mathematical transform are determined during the course of analysis.

13. The method of claim 1, further comprising the steps of:

determining whether the data processed by the screening rate accelerator toolbox satisfies the pre-determined signal quality response function value; and

if the processed data does not satisfy the pre-determined signal quality response value, re-applying the screening rate accelerator toolbox using a mathematical transform analysis different from the analysis previously applied until the data processed using the screen rate accelerator toolbox either satisfies the pre-determined signal quality response function value or comprises an optimized signal quality response function value.

14. The method of claim 13, further comprising repeating the method with a new, larger value for T_a if the data which is optimized using the screening rate accelerator toolbox does not satisfy the pre-determined signal quality response function value.

15. The method of claim 1, wherein if the collected data does not require application of the screening rate accelerator toolbox to satisfy a pre-determined signal quality response function value, a shorter pre-determined integration time T_a is selected, and the method is performed using the new value for T_a.

16. The method of claim 1, wherein the predetermined signal quality response function comprises one or more measured signal parameters.

17. The method of claim 16, wherein at least one of the measured signal parameters comprises signal resolution.

18. The method of claim 16, wherein at least one of the measured signal parameters comprises peak shift.

19. The method of claim 16, wherein at least one of the measured signal parameters comprises signal distortion.

20. The method of claim 16, wherein at least one of the measured signal parameters comprises a signal-to-noise ratio.

21. The method of claim 20, wherein the signal to noise ratio ranges from 1 to about 10,000.

22. The method of claim 20, wherein the signal to noise ratio ranges from 2 to 5,000.

23. The method of claim 20, wherein the signal to noise ratio ranges from 3 to 1,000.

24. The method of claim 1, wherein the relative improvement in signal integration time (T_b/T_a) ranges from about 1.5 to 1,000 fold.

25. The method of claim 1, wherein the relative improvement in signal integration time (T_b/T_a) ranges from about 1.5 to 500 fold.

26. The method of claim 1, wherein the relative improvement in signal integration time (T_b/T_a) ranges from about 1.5 to 200 fold.

27. The method of claim 1, wherein the analytical data comprises a first-order array.

28. The method of claim 1, wherein the analytical data comprises a multi-order array.

29. The method of claim 1, further comprising simultaneous evaluation of each individual sample in an array of samples.

30. The method of claim 1, wherein the analytical data comprise spectroscopic, imaging, sensor, or scanning data.

31. The method of claim 30, wherein the data further comprise measurements made using Raman, luminescence, ultraviolet-visible molecular absorbance, atomic absorbance, infra-red, near infrared, surface plasmon resonance, mass spectrometry, X-ray, nuclear magnetic resonance, refractometry, interferometry, scattering, inductively coupled plasma, atomic force microscopy, scanning tunneling microscopy, microwave evanescent wave microscopy, near-field scanning optical microscopy, atomic fluorescence, laser-induced breakdown spectroscopy, Auger electron spectroscopy, X-ray photoelectron spectroscopy, ultrasonic spectroscopy, dielectric spectroscopy, microwave spectroscopy, resonance-enhanced multiphoton ionization, or combinations thereof.

32. The method of claim 30, wherein the data further comprise measurements made using photon probe microscopy, electron probe microscopy, ion probe microscopy, field probe microscopy, or scanning probe microscopy techniques.

33. The method of claim 1, wherein analytical data is provided using techniques relying on collection of electromagnetic radiation in the range from 0.05 Angstroms to 500 millimeters (mm).

34. The method of claim 1, wherein the sample comprises inorganic material, organic material, polymeric material, biological material, or combinations thereof.

35. The method of claim 1, wherein the parameter of interest ranges from a single molecule to up to 100% of the sample.

36. The method of claim 1, wherein the sample comprises polycarbonate.

37. Computer readable media comprising software code for performing the method of claim 1.