Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The Amendment filed 06/20/2025 has been entered. Claims 1-18 remain pending in the application. Claims 1, 5-6, and 18 have been amended.
Status of Objections and Rejections
The objections to the abstract and claims have been withdrawn in view of Applicant's amendment.
The rejection of claim 5 under 35 U.S.C. 112(b) has been withdrawn in view of Applicant's amendment.
The rejection of claims 1-18 under 35 U.S.C. 103 has been withdrawn in view of Applicant's amendment.
The rejection of claims 1-18 under 35 U.S.C. 112(b) is maintained.
All rejections from the previous office action under 35 U.S.C. 101 are maintained.
New grounds of rejection under 35 U.S.C. 101 are necessitated by the amendments.
New grounds of rejection under 35 U.S.C. 112(b) are necessitated by the amendments.
New grounds of rejection under 35 U.S.C. 103 are necessitated by the amendments.
Response to Arguments
Applicant's arguments, see pages 9-17, filed 06/20/2025, with respect to the rejections of claims 1-18, under 35 U.S.C. 101 and 35 U.S.C. 103, have been fully considered but they are not persuasive.
With regard to the rejection of claims 1 and 18 under 35 U.S.C. 112(b), Applicant argues on page 10 that the amendment of claims 1 and 18 to include the word “automated” overcomes the rejection since “input data is implicitly machine-handled,” and therefore the unit upon which the data is deposited cannot be the human mind.
The Examiner respectfully disagrees.
Claim 1 still only recites “providing as input data a Raman spectrum only of a blood serum sample” without specifying what unit or system the data is deposited into. Automation of the claim limitations can still be performed in the mind, although tedious (See 35 U.S.C. 101 responses to arguments below). The omission of a unit leaves ambiguity as to the structural context of the method. Additionally, relying on implication from the specification does not cure indefiniteness (See MPEP 2173.05(e)). As such, Applicant’s argument is not persuasive and the rejection of claims 1-18 under 35 U.S.C. 112(b) remains.
With regard to the rejection under 35 U.S.C. 101, Applicant argues that claims 1 and 18 are not directed to a judicial exception, recite practical steps, and amount to significantly more than the alleged judicial exceptions (Remarks, pages 10-12).
The Examiner respectfully disagrees.
The steps of independent claims 1 and 18:
“performing a deconvolution of at least the second band and the third band of the Raman spectrum, obtaining a respective plurality of Gaussians;
calculating a first sum A2 of the areas of the individual Gaussians related to the second band, and a second sum A3 of the areas of the individual Gaussians related to the third band; calculating a first ratio A2/A1 and a second ratio A3/A1,”
are mathematical operations performed on spectral data. These constitute “mathematical relationships and algorithms,” a recognized category of abstract ideas (2019 PEG, Step 2A Prong 1), and is not a practical application. The claim does not improve Raman instrumentation or computer operation; it applies conventional mathematical tools to natural correlations. Merely reciting the words "apply it" (or an equivalent, such as “automate”) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea does not transform the claim to have a practical application (See MPEP 2106.05(f))(See 112(b) rejection for “automate” as there is not even a recitation of a specific unit for the input). Providing a Raman spectrum and selecting specific spectral bands relevant to known indicators of celiac disease are also not practical applications but insignificant extra-solution activity through mere data gathering and instructions to apply the abstract ideas (See MPEP 2106.05(g)).
Applicant argues that the claims include additional elements that amount to significantly more than the judicial except. However, the Examiner takes official notice that deconvolution and Gaussian analysis are routine or well-understood diagnostic techniques as supported by reference Fornsaro (“Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies”; 2018). Deconvolution and Gaussian analysis, although tedious, can be performed in the mind. A human could visually decompose a spectral band into sub-peaks, sketch Gaussian bell curves on graph paper, estimate their widths, calculate areas geometrically (using Reimann sums or Trapezoidal Rule), and derive ratios using basic arithmetic. The fact that software can automate these steps does not remove them from being mental process and is thus still an abstract idea and does amount to significantly more than the judicial exception. As for the step of verifying that the first ratio and second ratio are above specific threshold values and diagnosing the patient does not add significantly more to the judicial exception. Threshold comparison is a conventional mathematical operation can be performed in the mind, and the act of diagnosing based on the threshold merely applies the natural correlation between biomarker levels and disease state. The recitation of particular threshold values does not transform this abstract idea into an eligible application or significantly more than the judicial exception either (MPEP 2106.05(d)). The Examiner takes official notice that thresholds are well-known in biomarker analysis such as ROC-based cutoffs and Youden index as shown by reference Matthias (US20150110818) in Table 1 and paragraph [0086]. Furthermore, while using serum may be more convenient for patients than a biopsy, convenience of sample collection is not a technological advance in data processing. Reciting a beneficial use of an abstract idea does not transform it into patent-eligible subjection matter (See Mayo (2012); Ariosa (2015))
As such, Applicant’s argument is not persuasive and the rejection of claims 1-18 under 35 U.S.C. 101 remains.
With regard to the rejection under 35 U.S.C. 103, Applicant argues that Fornsaro does not disclose “providing as input data a Raman spectrum only of a blood serum sample,” but instead uses human serum albumin together with other pure components as references that were purchased from Sigma-Aldrich, Germany, and therefore the serum album sample never belongs to a patient of the diagnosis method (Responses, page 13).
The Examiner respectfully disagrees.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., the serum album sample belongs to a patient of the diagnosis method) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Amended claims 1 and 18, step a) only state “providing as input data a Raman spectrum only of a blood serum sample,” and does not specify the origin of the sample to be from a patient. Fornsaro teaches providing a human serum album sample which is naturally derived from human blood and therefore satisfies the limitation of step a). Additionally, Fornsaro discloses obtaining Raman spectra of multiple purified serum constituents such as albumin, IgG, hemoglobin, and lipid species including palmitoleic acid in addition to biopsy spectra. These components are natural constituents of blood serum. One of ordinary skill in the art before the effective filing date of the invention would have understood that analyzing spectra of serum constituents is effectively equivalent to analyzing blood serum itself, since serum is comprised of the mixture of these proteins, lipids, and metabolites in combination (See MPEP 2144.06(II)). As such, Applicant’s argument is not persuasive and the rejection of claims 1-18 under 35 U.S.C. 103 remains.
With regard to the rejection under 35 U.S.C. 103, Applicant argues that Fornsaro emphasizes biopsy tissue, so serum substitution would not be considered (Response, pp. 14-15).
The Examiner respectfully disagrees.
While Fornasaro performs deconvolution on a Raman spectrum of a biopsy sample instead of the serum sample, both biopsy samples and blood serum samples contain the same underlying biochemical markers of celiac disease. Fig. 2 shows pure serum albumin and other pure components present in a blood serum sample as a reference for the biopsy samples (page 357, column 2, Reference Material; Fig. 4). It would have been prima facie obvious before the effective filing date of the invention to have extended Fornasaro’s teachings to serum samples by substituting the blood serum sample for the biopsy sample since they contain the same underlying biochemical markers of celiac disease which would have yielded predictable results using known techniques for disease classification (See MPEP 2143(I)(B)). As such, Applicant’s argument is not persuasive and the rejection of claims 1-18 under 35 U.S.C. 103 remains.
With regard to the rejection under 35 U.S.C. 103, Applicant argues that the teaching of Fornasaro is limited to small-bowel mucosal biopsies and that his technique, useful for research purposes, is difficult to apply to clinical practice due to its complexity.
The Examiner respectfully disagrees.
Complexity of implementation does not negate obviousness (See MPEP 2145(D)). Fornasaro demonstrates that such data processing yields diagnostic discrimination. Whether the analysis is complex or simple depends on available computational tools. Automation of spectra processing was well-known at the time (MCR-ALS, Fornsaro, Title). As such, Applicant’s argument is not persuasive and the rejection of claims 1-18 under 35 U.S.C. 103 remains.
With regard to the rejection under 35 U.S.C. 103, Applicant argues that “Teh never refers to serum sample and to celiac disease. Moreover, Teh carries out a ratio of peak intensities and not a ratio of peak areas,” and therefore does not meet the claimed limitations.
The Examiner respectfully disagrees.
Area under a Raman band is directly proportional to peak intensity when full width at half maximum (FWHM), is constant, and both approaches are interchangeable for quantifying relative spectral contributions. One of ordinary skill in the art would have understood that either intensity or area ratios could be used since they are known equivalents (See MPEP 2144.06(II)).
Although Teh addresses gastric dysplasia rather than celiac disease, Teh nevertheless demonstrates that ratio-based analysis of Raman bands can differentiate diseased from normal tissue. The specific disease state analyzed is not critical; the principle of Raman-based classification using band ratios is transferable across biological contexts. As such, Applicant’s argument is not persuasive and the rejection of claims 1-18 under 35 U.S.C. 103 remains.
In conclusion, Applicant’s amendments and remarks do not overcome the outstanding rejections. Independent claim 1, which recites steps such as “performing a deconvolution…calculating a first ratio A2/A1, and a second ratio A3/A1…and verifying…threshold value,” remains indefinite under 35 U.S.C. 112(b), directed to an abstract idea under 35 U.S.C. 101, and obvious over Fornsaro in view of Teh and Matthias under 35 U.S.C. 103. Applicant’s reliance on unclaimed advantages and narrow readings of the art is unpersuasive. The rejections are therefore maintained.
Drawings
The drawings are objected to because the lack of quality images creates a hindrance to proper examination of the application contents.
Regarding Figs. 1-3, 4a-b, 5a-b, 6a, the spectrum curves and titles and numberings of the horizontal and vertical axes are poor in quality and illegible.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
In addition to Replacement Sheets containing the corrected drawing figure(s), applicant is required to submit a marked-up copy of each Replacement Sheet including annotations indicating the changes made to the previous version. The marked-up copy must be clearly labeled as “Annotated Sheets” and must be presented in the amendment or remarks section that explains the change(s) to the drawings. See 37 CFR 1.121(d)(1). Failure to timely submit the proposed drawing and marked-up copy will result in the abandonment of the application.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claims 1 and 18, these claims recite “automated” and “input”. It is unclear into what unit this input is deposited and by what unit it is automated. For example, it could be the human mind, a processor, or an instrumentation. The specification is also silent to where this input data is deposited. The Examiner interprets this input to be anything capable of receiving data including the human mind.
Claims 2-17 are rejected upon rejected independent claim 1.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-18 are rejected under 35 U.S.C. 101. Although the claims fall within the statutory category of a process, the claimed invention is directed to an abstract idea without practical application and without significantly more. The claims recite
“verifying that the first ratio A2/A1 is greater than a first threshold value and that the second ratio A3/A1 is greater than a second threshold value to confirm that the blood serum sample belongs to a celiac patient” (claims 1 and 18).
calculating a first sum A2 of the areas of the individual Gaussians related to the second band, and a second sum A3 of the areas of the individual Gaussians related to the third band,
calculating a first ratio A2/A1 and a second ratio A3/A1, wherein A1 is the area under the first band of the Raman spectrum
The limitation of verifying that the first ratio A2/A1 is greater than a first threshold value and that the second ratio A3/A1 is greater than a second threshold value to confirm that the blood serum sample belongs to a celiac patient is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, “verifying” to “confirm” in the context of this claim encompasses the user mentally/visually observing the status of one value compared to another to decide/confirm against a natural correlation of an indicator compound (claim 2) and disease categorization. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the checking that the first ratio A2/A1 is greater than a first threshold value and that the second ratio A3/A1 is greater than a second threshold value, then it falls within the “Mental Processes” grouping of abstract ideas by way of observation and evaluation as well as “Mathematical Concepts” (MPEP 2106.04(a)) through the calculating steps. Confirming that the blood serum sample belongs to a celiac patient is performed by correlating the ratio of band areas to a threshold value. For example, Tables 1 “shows the comparison between a healthy subject and a subject affected by celiac disease” while Table 2 shows cut-off values obtained from the analysis of “ROC curves related to the A2/A1 and A3/A1 ratios” (pages 11-12, last paragraph). These ROC curves can always be created manually with the hand or with the assistance of physical aids such as pens or paper by the manipulating of mathematical equations Once the ratios are calculated, and compared to a cut-off value to confirm that the blood serum sample belongs to a celiac patient, no further action is taken. This correlation is the abstract idea (mental step/math). Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites the following additional elements
- providing as input data a Raman spectrum of a blood serum sample.
- selecting from said Raman spectrum a first characteristic band of a first indicator of the presence of celiac disease, a second characteristic band of a second indicator of the presence of celiac disease, and a third characteristic band of a third indicator of the presence of celiac disease
- performing a deconvolution of at least the second band and the third band of the Raman spectrum, obtaining a respective plurality of Gaussians; (claim 1 only)
- cleaning of the second band and third band of the spectrum from any possible observed noise signal is provided (claim 17)
After verifying and confirming that the blood serum sample belongs to a celiac patient, there is no action. Additionally, claim 17 (which is dependent upon claim 1) also recites the step of cleaning of the second band and third band of the spectrum from any possible observed noise signal is provided. Note that these additional elements are drawn to data gathering where the measured property is then used in the abstract idea (correlation). Mere data gathering in a general way is not significantly more than the abstract idea. See MPEP 2106.05(g). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is still directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception as shown in the 103 rejections below. The use of a Raman spectrometer to obtain spectra as an input represents a step that is well-understood and a purely conventional routine technique in the art, as shown by the prior art, Fornasaro (Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies, 2018) with Supporting Materials (PTO-892) and Teh (Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue, 2008). Fornasaro teaches that the use of an InVia Raman microscope which includes a monochromator and spectrometer (Supporting Materials) creates deconvoluted spectra of compounds pertaining to celiac disease using human serum albumin which are correlated to the presence of cells, wherein cells are found in a blood sample. Teh teaches taking a ratio of intensities of these compounds “for tissue classification…between normal and dysplasia tissues” (page 459, column 2, Empirical Approach) and verification by sensitivity and specificity which is the basis of ROC analysis is well-known and used in the prior art to establish a cut-off value (threshold value of the instant claims). These prior art, therefore, show that the natural correlation and mathematical relationships are applied to establish a classification of celiac disease.
The instant claims only require the naturally occurring correlation to be observed by applying the known methods in the art. The instantly rejected claims do not recite any elements in addition to the natural correlation that impose meaningful limits on the claim scope and would substantially foreclose others from using this natural correlation of compounds indicative of celiac disease in ill patients such as temperature or flow rate as it relates to the contamination of a drinking water supply. The intended use of this method does not further limit or apply any significant action once the natural correlation has been observed using the claimed method. The use of human serum albumin (a component of human) blood is tested for compounds in Fornasaro and confirmed in patents through biopsy samples which thereby confirms the use of a blood sample to characterize status of disease in a patient (See claim 1 rejection). Teh further streamlines this process by taking a ratio of intensities of these compounds to create a ROC curve to determine a threshold value with which to compare results (See statistical computing of Fornasaro in Data Analysis section. Sarna also teaches the use of a blood sample for celiac disease testing to replace the need for a gluten-free diet and subsequent duodenum biopsy (page 893, column 2, paragraph 2). The natural correlation is found in nature whether it is observed or not and would be present and act quite independently of any effort of the patentee.
Note that recited specific methods of detection do nothing more to satisfy step 2B (Step 2B: No).
Thus, for reasons fully explained above, claims 1-18 do not satisfy the requirement of 35 U.S.C. 101 and are therefore rejected.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-5, 7-11, 13-18 are rejected under 35 U.S.C. 103 as being unpatentable over Fornasaro (Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies, 2018) and Supporting Materials (PTO-892) in view of Teh (Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue, 2008).
Regarding claim 1, Fornasaro teaches an automated (Use of MCR-ALS and other software; Title; Page 358, column 1, Raman imaging and Data Analysis) diagnosis method for detecting celiac disease comprising the following steps:
a) providing as input data a Raman spectrum (Raman imaging was performed on twelve biopsy samples from twelve patients; page 359, column 1, paragraph 4, lines 1);
b) selecting from said Raman spectrum a first characteristic band of a first indicator of the presence of celiac disease (1002 cm-1, breathing ring of phenylalanine; page 359, column 2, line 2), a second characteristic band of a second indicator of the presence of celiac disease (1444 cm-1, CH2 bending); page 359, column 2, lines 2-3), and a third characteristic band of a third indicator of the presence of celiac disease (1654 cm-1, amide I, a-helix); page 359, column 2, line 3);
d) calculating A2, the area related to the second band (band intensities for CD samples” including “1444 cm-1 (CH2 bending”; page 359, column 2, paragraph 1) and A3, the area related to the third band (“band intensities for CD samples” including “1654 cm-1 (amide I, a-helix)”; page 359, column 2, paragraph 1)
e) calculating A1, the area under the first band of the Raman spectrum (“band intensities for CD samples” including “1002 cm-1 (breathing ring of phenylalanine)”; page 359, column 2, paragraph 1)
f) confirming that the blood serum sample belongs to a celiac patient (page 359 discusses how the specific bands of proteins and lipids listed are “suggesting biomolecular changes associated with CD involving proteins and lipids” whereby these bands are pulled from human serum albumin in which blood encompasses)
Fornasaro fails to teach:
a) providing as input data a Raman spectrum only of a blood serum sample (emphasis added);
c) performing a deconvolution of at least the second band and the third
band of the Raman spectrum, obtaining a respective plurality of Gaussians
d) calculating a first sum A2 of the areas of the individual Gaussians related to the second band, and a second sum A3 of the areas of the individual Gaussians related to the third band (emphasis added)
e) calculating a first ratio A2/A1 and a second ratio A3/A1,
f) verifying that the first ratio A2/A1 is greater than a first threshold value
and that the second ratio A3/A1 is greater than a second threshold value.
Fornasaro does teach the steps for MCR-ALS, a deconvolution method:
“data pre-processing is required to extract the biological information and to remove insignificant variability,” by applying the steps of “removal of cosmic ray artefacts, baseline correction to reduce the impact of tissue autofluorescence, and subsequent smoothing interpolation to project the spectra on an evenly spaced wavenumber axis” This is followed by “intensity vector normalization” to remove outliers by the PCA analysis; page 358, columns 1-2; Input data pre-processing) . Since “more than 100 random spectra for each dataset” were used (page 358, columns1-2) and this “raw spectra” were subjected to pre-processing (page 358-359; Input data pre-processing) this would include the second and third bands.
While Fornasaro doesn't specifically speak of performing a deconvolution by calculating a sum of the areas of the individual Gaussians related to the second and third bands, Fornsaro does use MCR-ALS which is a type of deconvolution technique that produces relative concentration maps for the second and third bands (page 359, column 2, paragraph 2; See Figs. 2-3). It would have been prima facie obvious before the effective filing date of the invention to have substituted the MCR-ALS for Gaussian summation, a technique that is well-known in the art and would have yielded predictable results since the two processes serve the same purpose (See MPEP 2143(I)(B).
While Fornasaro performs deconvolution on a Raman spectrum of a biopsy sample, both biopsy samples and blood serum samples contain the same underlying biochemical markers of celiac disease. Fig. 2 shows pure serum albumin and other pure components present in a blood serum sample as a reference for the biopsy samples. The sum of these pure components is an obvious variant of an actual blood serum sample since they would contain the same naturally occurring components that are the biomarkers for celiac disease identified in Fornsaro; therefore a single blood serum sample can be substituted for the mixture of pure compounds used as reference materials (page 357, column 2, Reference Material; Fig. 4)(See MPEP 2144.06(II)). It would have been prima facie obvious before the effective filing date of the invention to have substituted a blood serum sample for a biopsy sample since they contain the same underlying biochemical markers of celiac disease which would have yielded predictable results using known techniques for disease classification (See MPEP 2143(I)(B)).
Modified Fornasaro fails to teach:
e) calculating a first ratio A2/A1 and a second ratio A3/A1,
f) verifying that the first ratio A2/A1 is greater than a first threshold value
and that the second ratio A3/A1 is greater than a second threshold value.
Modified Fornasaro does teach that the bands of A1, A2, and A3 (1002 cm-1 (breathing ring of phenylalanine), 1444 cm-1 (CH2 bending), and 1654 cm-1 (amide I, a-helix), respectively) “are correlated to the presence of cells in the studied area… suggesting biomolecular changes associated with CD involving proteins and lipids,” (page 359, column 2, paragraph 1)
Teh teaches:
e) calculating a first ratio and a second ratio (diagnostic algorithm derived from the intensity ratio of I875/I1450)(For differentiation of normal and precancerous tissues, other different intensity bands and ratios such as I1656, I1656/I1325, I1330/I1454 vs I1454/I1656, and I1336/I1250 had also been reported to be of effective diagnostic algorithms for tissue diagnosis and characterization; page 464, column 1, paragraph 2, lines 14-18),
f) verifying that the first ratio is greater than a first threshold value and that the second ratio is greater than a second threshold value (The decision line (I875/I1450 =0.717) separates dysplasia tissue from normal tissue; Fig. 5)(Since difference ratios are also effective, other decisions line would be created from these ratios).
Teh is considered to be analogous to the claimed invention because it is in the same field of endeavor for using Raman spectroscopy and compound analysis for diagnosing diseased transformation of cells. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Fornasaro in view of Fornasaro to incorporate the teachings of Teh by further calculating ratios of the band areas and comparing them to a threshold value. Applying this technique is advantageous “to develop simple but effective algorithms for identifying abnormal tissue from normal tissue” (Teh, page 464, paragraph 2). Fig. 4A of Teh shows the compounds of interest phenylalanine, phospholipids, and amide I bands (page 460, paragraph 3) which are compound bands of interest also taught by Fornasaro (page 359, column 2). Using the technique of Teh to compare different ratio intensities of these three bands which are indicative of cell changes associated with celiac’s disease is routine experimentation to determine the optimal ratio that satisfies the prediction of the disease. Teh notes that the two compounds with the most significant difference pulled from the difference spectrum between normal and dysplasia tissue yields the best intensity ratio for predicting biological markers of the disease (page 464, paragraph 2, lines 23-35). Fornasaro shows a difference spectrum (Fig. 1, bottom) where the highest difference is 1002 cm-1 which is associated with the first band (phenylalanine) and the second and third bands at 1464cm-1 and 1654 cm-1, respectively, are both lower than the first band. Using this same logic taught by Teh to yield an intensity ratio I875/I1450, Fornasaro would yield intensity ratios of I1464/I1002 and I1654/I1002 meeting the limitation of A2/A1 and A3/A1 since intensity ratios and area ratios are mathematically and functionally equivalents that would yield predictable results (See MPEP 2144.06(II)). From here, a decision line would be generated for each ratio in order to discriminate dysplasia tissue from normal tissue (page 461, column 2, paragraph 2) in order to confirm that the blood serum sample belongs to a celiac patient. Raman spectra has been widely applied in a number of organ sites to evaluate variations in the tissue spectra,” (Teh, page ,) it would have been obvious to apply this same method to evaluate human serum albumin as taught by Fornasaro.
Regarding claim 2, Fornasaro in view of Teh teaches the method according to claim 1, wherein said first indicator is given by phenylalanine (1002 cm-1 (breathing ring of phenylalanine; Fornasaro page 359, column 2, line 2); wherein said second indicator is given by phospholipids (1444 cm-1 (CH2 bending), wherein this shift is included in the range of phospholipid vibration modes between 1500 cm-1 and 1400 cm-1 as described in the instant specification page 10 lines 15-16; Fornasaro, page 359, column 2, lines 2-3) and wherein said third indicator is given by amide-I (1654 cm-1 (amide I, a-helix); Fornasaro, page 359, column 2, line 3).
Regarding claim 3, Fornasaro in view of Teh teaches the method according to claim 1, wherein said first indicator is given by the breathing vibration mode of the phenylalanine aromatic ring (1002 cm1 (breathing ring of phenylalanine, wherein this shift is included in the range of amide-I vibration modes between 1015 cm-1 and 990 cm-1 as described in the instant specification page 10 lines 17-18; Fornasaro, page 359; page 359, column 2, line 2); wherein said second indicator is given by the phospholipid vibration modes (1444 cm-1 (CH2 bending), wherein this shift is included in the range of phospholipid vibration modes between 1500 cm-1 and 1400 cm-1 as described in the instant specification page 10 lines 15-16; Fornasaro, page 359, column 2, lines 2-3); and wherein said third indicator is given by the amide-I vibration modes (1654 cm-1 (amide I, a-helix), wherein this shift is included in the range of amide-I vibration modes between 1750 cm-1 and 1550 cm-1 as described in the instant specification page 10 lines 17-18; Fornasaro, page 359, column 2, line 3).
Regarding claim 4, Fornasaro in view of Teh teaches the method according to claim 1, wherein the first band is comprised in a first sub-range of wavenumbers (1002 cm1 (breathing ring of phenylalanine, wherein this shift is included in the range of amide-I vibration modes between 1015 cm-1 and 990 cm-1 as described in the instant specification page 10 lines 17-18; page 359; page 359, column 2, line 2), the second band is comprised in a second sub-range of wavenumbers (1444 cm-1 (CH2 bending), wherein this shift is included in the range of phospholipid vibration modes between 1500 cm-1 and 1400 cm-1 as described in the instant specification page 10 lines 15-16; Fornasaro, page 359, column 2, lines 2-3), and the third band is comprised in a third sub- range of wavenumbers (1654 cm-1 (amide I, a-helix), wherein this shift is included in the range of amide-I vibration modes between 1750 cm-1 and 1550 cm-1 as described in the instant specification page 10 lines 17-18; page 359, column 2, line 3).
Regarding claim 5, Fornasaro in view of Teh teaches the method according to claim 4, wherein said first sub-range of wavenumbers is between 1015 cm-1 and 990 cm-1,(1002 cm1 (breathing ring of phenylalanine; Fornasaro, page 359, column 2, line 2) said second sub-range of wavenumbers is between 1500 cm-1 and 1400 cm-1,(1444 cm-1 (CH2 bending); Fornasaro, page 359, column 2, lines 2-3) and said third sub-range of wavenumbers is between 1750 cm-1 and 1550 cm-1.(1654 cm-1 (amide I, a-helix); Fornasaro, page 359, column 2, line 3)( the examiner interprets the indefinite term of “about” to include any value from 0 cm-1 to infinity; See 112b rejection above).
Regarding claim 7, Fornasaro in view of Teh teaches the method according to claim 1,
Fornasaro in view of Teh fails to teach said second threshold value is greater than said first threshold value. This limitation can be met through routine experimentation based on the results of the spectral intensities of the compounds of interest. This is a result-effective variable based upon which compounds are chosen and the content of the samples analyzed. MPEP 2144.05.
Regarding claim 8, Fornasaro in view of Teh teaches the method according to claim 1, wherein the Raman spectrum is acquired in a range of wavenumbers between 3500 cm-1 and 300 cm (The spectrograph was set to provide a spectral range of 500–1800 cm-1; page 358; lines 21-22).
Regarding claim 9, Fornasaro in view of Teh teaches the method according to claim 1, wherein, in order to obtain the Raman spectrum of the blood serum sample a Raman spectrometer is used (“InVia Raman microscope,” wherein by design an InVia Raman microscope includes a “spectrometer”; Fornasaro, page 358, column 1; See supporting document as cited on the PTO-892).
Regarding claim 10, Fornasaro in view of Teh teaches the method according to claim 9, wherein a detector is connected to said Raman spectrometer (Fornasaro, charge coupled device (CCD); page 358, column 1, line 5).
Regarding claim 11, Fornasaro in view of Teh teaches the method according to claim 9,
Fornasaro in view of Teh teaches fails to teach the Raman spectrum is acquired by performing a number of scans of the serum sample between 25 and 35, with an exposure time between 30 and 90 seconds for each scan. However, Fornasaro in view of Teh does teach performing Raman imaging through use of a ProScan II motorized stage (page 358, column 1, Raman imaging). The number of scans and the exposure time are variables that would vary depending which combination yields optimal scans of the best quality, for example improvement of the signal to noise ratio or other interferences. MPEP 2144.05.
Regarding claim 13, Fornasaro in view of Teh teaches the method according to claim 8, wherein the Raman spectrum is acquired in a range of wavenumbers between 3300 cm-1 and 400 cm-1 (The spectrograph was set to provide a spectral range of 500–1800 cm-1; page 358; lines 21-22; Fornasaro, page 358, column 1, Raman imaging).
Regarding claim 14, Fornasaro in view of Teh teaches the method according to claim 13, wherein the Raman spectrum is acquired in a range of wavenumbers between 2500 cm-1 and 500 cm-1 (The spectrograph was set to provide a spectral range of 500–1800 cm-1; Fornasaro, page 358; column 1).
Regarding claim 15, Fornasaro in view of Teh teaches the method according to claim 10, wherein said detector is a charge-coupled device (CCD) (charge coupled device (CCD); Fornasaro, page 358, column 1, line 5).
Regarding claim 16, Fornasaro in view of Teh teaches the method according to claim 15, wherein said detector is integrated with a monochromator (the InVia Raman microscope structurally incorporates a “monochromator”; Fornasaro, page 358, column 1; See supporting document as cited on the PTO-892).
Regarding claim 17, Fornasaro in view of Teh teaches the method according to claim 1, wherein between step c) and d) a cleaning of the second band and third band of the spectrum from any possible observed noise signal is provided (through data pre-processing “presence of significant background signals (e.g. autofluorescence, noise),” is implemented “to remove insignificant variability,” wherein the step is applied to “raw spectra” which would include the second and third band; Fornasaro, a page 358, column 1, Input data pre-processing).
Regarding claim 18, Fornasaro teaches an automated (Use of MCR-ALS and other software; Title; Page 358, column 1, Raman imaging and Data Analysis) diagnosis method for detecting celiac disease comprising the following steps:
a) providing as input data a Raman spectrum (spectral data acquisition of Raman maps; page 358, column 1, Input data pre-processing) of a blood serum sample (“human serum albumin,” which originates within blood; page 357, Reference Material; Fig. 4);
b) selecting from said Raman spectrum a first characteristic band of a first indicator of the presence of celiac disease (1002 cm-1, breathing ring of phenylalanine; page 359, column 2, line 2), a second characteristic band of a second indicator of the presence of celiac disease (1444 cm-1, CH2 bending); page 359, column 2, lines 2-3), and a third characteristic band of a third indicator of the presence of celiac disease (1654 cm-1, amide I, a-helix); page 359, column 2, line 3);
c) calculating A2, the area related to the second band (band intensities for CD samples” including “1444 cm-1 (CH2 bending”; page 359, column 2, paragraph 1) and A3, the area related to the third band (“band intensities for CD samples” including “1654 cm-1 (amide I, a-helix)”; page 359, column 2, paragraph 1) and calculating A1, the area under the first band of the Raman spectrum (“band intensities for CD samples” including “1002 cm-1 (breathing ring of phenylalanine)”; page 359, column 2, paragraph 1)calculating a first ratio A2/A1 and a second ratio A3/A1, wherein A1 is the area under the first band, A2 is the area under the second band, and A3 is the area under the third band;
Fornasaro fails to teach:
a) providing as input data a Raman spectrum of only a blood serum sample ;
c) calculating a first ratio A2/A1 and a second ratio A3/A1,
d) verifying that the first ratio A2/A1 is greater than a first threshold value and that the second ratio A3/A1 is greater than a second threshold value to confirm that the blood serum sample belongs to a celiac patient.
Fornasaro does teach that the bands of A1, A2, and A3 (1002 cm-1 (breathing ring of phenylalanine), 1444 cm-1 (CH2 bending), and 1654 cm-1 (amide I, a-helix), respectively) “are correlated to the presence of cells in the studied area… suggesting biomolecular changes associated with CD involving proteins and lipids,” (page 359, column 2, paragraph 1)
While Fornasaro provides a Raman spectrum of a biopsy sample, both biopsy samples and blood serum samples contain the same underlying biochemical markers of celiac disease. Fig. 2 shows pure serum albumin and other pure components present in a blood serum sample as a reference for the biopsy samples. The sum of these pure components is an obvious variant of an actual blood serum sample since they would contain the same naturally occurring components that are the biomarkers for celiac disease identified in Fornsaro; therefore a single blood serum sample can be substituted for the mixture of pure compounds used as reference materials (page 357, column 2, Reference Material; Fig. 4)(See MPEP 2144.06(II)). It would have been prima facie obvious before the effective filing date of the invention to have substituted a blood serum sample for a biopsy sample since they contain the same underlying biochemical markers of celiac disease which would have yielded predictable results using known techniques for disease classification (See MPEP 2143(I)(B)).
Teh teaches:
e) calculating a first ratio and a second ratio (diagnostic algorithm derived from the intensity ratio of I875/I1450)(For differentiation of normal and precancerous tissues, other different intensity bands and ratios such as I1656, I1656/I1325, I1330/I1454 vs I1454/I1656, and I1336/I1250 had also been reported to be of effective diagnostic algorithms for tissue diagnosis and characterization; page 464, column 1, paragraph 2, lines 14-18),
f) verifying that the first ratio is greater than a first threshold value and that the second ratio is greater than a second threshold value (The decision line (I875/I1450 =0.717) separates dysplasia tissue from normal tissue; Fig. 5)(Since difference ratios are also effective, other decisions line would be created from these ratios)
Teh is considered to be analogous to the claimed invention because it is in the same field of endeavor for using Raman spectroscopy and compound analysis for diagnosing diseased transformation of cells. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Fornasaro in view of Fornasaro to incorporate the teachings of Teh by further calculating ratios of the band areas and comparing them to a threshold value. Applying this technique is advantageous “to develop simple but effective algorithms for identifying abnormal tissue from normal tissue” (Teh, page 464, paragraph 2). Fig. 4A of Teh shows the compounds of interest phenylalanine, phospholipids, and amide I bands (page 460, paragraph 3) which are compound bands of interest also taught by Fornasaro (page 359, column 2). Using the technique of Teh to compare different ratio intensities of these three bands which are indicative of cell changes associated with celiac’s disease is routine experimentation to determine the optimal ratio that satisfies the prediction of the disease. Teh notes that the two compounds with the most significant difference pulled from the difference spectrum between normal and dysplasia tissue yields the best intensity ratio for predicting biological markers of the disease (page 464, paragraph 2, lines 23-35). Fornasaro shows a difference spectrum (Fig. 1, bottom) where the highest difference is 1002 cm-1 which is associated with the first band (phenylalanine) and the second and third bands at 1464cm-1 and 1654 cm-1, respectively, are both lower than the first band. Using this same logic taught by Teh to yield an intensity ratio I875/I1450, Fornasaro would yield intensity ratios of I1464/I1002 and I1654/I1002 meeting the limitation of A2/A1 and A3/A1 since intensity ratios and area ratios are mathematically and functionally equivalents that would yield predictable results (See MPEP 2144.06(II)). From here, a decision line would be generated for each ratio in order to discriminate dysplasia tissue from normal tissue (page 461, column 2, paragraph 2) in order to confirm that the blood serum sample belongs to a celiac patient. Raman spectra has been widely applied in a number of organ sites to evaluate variations in the tissue spectra,” (Teh, page ,) it would have been obvious to apply this same method to evaluate human serum albumin as taught by Fornasaro.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Fornasaro (Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies, 2018) and Supporting Materials (PTO-892) in view of Teh (Diagnostic potential of near-infrared Raman spectroscopy in the stomach: differentiating dysplasia from normal tissue, 2008) and in further view of Matthias (US 20150110818 A1)
Regarding claim 6, Fornasaro in view of Teh teaches the method according to claim 1, wherein said first threshold value and said second threshold value can be defined by performing the following steps:
- providing a Raman spectrum of a sample (twelve biopsy samples from
twelve patients; page 359, Samples studied; Fornasaro, Fig. 4) for each patient of a first known group of celiac patients (CD samples group (red, n = 21 315),” wherein CD means celiac disease); Fornasaro, Fig. 1) and for each patient of a second known group of non-celiac patients (“HC samples group (black, n = 20 172),” wherein HC means healthy control; Fornasaro, Fig. 1;
for each patient, both of the first group and of the second group, selecting from the respective Raman spectrum the first band characteristic of the first indicator (1002 cm-1, breathing ring of phenylalanine; Fornasaro, page 359, column 2, line 2), a second characteristic band of a second indicator of the presence of celiac disease (1444 cm-1, CH2 bending); Fornasaro, page 359, column 2, lines 2-3), and a third characteristic band of a third indicator of the presence of celiac disease (1654 cm-1, amide I, a-helix); Fornasaro, page 359, column 2, line 3);
calculating the first ratio A2/A1 and the second ratio A3/A1, wherein A1 is the area under the first band of the Raman spectrum; and calculating the first ratio A2/A1 and the second ratio A3/A1, wherein A1 is the area under the first band of the Raman spectrum (For differentiation of normal and precancerous tissues, other different intensity bands and ratios such as I1656, I1656/I1325, I1330/I1454 vs I1454/I1656, and I1336/I1250 had also been reported to be of effective diagnostic algorithms for tissue diagnosis and characterization; Teh, page 464, column 1, paragraph 2, lines 14-18)(See motivation in claim 1 for combining arts to yield ratios in terms of A2/A1 and A3/A1)
- a database of the first ratios A2/A1 a database of the second ratios A3/A1 (the ratio becomes a ment