DETAILED ACTION
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Objections
Claims 5, 12, and 13 objected to because of the following informalities:
Claim 5 recites the limitation "an MS/MS spectral summary obtained in step B.1" in lines 6-7 of the claim. Claim 5 also recites “a mass spectrometry (MS)/MS spectral summary” in line 5 of the claim. The “an MS/MS spectral summary obtained in step B.1” should read as “the MS/MS spectral summary obtained in step B.1”.
Claim 12 recites the limitation "an MS/MS spectral summary obtained in step B.1" in lines 6-7 of the claim. Claim 12 also recites “a mass spectrometry (MS)/MS spectral summary” in line 5 of the claim. The “an MS/MS spectral summary obtained in step B.1” should read as “the MS/MS spectral summary obtained in step B.1”.
Claim 13 recites the limitation "an MS/MS spectral summary obtained in step B.1" in lines 6-7 of the claim. Claim 13 also recites “a mass spectrometry (MS)/MS spectral summary” in line 5 of the claim. The “an MS/MS spectral summary obtained in step B.1” should read as “the MS/MS spectral summary obtained in step B.1”.
Appropriate correction is required.
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 1-20 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.
Claim 1 recites the limitation "the mass spectrometry data obtained in step 1" in line 6 of the claim. There is insufficient antecedent basis for this limitation in the claim. It is unclear if “the mass spectrometry data obtained in step 1” is referring to “non-target data” or “a peak list”. For examination purposes, “the mass spectrometry data obtained in step 1” will be interpreted as “mass spectrometry data obtained in step 1”.
Claims 2-20 depend on claim 1, therefore claims 2-20 inherit the same issues as claim 1 and are rejected for the same reasons.
Claim 2 recites the limitation "the predicted transformation products obtained in step A.2" in line 8 of the claim. There is insufficient antecedent basis for this limitation in the claim. For examination purposes “the predicted transformation products obtained in step A.2” will be interpreted as “predicted transformation products obtained in step A.2”.
Claims 3-4 and 11-20 depend on claim 2, therefore claims 3-4 and 11-20 inherit the same issues as claim 2 and are rejected for the same reasons.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an abstract idea as discussed below. This judicial exception is not integrated into a practical application for the reasons discussed below. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for reasons discussed below.
Step 1 of the 2019 Guidance requires the examiner to determine if the claims are to one of the statutory categories of invention. Applied to the present application, the claims belong to the statutory class of a process.
Step 2A of the 2019 Guidance is divided into two Prongs. Prong 1 requires the examiner to determine if the claims recite an abstract idea, and further requires that the abstract idea belong to one of three enumerated groupings: mathematical concepts, mental processes, and certain methods of organizing human activity.
Claim 1 is copied below, with limitations belonging to an abstract idea being underlined.
A method for identifying transformation products of antibiotics from known and potential unknown transformation pathways, comprising:
step 1: collecting samples from different sampling sites in a target area, extracting antibiotics and transformation products thereof, and collecting non-target data by ultra-high performance liquid chromatography-high resolution mass spectrometry to obtain a peak list;
step 2: based on the mass spectrometry data obtained in step 1, performing step A of identifying transformation products of the antibiotics from known transformation pathways and performing step B of identifying transformation products of the antibiotics from unknown transformation pathways;
wherein step A comprises: collecting structural information of known antibiotics, establishing an information list of parent antibiotics, and establishing a suspect list of transformation products; and step B comprises: establishing a molecular network, extracting all features of a sub-network where a parent is located, and obtaining the transformation products from the unknown transformation pathways;
step 3: obtaining a list of candidate transformation products based on the transformation products from the known and unknown transformation pathways obtained in step 2, and annotating structures of the transformation products;
step 4: extracting feature fragments based on structure annotations of the transformation products obtained in step 3, and searching for spectra with the feature fragments, and supplementing the transformation products from the unknown transformation pathways; and
step 5: obtaining a final list of identified products after annotating the structures of transformation products.
The limitations underlined can be considered to describe a mental process, namely a process of identifying the transformation products of antibiotics. This is accomplished by examining and analyzing data taken from mass spectrometry.
Step 2A Prong 2 of the 2019 Guidance requires the examiner to determine whether the claim integrates the judicial exception into a practical application.
The additional limitations of “transformation products of antibiotics from known and potential unknown transformation pathways” and “ultra-high performance liquid chromatography-high resolution mass spectrometry” only limit the abstract idea to a field of use (see MPEP 2106.05(h)).
The additional limitations of “step 1: collecting samples”, “collecting non-target data”, and “collecting structural information” are insignificant extra-solution activity, i.e. data gathering (see MPEP 2106.05(g)).
The claim does not integrate the abstract idea into a practical application. Various considerations are used to determine whether the additional elements are sufficient to integrate the abstract idea into a practical application. The claim does not recite a particular machine applying or being used by the abstract idea. The claim does not effect a real-world transformation or reduction of any particular article to a different state or thing. The claim does not contain additional elements which describe the functioning of a computer, or which describe a particular technology or technical field, being improved by the use of the abstract idea.
Step 2B of the 2019 Guidance requires the examiner to determine whether the additional elements cause the claim to amount to significantly more than the abstract idea itself. The considerations for this particular claim are essentially the same as the considerations for Prong 2 of Step 2A, and the same analysis leads to the conclusion that the claim does not amount to significantly more than the abstract idea.
Therefore, Claim 1 is rejected as ineligible under 35 USC 101.
Dependent Claims 2-20 are similarly ineligible. Dependent Claim 2 adds the recited “establishing the information list”, “obtaining the suspect list”, and “merging the predicted transformation products” to the abstract idea limitations discussed above. Dependent Claim 2 additionally recites “collecting structural information” which is mere data gathering. Dependent Claim 3 additionally recites “the suspect list… comprises known transformation products and predicted transformation products” which only limits the abstract idea to a field of use. Dependent Claim 4 adds the recited “removing a transformation product having a similarity of less than a set value” to the abstract idea limitations. Dependent Claim 5 adds the recited “preprocessing the mass spectrometry data”, “establishing the molecular network”, and “extracting mass spectrum peak information” to the abstract idea limitations. Dependent Claim 5 additionally recites “a feature quantification table and a mass spectrometry (MS)/MS spectral summary” which only limits the abstract idea to a field of use. Dependent Claim 6 adds the recited “creating the molecular network” and “setting a minimum matched fragment ion and a cosine score” to the abstract idea limitations. Dependent Claim 6 additionally recites “exporting … to Global Natural Products Social Molecular Networking platform” which only limits the abstract idea to a field of use. Dependent Claim 7 adds the recited “locating”, “extracting”, and “obtaining” to the abstract idea limitations. Dependent Claim 8 adds the recited “annotating” and “assigning” to the abstract idea limitations. Dependent Claim 9 adds the recited “using”, “searching”, and “supplementing” to the abstract idea limitations. Dependent Claim 10 adds the recited “selecting” to the abstract idea limitations. Dependent Claims 11-20 are analogous to claims 2-10. None of these dependent claims recite any further additional elements which would cause the claim as a whole to integrate the recited abstract idea into a particular practical application at Step 2A Prong 2, or provide significantly more than the recited abstract idea at Step 2B. Claims 2-20 are therefore rejected as ineligible under 35 USC 101 as well.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-9 and 11-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hu ("Integration of target, suspect, and nontarget screening with risk modeling for per- and polyfluoroalkyl substances prioritization in surface waters", Water Research, Volume 233, 2023) in view of Majewsky (" Systematic suspect screening and identification of sulfonamide antibiotic transformation products in the aquatic environment", Analytical and Bioanalytical Chemistry, Volume 407, 2015) and further in view of Geng (CN 111707741).
Regarding Claim 1, Hu teaches a method for identifying
step 1: collecting samples from different sampling sites in a target area (Section 2.1: “We collected surface water samples (n = 90) in 2-L pre-rinsed polypropylene bottles in September 2020 (Autumn) and April 2021 (Spring) from 45 routine monitoring stations of the Chaobai River, Beijing”),
extracting
collecting non-target data by ultra-high performance liquid chromatography-high resolution mass spectrometry to obtain a peak list (Section 2.1: “the extracted samples were analyzed by an ultrahigh performance liquid chromatography interfaced to a hybrid quadrupole Orbitrap” and Section 2.2: “we performed data preprocessing of Orbitrap raw data, including peak picking, retention time alignment, grouping of peaks across files, and background subtraction, which generated a peak list”);
step 2: based on the mass spectrometry data obtained in step 1, performing step A of identifying
performing step B of identifying transformation products of the antibiotics from unknown transformation pathways (Section 2.3: “We developed a random forest regression model to quantify the 13 nontarget PFAS without authentic standards through the prediction of response factors”);
wherein step A comprises: collecting structural information of known antibiotics, establishing an information list of
step 3: obtaining a list of candidate transformation products based on the transformation products from the known and unknown transformation pathways obtained in step 2 (Section 2.2: “After removing duplicates and checking peak shape, the peaks with positive hits from suspect screening and the filtered peaks from nontarget screening were labeled as PFAS candidates”), and
annotating structures of the transformation products (Section 2.2: “To identify PFAS candidates’ structures, the predicted molecular formula was determined with the criteria of 1) maximum element counts: C50H50F50O12S4N4P4, 2) ring double bond equivalents (RDBE): 0−5, 3) isotopic fit threshold > 80%, and 4) mass tolerance < 5 ppm, using the function of “Predict Compositions” in Compound Discover 3.2”);
step 4: extracting feature fragments based on structure annotations of the transformation products obtained in step 3, and searching for spectra with the feature fragments, and supplementing the transformation products from the unknown transformation pathways (Section 2.2: “When having PFAS candidates without MS/MS spectra, we reinjected the samples into Orbitrap after adding m/z of these PFAS to the inclusion list”); and
step 5: obtaining a final list of identified products after annotating the structures of transformation products (Section 3.2: “Combining target, suspect, and nontarget screening, we identified 33 PFAS in river water samples”).
Hu does not explicitly teach transformation products of antibiotics and step B comprises: establishing a molecular network, extracting all features of a sub-network where a parent is located, and obtaining the transformation products from the unknown transformation pathways.
Majewsky teaches identifying transformation products of antibiotics (Abstract: “Therefore, in the present study, a generic scheme was developed to predict 29 potential TPs of sulfonamide antibiotics via identification of the major transformation and breakdown reactions”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu with the method of Majewsky by substituting the PFAs of Hu with the antibiotics of Majewsky. Doing so would allow for accurate identification of the transformation products of antibiotics in water systems.
Geng teaches step B comprises: establishing a molecular network (Para 17: “the preprocessed data is imported into the GNPS molecular network processing platform”),
extracting all features of a sub-network where a parent is located (Para 19: “Based on the m/z values of the parent ion displayed at the nodes in the molecular network, identify the m/z regions of the target compound and known transformation products. The m/z peaks connected to these regions with thicker lines (high similarity in secondary spectra) are considered to be the mass spectrum peaks of the transformation products of the target compound”),
and obtaining the transformation products from the unknown transformation pathways (Para 19: “Based on the m/z difference between the mass spectrum peak of the product and the mass spectrum peaks of adjacent parent compounds or adjacent known structures, deduce the structural formula of the product”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky with the method of Geng by substituting the random forest regression model of Hu with the molecular network method of Geng. Doing so would improve accuracy in identifying transformation products from unknown transformation pathways.
Regarding Claim 2, Hu in view of Majewsky and Geng teach the limitations of claim 1, and Hu further teaches wherein step A comprises:
step A.1: collecting the structural information of the known antibiotics and establishing the information list of parent antibiotics (Section 2.2: “selection of PFAS candidates, and structure identification”);
step A.2: for a parent antibiotic obtained in step A.1, obtaining the suspect list of all transformation products (Section 2.2: “For suspect screening, firstly, we compiled a suspect list comprised of 7676 MS-ready PFAS with exact neutral mass and structure, by combining 9252 PFAS in the PFAS Master List of PFAS Substances (accessed May 13th 2021) from the United States Environmental Protection Agency (US EPA) CompTox Chemistry Dashboard and 1030 PFAS from NORMAN Suspect List Exchange with the removal of duplicates, metal ions, salts, isotopes, and mixtures”); and
step A.3: merging the predicted transformation products obtained in step A.2 (Section 2.2: “matching the peak list with this suspect list”).
Regarding Claim 3, Hu in view of Majewsky and Geng teach the limitations of claim 2, and Hu further teaches wherein: in step A.2, the suspect list of the transformation products established according to the known transformation pathways comprises known transformation products and predicted transformation products from the known transformation pathways (Section 2.2: “For suspect screening, firstly, we compiled a suspect list comprised of 7676 MS-ready PFAS with exact neutral mass and structure, by combining 9252 PFAS in the PFAS Master List of PFAS Substances (accessed May 13th 2021) from the United States Environmental Protection Agency (US EPA) CompTox Chemistry Dashboard and 1030 PFAS from NORMAN Suspect List Exchange with the removal of duplicates, metal ions, salts, isotopes, and mixtures”).
Regarding Claim 4, Hu in view of Majewsky and Geng teach the limitations of claim 2, and Hu further teaches wherein: step A.3 comprises: removing a transformation product having a similarity of less than a set value and having the same molecular descriptor with a parent structure for merging the prediction results of the transformation products obtained in step A.2 (Section 2.2: “Through the function of “Search Mass Lists” in Compound Discover 3.2, we identified the positive hits by matching the peak list with this suspect list using the criteria of mass tolerance < 5 ppm” and “After removing duplicates”).
Regarding Claim 5, Hu in view of Majewsky and Geng teach the limitations of claim 1, but Hu and Majewsky do not explicitly teach wherein: step B specifically comprises:
step B.1: preprocessing the mass spectrometry data obtained in step 1 to obtain a feature quantification table and a mass spectrometry (MS)/MS spectral summary;
step B.2: establishing the molecular network with the feature quantification table and an MS/MS spectral summary obtained in step B.1; and
step B.3: extracting mass spectrum peak information of transformation products of the parent antibiotic from the unknown transformation pathways using the molecular network obtained in step B.2.
Geng teaches wherein: step B specifically comprises:
step B.1: preprocessing the mass spectrometry data obtained in step 1 to obtain a feature quantification table and a mass spectrometry (MS)/MS spectral summary (Para 15: “The preprocessing mainly includes: chromatographic peak extraction, chromatographic peak deconvolution, isotope peak classification, mass spectrometry characteristic peak classification, and isotope filtering”);
step B.2: establishing the molecular network with the feature quantification table and an MS/MS spectral summary obtained in step B.1 (Para 17: “After processing, the preprocessed data is imported into the GNPS molecular network processing platform”); and
step B.3: extracting mass spectrum peak information of transformation products of the parent antibiotic from the unknown transformation pathways using the molecular network obtained in step B.2 (Para 19: “Based on the m/z values of the parent ion displayed at the nodes in the molecular network, identify the m/z regions of the target compound and known transformation products” and “Based on the m/z difference between the mass spectrum peak of the product and the mass spectrum peaks of adjacent parent compounds or adjacent known structures, deduce the structural formula of the product”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is established and used into the invention. Doing so would ensure the molecular network method would accurately identify transformation products from unknown transformation pathways.
Regarding Claim 6, Hu in view of Majewsky and Geng teach the limitations of claim 5, but Hu and Majewsky do not explicitly teach wherein: step B.2 comprises: exporting the feature quantification table and the MS/MS spectral summary obtained in step B.1 to Global Natural Products Social Molecular Networking platform, creating the molecular network using a feature-based molecular networking workflow, and setting a minimum matched fragment ion and a cosine score.
Geng teaches wherein: step B.2 comprises: exporting the feature quantification table and the MS/MS spectral summary obtained in step B.1 to Global Natural Products Social Molecular Networking platform (Para 19: “After processing, the preprocessed data is imported into the GNPS molecular network processing platform for secondary spectrum clustering and calculation”),
creating the molecular network using a feature-based molecular networking workflow (Para 19: “The resulting data is then imported into Cytoscape 2.8.3 software for molecular network visualization, yielding a visualized network diagram of the target compound's transformation products”),
and setting a minimum matched fragment ion and a cosine score (Para 23: “the cosine similarity is selected as 0.6, and the minimum number of matching peaks is set as 4”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is established into the invention. Doing so would ensure the molecular network method would be able to accurately identify transformation products from unknown transformation pathways.
Regarding Claim 7, Hu in view of Majewsky and Geng teach the limitations of claim 6, but Hu and Majewsky do not explicitly teach wherein: step B.3 comprises: in a graph of the molecular network established in step B.2, locating an area where the parent antibiotic and the known transformation products are present based on a mass-to-charge ratio of a precursor ion shown on a node in the molecular network, thereby extracting all the features of the sub-network, and obtaining mass spectra of the transformation products of the parent antibiotic from the unknown transformation pathways.
Geng teaches wherein: step B.3 comprises: in a graph of the molecular network established in step B.2, locating an area where the parent antibiotic and the known transformation products are present based on a mass-to-charge ratio of a precursor ion shown on a node in the molecular network (Para 19: “Based on the m/z values of the parent ion displayed at the nodes in the molecular network, identify the m/z regions of the target compound and known transformation products”),
thereby extracting all the features of the sub-network, and obtaining mass spectra of the transformation products of the parent antibiotic from the unknown transformation pathways (Para 19: “Based on the m/z difference between the mass spectrum peak of the product and the mass spectrum peaks of adjacent parent compounds or adjacent known structures, deduce the structural formula of the product”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is used into the invention. Doing so would ensure the molecular network method would accurately identify transformation products from unknown transformation pathways.
Regarding Claim 8, Hu in view of Majewsky and Geng teach the limitations of claim 6, and Hu further teaches wherein step 3 comprises: annotating the structure of the transformation product from the unknown transformation pathways and assigning corresponding confidence levels
However, Hu in view of Majewsky and Geng does not explicitly teach confidence levels 1 to 5.
A prima facie case of obviousness exists when the claimed range overlaps or lies inside ranges disclosed by the prior art (see MPEP 2144.05). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng to have confidence levels 1 to 5. Increasing the number of confidence levels from 3 to 5 would allow for improved specificity in the confidence of a prediction.
Regarding Claim 9, Hu in view of Majewsky and Geng teach the limitations of claim 1, Hu further teaches where in Step 4 comprises: using fragment ions frequently occurring in the parent antibiotic and transformation products screened from the samples as the feature fragments, searching the peak list with the feature fragments, and supplementing the transformation product from the unknown transformation pathways (Section 2.2: “When having PFAS candidates without MS/MS spectra, we reinjected the samples into Orbitrap after adding m/z of these PFAS to the inclusion list”. The examiner notes that “PFAS candidates” are fragment ions occurring in the parent chemical and its transformation products. The examiner notes that reinjecting the samples into the MS Orbitrap after adding the m/z to the inclusion list results in searching a peak list and supplementing the transformation product from the unknown transformation pathways).
Regarding Claim 11, Hu in view of Majewsky and Geng teach the limitations of claim 3, and Hu further teaches wherein: step A.3 comprises: removing a transformation product having a similarity of less than a set value and having the same molecular descriptor with a parent structure for merging the prediction results of the transformation products obtained in step A.2 (Section 2.2: “Through the function of “Search Mass Lists” in Compound Discover 3.2, we identified the positive hits by matching the peak list with this suspect list using the criteria of mass tolerance < 5 ppm” and “After removing duplicates”).
Regarding Claim 12, Hu in view of Majewsky and Geng teach the limitations of claim 2, but Hu and Majewsky do not explicitly teach wherein: step B specifically comprises:
step B.1: preprocessing the mass spectrometry data obtained in step 1 to obtain a feature quantification table and a mass spectrometry (MS)/MS spectral summary;
step B.2: establishing the molecular network with the feature quantification table and an MS/MS spectral summary obtained in step B.1; and
step B.3: extracting mass spectrum peak information of transformation products of the parent antibiotic from the unknown transformation pathways using the molecular network obtained in step B.2.
Geng teaches wherein: step B specifically comprises:
step B.1: preprocessing the mass spectrometry data obtained in step 1 to obtain a feature quantification table and a mass spectrometry (MS)/MS spectral summary (Para 15: “The preprocessing mainly includes: chromatographic peak extraction, chromatographic peak deconvolution, isotope peak classification, mass spectrometry characteristic peak classification, and isotope filtering”);
step B.2: establishing the molecular network with the feature quantification table and an MS/MS spectral summary obtained in step B.1 (Para 17: “After processing, the preprocessed data is imported into the GNPS molecular network processing platform”); and
step B.3: extracting mass spectrum peak information of transformation products of the parent antibiotic from the unknown transformation pathways using the molecular network obtained in step B.2 (Para 19: “Based on the m/z values of the parent ion displayed at the nodes in the molecular network, identify the m/z regions of the target compound and known transformation products” and “Based on the m/z difference between the mass spectrum peak of the product and the mass spectrum peaks of adjacent parent compounds or adjacent known structures, deduce the structural formula of the product”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is established and used into the invention. Doing so would ensure the molecular network method would accurately identify transformation products from unknown transformation pathways.
Regarding Claim 13, Hu in view of Majewsky and Geng teach the limitations of claim 3, but Hu and Majewsky do not explicitly teach wherein: step B specifically comprises:
step B.1: preprocessing the mass spectrometry data obtained in step 1 to obtain a feature quantification table and a mass spectrometry (MS)/MS spectral summary;
step B.2: establishing the molecular network with the feature quantification table and an MS/MS spectral summary obtained in step B.1; and
step B.3: extracting mass spectrum peak information of transformation products of the parent antibiotic from the unknown transformation pathways using the molecular network obtained in step B.2.
Geng teaches wherein: step B specifically comprises:
step B.1: preprocessing the mass spectrometry data obtained in step 1 to obtain a feature quantification table and a mass spectrometry (MS)/MS spectral summary (Para 15: “The preprocessing mainly includes: chromatographic peak extraction, chromatographic peak deconvolution, isotope peak classification, mass spectrometry characteristic peak classification, and isotope filtering”);
step B.2: establishing the molecular network with the feature quantification table and an MS/MS spectral summary obtained in step B.1 (Para 17: “After processing, the preprocessed data is imported into the GNPS molecular network processing platform”); and
step B.3: extracting mass spectrum peak information of transformation products of the parent antibiotic from the unknown transformation pathways using the molecular network obtained in step B.2 (Para 19: “Based on the m/z values of the parent ion displayed at the nodes in the molecular network, identify the m/z regions of the target compound and known transformation products” and “Based on the m/z difference between the mass spectrum peak of the product and the mass spectrum peaks of adjacent parent compounds or adjacent known structures, deduce the structural formula of the product”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is established and used into the invention. Doing so would ensure the molecular network method would accurately identify transformation products from unknown transformation pathways.
Regarding Claim 14, Hu in view of Majewsky and Geng teach the limitations of claim 12, but Hu and Majewsky do not explicitly teach wherein: step B.2 comprises: exporting the feature quantification table and the MS/MS spectral summary obtained in step B.1 to Global Natural Products Social Molecular Networking platform, creating the molecular network using a feature-based molecular networking workflow, and setting a minimum matched fragment ion and a cosine score.
Geng teaches wherein: step B.2 comprises: exporting the feature quantification table and the MS/MS spectral summary obtained in step B.1 to Global Natural Products Social Molecular Networking platform (Para 19: “After processing, the preprocessed data is imported into the GNPS molecular network processing platform for secondary spectrum clustering and calculation”),
creating the molecular network using a feature-based molecular networking workflow (Para 19: “The resulting data is then imported into Cytoscape 2.8.3 software for molecular network visualization, yielding a visualized network diagram of the target compound's transformation products”),
and setting a minimum matched fragment ion and a cosine score (Para 23: “the cosine similarity is selected as 0.6, and the minimum number of matching peaks is set as 4”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is established into the invention. Doing so would ensure the molecular network method would be able to accurately identify transformation products from unknown transformation pathways.
Regarding Claim 15, Hu in view of Majewsky and Geng teach the limitations of claim 13, but Hu and Majewsky do not explicitly teach wherein: step B.2 comprises: exporting the feature quantification table and the MS/MS spectral summary obtained in step B.1 to Global Natural Products Social Molecular Networking platform, creating the molecular network using a feature-based molecular networking workflow, and setting a minimum matched fragment ion and a cosine score.
Geng teaches wherein: step B.2 comprises: exporting the feature quantification table and the MS/MS spectral summary obtained in step B.1 to Global Natural Products Social Molecular Networking platform (Para 19: “After processing, the preprocessed data is imported into the GNPS molecular network processing platform for secondary spectrum clustering and calculation”),
creating the molecular network using a feature-based molecular networking workflow (Para 19: “The resulting data is then imported into Cytoscape 2.8.3 software for molecular network visualization, yielding a visualized network diagram of the target compound's transformation products”),
and setting a minimum matched fragment ion and a cosine score (Para 23: “the cosine similarity is selected as 0.6, and the minimum number of matching peaks is set as 4”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is established into the invention. Doing so would ensure the molecular network method would be able to accurately identify transformation products from unknown transformation pathways.
Regarding Claim 16, Hu in view of Majewsky and Geng teach the limitations of claim 14, but Hu and Majewsky do not explicitly teach wherein: step B.3 comprises: in a graph of the molecular network established in step B.2, locating an area where the parent antibiotic and the known transformation products are present based on a mass-to-charge ratio of a precursor ion shown on a node in the molecular network, thereby extracting all the features of the sub-network, and obtaining mass spectra of the transformation products of the parent antibiotic from the unknown transformation pathways.
Geng teaches wherein: step B.3 comprises: in a graph of the molecular network established in step B.2, locating an area where the parent antibiotic and the known transformation products are present based on a mass-to-charge ratio of a precursor ion shown on a node in the molecular network (Para 19: “Based on the m/z values of the parent ion displayed at the nodes in the molecular network, identify the m/z regions of the target compound and known transformation products”),
thereby extracting all the features of the sub-network, and obtaining mass spectra of the transformation products of the parent antibiotic from the unknown transformation pathways (Para 19: “Based on the m/z difference between the mass spectrum peak of the product and the mass spectrum peaks of adjacent parent compounds or adjacent known structures, deduce the structural formula of the product”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Geng by further incorporating how the molecular network is used into the invention. Doing so would ensure the molecular network method would accurately identify transformation products from unknown transformation pathways.
Regarding Claim 17, Hu in view of Majewsky and Geng teach the limitations of claim 2, and Hu further teaches wherein step 3 comprises: annotating the structure of the transformation product from the unknown transformation pathways and assigning corresponding confidence levels
However, Hu in view of Majewsky and Geng does not explicitly teach confidence levels 1 to 5.
A prima facie case of obviousness exists when the claimed range overlaps or lies inside ranges disclosed by the prior art (see MPEP 2144.05). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng to have confidence levels 1 to 5. Increasing the number of confidence levels from 3 to 5 would allow for improved specificity in the confidence of a prediction.
Regarding Claim 18, Hu in view of Majewsky and Geng teach the limitations of claim 3, and Hu further teaches wherein step 3 comprises: annotating the structure of the transformation product from the unknown transformation pathways and assigning corresponding confidence levels
However, Hu in view of Majewsky and Geng does not explicitly teach confidence levels 1 to 5.
A prima facie case of obviousness exists when the claimed range overlaps or lies inside ranges disclosed by the prior art (see MPEP 2144.05). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng to have confidence levels 1 to 5. Increasing the number of confidence levels from 3 to 5 would allow for improved specificity in the confidence of a prediction.
Regarding Claim 19, Hu in view of Majewsky and Geng teach the limitations of claim 2, Hu further teaches where in Step 4 comprises: using fragment ions frequently occurring in the parent antibiotic and transformation products screened from the samples as the feature fragments, searching the peak list with the feature fragments, and supplementing the transformation product from the unknown transformation pathways (Section 2.2: “When having PFAS candidates without MS/MS spectra, we reinjected the samples into Orbitrap after adding m/z of these PFAS to the inclusion list”. The examiner notes that “PFAS candidates” are fragment ions occurring in the parent chemical and its transformation products. The examiner notes that reinjecting the samples into the MS Orbitrap after adding the m/z to the inclusion list results in searching a peak list and supplementing the transformation product from the unknown transformation pathways).
Regarding Claim 20, Hu in view of Majewsky and Geng teach the limitations of claim 3, Hu further teaches where in Step 4 comprises: using fragment ions frequently occurring in the parent antibiotic and transformation products screened from the samples as the feature fragments, searching the peak list with the feature fragments, and supplementing the transformation product from the unknown transformation pathways (Section 2.2: “When having PFAS candidates without MS/MS spectra, we reinjected the samples into Orbitrap after adding m/z of these PFAS to the inclusion list”. The examiner notes that “PFAS candidates” are fragment ions occurring in the parent chemical and its transformation products. The examiner notes that reinjecting the samples into the MS Orbitrap after adding the m/z to the inclusion list results in searching a peak list and supplementing the transformation product from the unknown transformation pathways).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Majewsky and Geng as applied to claim 8 above, and further in view of Duchoslav (WO 2023037295 A2).
Regarding Claim 10, Hu in view of Majewsky and Geng teach the limitations of claim 8, but Hu does not explicitly teach where step 5 comprises: selecting the transformation products at the confidence levels 1 to 3 to obtain the final list of identified products.
Duchoslav teaches selecting the transformation products at the confidence levels
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Hu in view of Majewsky and Geng with the method of Duchoslav by selecting transformation products above a confidence level threshold. Doing so would improve the accuracy and reliability of the identified transformation products. A prima facie case of obviousness exists when a claimed invention is a result of routine optimization (see MPEP 2144.05). The confidence level threshold is a result-effective variable chosen to optimize the accuracy of the system. The selection of a confidence level above 3 amounts to a design choice based on the exact needs of the system.
Conclusion
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/RODGER STEWART MENSING/ Examiner, Art Unit 2857
/LINA CORDERO/ Primary Examiner, Art Unit 2857
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