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 .
Response to Arguments
Applicant’s amendments and arguments, filed 6/4/2026, with respect to the rejection of claims 1, 2, 4, 6, 9, 11, 12, 15, 18, 19, 21, 22, 26, 28, 30, 34 and 37 under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Fritsche et al. (WO 2020/010256 A), have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. The additional dependent prior art rejections have been withdrawn as well. However, upon further consideration, a new ground(s) of rejection is made in view of Karl et al. (US 2010/0240068 A1) and Colley et al. (US 2021/0090694 A1).
The previous rejection of claims 1 – 4, 6, 9, 11, 12 and 15 under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, has been withdrawn.
Note Regarding Prior Art
Examiner cites particular sections, columns, line numbers, paragraphs and figures, in the references as applied to the claims below for the convenience of the Applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the Applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
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 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.
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.
Claim(s) 1, 2, 4, 6, 9, 11, 12 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fritsche et al. (WO 2020/010256 A1; hereinafter “Fritsche”) in view of Karl et al. (US 2010/0240068 A1; hereinafter “Karl”).
Regarding claim 1, Fritsche teaches throughout the publication a kit for detecting five markers in a subject of an unknown status (Fritsche specifically teaches a kit for detecting at least four polypeptide markers and further including additional polypeptide markers using additional associated respective reagents for each polypeptide marker; paragraphs 6, 7, 9, 94 and 95; claims 1, 6 – 11, 152 and 153) comprising:
at least five reagents, wherein each of the at least five reagents specifically binds to one of a plurality of polypeptide markers in a sample from the subject, the plurality of polypeptide markers comprising ferritin, keratin 1-10, IL-8, CEA, and LICAM (paragraphs 7, 9 and 95); and
at least one standard comprising a known amount of one of the plurality of polypeptide markers (Abstract; paragraphs 14 – 17).
Fritsche does not specifically teach wherein a known amount of ferritin in the standard is about 20 ng/ml to about 90 ng/ml.
Fritsche does teach the use of ferritin (paragraphs 9, 55, 96, 117, 119 – 122, 129, 130, 160, 161, 181, 182 and 184; claims 9 – 11 and 41).
Karl teaches a marker panel for colorectal cancer (paragraphs 105 – 109). Elevated ferritin values can be encountered with certain carcinomas (paragraph 107). Karl teaches the use of a threshold value of 20 ng/ml (paragraph 107). Consequently, as evidenced by Karl, using a known amount of ferritin of around 20 ng/ml as a standard would have been considered to be suitable and predictable to a person of ordinary skill in the art. The rationale to support an obviousness rejection under 35 U.S.C. 103 may rely on logic and sound scientific principle (see MPEP § 2144.02). The combination of familiar elements is likely to be obvious when it does no more than yield predictable results (see MPEP § 2143, A.). Furthermore, the prior art can be modified or combined to reject claims as prima facie obvious as long as there is a reasonable expectation of success (see MPEP § 2143.02). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to provide wherein a known amount of ferritin in the standard is about 20 ng/ml to about 90 ng/ml.
Regarding claim 2, Fritsche teaches the kit of claim 1, further comprising one or more non-transitory computer-readable media having computer-executable instructions embodied thereon that, when executed by one or more computing devices, cause the computing devices to analyze a detected amount of each of the plurality of polypeptide markers by a machine learning model to generate a risk assessment of the subject having or not having colorectal cancer (Abstract; paragraphs 1, 23, 25, 26 and 99; claim 2).
Regarding claim 4, Fritsche teaches the kit of claim 1, further comprising at least five detectably labelled secondary reagents, wherein each of the at least five detectably labelled secondary reagents specifically binds to one of the plurality of polypeptide markers, and each of the at least five detectably labelled secondary reagents has a different detectable label (claim 4), wherein the detectable label comprises a radioactive isotope, a fluorescent dye, and enzyme, a quantum dot, a luminescent reactant, or combinations thereof (claim 5). As discussed above, Fritsche teaches the detection of five polypeptide markers (claims 1 and 9 – 11), and also five associated detectably labelled secondary reagents or the respective polypeptide markers (claim 13).
Regarding claim 6, Fritsche teaches the kit of claim 1, further comprising a reagent for detecting GDF15, wherein the plurality of polypeptide markers further comprises GDF15 (claim 12) and at least one of MIA, Hepsin (claim 12), YKL-40, and NSE.
Regarding claim 9, Fritsche teaches the kit of claim 1, wherein the at least five reagents comprise at least five primary antibodies or antigen binding fragments thereof, each of the at least five primary antibodies or antigen binding fragments thereof specifically binding to one of the plurality of polypeptide markers (claim 12), wherein the at least five detectably labelled secondary reagents comprise at least five secondary antibodies or antigen binding fragments thereof; each of the at least five detectably labelled secondary antibodies or antigen binding fragments thereof specifically binding to one of the plurality of polypeptide markers; and each of the at least five detectably labelled antibodies or antigen binding fragments thereof has a different detectable label (claim 13).
Regarding claim 11, Fritsche teaches the kit of claim 9, wherein each of the at least five primary antibodies or antigen binding fragments thereof that specifically binds to the one of the plurality of polypeptide markers binds at a different epitope than the one of the at least five detectably labelled secondary antibodies or antigen binding fragments thereof that specifically binds to the same one of the plurality of polypeptide markers (claim 14).
Regarding claim 12, Fritsche teaches the kit of claim 4, wherein each of the at least five reagents is attached to a solid surface (claim 15), wherein the solid surface comprises a bead, a magnetic bead, a well, slide, a tube, or combinations thereof (claim 16), wherein each of the at least five reagents is attached to a different solid surface (claim 17).
Regarding claim 15, Fritsche teaches the kit of claim 12, wherein the different solid surface comprises a magnetic bead with a different internal marker (claim 18), wherein the different internal marker comprises: a fluorescent dye, a quantum dot, a protein tag, a RFID tag, or combinations thereof (claim 19), wherein the internal marker of the solid surface is different from the detectable label of the one of the at least five detectably labelled secondary reagents specific for polypeptide or nucleic acid coding for the one of the at least five polypeptides attached to the solid surface (claim 20).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fritsche et al. (WO 2020/010256 A1; hereinafter “Fritsche”) in view of Karl et al. (US 2010/0240068 A1; hereinafter “Karl”), and further in view of Micallef et al. (WO 2018/019827 A1; hereinafter “Micallef”).
Regarding claim 3, modified Fritsche teaches the kit of claim 2, wherein the risk assessment is generated by:
receiving the detected amount of each of the plurality of polypeptide markers (claim 3);
retrieving a coefficient for each of the detected amounts of each of the plurality of polypeptide markers from a database (claim 3);
multiplying each of the detected amounts of the plurality of polypeptide markers by the corresponding coefficient to generate a weighted level for each of the plurality of polypeptides (claim 3); and
analyzing a combination of weighted levels for each of the plurality of polypeptide markers with the machine learning model to determine the probability that the subject has colorectal cancer based on a change or lack thereof from a combination of predetermined weighted values of each of the plurality of polypeptide markers for normal subjects (paragraphs 19 and 25; claim 3).
However, modified Fritsche does not specifically teach further analyzing a combination of weighted levels for each of the plurality of polypeptide markers with the machine learning model to determine the probability that the subject has colorectal cancer based on an age of the subject; and a FIT concentration associated with the subject.
Micallef teaches a combination test for colorectal cancer that determines the probability that the subject has colorectal cancer based on subject age and a FIT (fecal immunochemical test) concentration of the subject (pages 1 – 8). Micallef specifically states that the combined age and numerical FIT level increases the accuracy of the combined test over the use of FIT alone (page 8, lines 1 and 2). Consequently, the additional steps of determining the probability that the subject has colorectal cancer based on an age of the subject; and a FIT concentration associated with the subject using the machine learning model would have been considered to be suitable and predictable to a person of ordinary skill in the art to improve the accuracy of the Fritsche kit and methodology disclosed therein. The combination of familiar elements is likely to be obvious when it does no more than yield predictable results (see MPEP § 2143, A.). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to additionally include the step of further analyzing a combination of weighted levels for each of the plurality of polypeptides with the machine learning model to determine the probability that the subject has colorectal cancer based on an age of the subject; and a FIT concentration associated with the subject.
Claim(s) 18, 19, 21, 22, 26, 28, 34 and 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fritsche et al. (WO 2020/010256 A1; hereinafter “Fritsche”) in view of Micallef et al. (WO 2018/019827 A1; hereinafter “Micallef”).
Regarding claim 18, Fritsche teaches a method for detecting at least five different polypeptides in a sample from a subject with unknown status (Fritsche specifically teaches a kit for detecting at least four polypeptide markers and further including additional polypeptide markers using additional associated respective reagents for each polypeptide marker; paragraphs 6, 7, 9, 94 and 95; claims 1, 6 – 11 and 21) comprising:
detecting the presence or an amount of the at least five polypeptide markers in the sample by contacting the sample with at least five reagents, each of the at least five reagents specifically detecting the presence and/or amount of one of the at least five polypeptide markers, the at least five polypeptides comprising: ferritin, keratin 1-10, IL-8, CEA, and L1CAM (paragraphs 7, 9 and 95; claims 21); and
determining whether the combination of the presence of and/or detected amounts of each of the at least five polypeptide markers is indicative of the presence of or an increased risk of the presence of colorectal cancer in the subject (abstract; claims 2 and 21),
wherein determining if the combination of the detected amounts of the at least five polypeptide markers in the sample is indicative of the presence of or an increased risk of the presence of colorectal cancer in the subject comprises:
receiving the detected amount of each of the at least five polypeptide markers on a computing device (claims 2 and 3);
retrieving a coefficient for each of the detected amounts of each of the at least five polypeptide markers from a database on the computing device (claims 2 and 3);
multiplying each of the detected amounts by the corresponding coefficient to generate a weighted level for each of the at least five polypeptide markers on the computing device (claims 2 and 3); and
analyzing the combination of weighted levels for each of the at least five polypeptide markers with a machine learning model on the computing device to determine if the subject has an increased risk of colorectal cancer, wherein the determination is based on at least one of:
a change or lack thereof in the combination of weighted levels for each of the at least five polypeptide markers detected in the sample from the subject to the combination of predetermined weighted values of the polypeptide markers for normal subjects (paragraphs 19 and 25; claim 3).
Fritsche does not specifically teach further analyzing a combination of weighted levels for each of the plurality of polypeptide markers with the machine learning model to determine the probability that the subject has colorectal cancer based on an age of the subject and a FIT concentration associated with the subject, wherein the determination classifies the subject into one of: low risk adenomatous polyps, high risk adenomatous polyps, stage I colorectal cancer, stage II colorectal cancer, stage III colorectal cancer and stage IV colorectal cancer.
Micallef teaches a combination test for colorectal cancer that determines the probability that the subject has colorectal cancer based on subject age and a FIT (fecal immunochemical test) concentration of the subject (pages 1 – 8). Micallef specifically states that the combined age and numerical FIT level increases the accuracy of the combined test over the use of FIT alone (page 8, lines 1 and 2). Micallef teaches that the determination can classify the subject as a high or low likelihood of having colorectal cancer or a colorectal adenoma or polyp (e.g., pages 8 – 15). Consequently, the additional steps of determining the probability that the subject has colorectal cancer based on an age of the subject; and a FIT concentration associated with the subject using the machine learning model would have been considered to be suitable and predictable to a person of ordinary skill in the art to improve the accuracy of the Fritsche kit and methodology disclosed therein. The combination of familiar elements is likely to be obvious when it does no more than yield predictable results (see MPEP § 2143, A.). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to additionally include the step of further analyzing a combination of weighted levels for each of the plurality of polypeptide markers with the machine learning model to determine the probability that the subject has colorectal cancer based on an age of the subject; and a FIT concentration associated with the subject, wherein the determination classifies the subject into one of: low risk adenomatous polyps, high risk adenomatous polyps, stage I colorectal cancer, stage II colorectal cancer, stage III colorectal cancer and stage IV colorectal cancer.
Regarding claim 19, Fritsche teaches wherein the sample is a serum sample, a blood sample, a plasma sample, a urine sample, a tissue sample, a feces sample, or a saliva sample (paragraphs 8; claim 22).
Regarding claim 21, Fritsche teaches wherein the at least five reagents comprise a primary antibody or antigen binding fragment thereof, wherein each of the at least five primary antibodies or antigen binding fragments thereof specifically binds to one of the at least five polypeptide markers (claim 24).
Regarding claim 22, Fritsche teaches wherein each of the at least five primary antibodies or antigen binding fragments thereof that specifically binds to one of the at least five polypeptide markers is attached to a solid surface (claim 25), wherein each of the at least five primary antibodies or antigen binding fragments thereof that specifically binds to one of the at least five polypeptide markers is attached to a different solid surface (claim 26), wherein each of the different solid surfaces has a different internal marker (claim 27), wherein the internal markers comprise a fluorescent dye, a quantum dot, a protein tag, a RFID tag, or combinations thereof (claim 28).
Regarding claim 26, Fritsche teaches wherein the at least five reagents are present in a single container (claim 29).
Regarding claim 28, Fritsche teaches the step of contacting the sample with at least five detectably labelled secondary reagents, each of the at least five detectably labelled secondary reagent specifically binding to one of the at least five polypeptide markers, each of the at least five detectably labelled secondary reagents having a different detectable label (claim 31),
wherein each of the at least five reagents form a complex with one specific polypeptide of the at least five polypeptide markers if present in the sample (claim 30), and
wherein each of the at least five detectably labelled secondary reagents comprises a secondary antibody or antigen binding fragments thereof, each secondary antibody or antigen binding fragment thereof specifically binding to one of the at least five polypeptide markers (claim 32).
Regarding claim 34, Fritsche teaches the steps of:
conducting an examination of the colon of the subject for colorectal cancer if the output shows an increased risk of the presence of colorectal cancer in the subject (claim 37); and
treating the subject for colorectal cancer if the output shows an increased risk of the presence of colorectal cancer (claim 38).
Regarding claim 37, Fritsche teaches wherein the at least five polypeptides further comprises at least one of: GDF 15, MIA, Hepsin, YKL-40, and NSE (claim 41).
Claim(s) 30 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fritsche et al. (WO 2020/010256 A1; hereinafter “Fritsche”) and Micallef et al. (WO 2018/019827 A1; hereinafter “Micallef”), and further in view of Karl et al. (US 2010/0240068 A1; hereinafter “Karl”).
Regarding claim 30, Fritsche teaches the method of claim 18, further comprising:
contacting the at least five reagents with a standard comprising a known amount of at least one of the at least five polypeptide markers (paragraph 14);
determining the amount of the at least one of the at least five polypeptide markers in the standard (paragraph 14); and
determining the accuracy of the measurement of the detected amounts of each of the at least five polypeptide markers by determining the percent coefficient of variation for each of the at least five polypeptide markers based on the detected amount of each of the at least five polypeptide markers in the standard (paragraph 17).
Fritsche does not specifically teach wherein a known amount of ferritin in the standard is about 20 ng/ml to about 90 ng/ml.
Fritsche does teach the use of ferritin (paragraphs 9, 55, 96, 117, 119 – 122, 129, 130, 160, 161, 181, 182 and 184; claims 9 – 11 and 41).
Karl teaches a marker panel for colorectal cancer (paragraphs 105 – 109). Elevated ferritin values can be encountered with certain carcinomas (paragraph 107). Karl teaches the use of a threshold value of 20 ng/ml (paragraph 107). Consequently, as evidenced by Karl, using a known amount of ferritin of around 20 ng/ml as a standard would have been considered to be suitable and predictable to a person of ordinary skill in the art. The rationale to support an obviousness rejection under 35 U.S.C. 103 may rely on logic and sound scientific principle (see MPEP § 2144.02). The combination of familiar elements is likely to be obvious when it does no more than yield predictable results (see MPEP § 2143, A.). Furthermore, the prior art can be modified or combined to reject claims as prima facie obvious as long as there is a reasonable expectation of success (see MPEP § 2143.02). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to provide wherein a known amount of ferritin in the standard is about 20 ng/ml to about 90 ng/ml.
Claim(s) 38 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fritsche et al. (WO 2020/010256 A1; hereinafter “Fritsche”) and Micallef et al. (WO 2018/019827 A1; hereinafter “Micallef”), and further in view of Wright, Jr (US 2004/0018519 A1; hereinafter “Wright”), Suleiman et al. (US 2014/0258187 A1; hereinafter “Suleiman”), Brandon et al. (US 2015/0218640 A1; hereinafter “Brandon”) and Aliper et al. (US 2019/0272890 A1; hereinafter “Aliper”).
Regarding claim 38, modified Fritsche does not specifically teach the method of claim 18, further comprising the step of transforming data associated with the detected amount of each of the at least five polypeptide markers, comprising:
detecting outliers of the data;
clamping values of the outliers;
applying a log transformation to data with log-normal distributions; and
applying a z-score normalization to all data.
Fritsche does teach the use of statistical methodologies and/or different types of mathematical models for data analysis (e.g., paragraphs 155 – 158, 172 and 182).
However, the following steps of: detecting outliers of the data (Wright; paragraph 137); clamping values of the outliers (Suleiman; paragraph 75); applying a log transformation to data with log-normal distributions (Brandon; paragraph 933); and applying a z-score normalization to all data (Aliper; paragraph 142), are well known in the art of data and statistical analysis. Consequently, the use these additional steps of data and statistical analysis for studying the data of polypeptide marker detection would have been considered to be suitable and predictable to a person of ordinary skill in the art to improve the accuracy of the Fritsche kit and methodology disclosed therein. The combination of familiar elements is likely to be obvious when it does no more than yield predictable results (see MPEP § 2143, A.). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to additionally include these additional data and statistical analysis steps.
Claim(s) 39 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fritsche et al. (WO 2020/010256 A1; hereinafter “Fritsche”) and Micallef et al. (WO 2018/019827 A1; hereinafter “Micallef”), and further in view of Colley et al. (US 2021/0090694 A1; hereinafter”Colley”).
Regarding claim 39, modified Fritsche does not specifically teach the method of claim 18, wherein:
the machine learning model comprises a support vector classification algorithm trained using training data comprising the detected amounts of the at least five polypeptide markers, the age of the subject, and the FIT concentration associated with the subject, and
wherein analyzing the combination of weighted levels for each of the at least five polypeptide markers with the machine learning model on the computing device to determine if the subject has an increased risk of colorectal cancer classifies the subject into one of: low risk adenomatous polyps, high risk adenomatous polyps, stage I colorectal cancer, stage II colorectal cancer, stage III colorectal cancer, or stage IV colorectal cancer.
Colley teaches the use of machine learning models comprising a support vector classification algorithm in data-based cancer research and treatment systems and methods (e.g., paragraphs 1131, 1150, 1477, 1503 and 1640).
Micallef teaches a combination test for colorectal cancer that determines the probability that the subject has colorectal cancer based on subject age and a FIT (fecal immunochemical test) concentration of the subject (pages 1 – 8). Micallef specifically states that the combined age and numerical FIT level increases the accuracy of the combined test over the use of FIT alone (page 8, lines 1 and 2). Micallef teaches that the determination can classify the subject as a high or low likelihood of having colorectal cancer or a colorectal adenoma or polyp (e.g., pages 8 – 15). Consequently, the additional steps of determining the probability that the subject has colorectal cancer based on an age of the subject; and a FIT concentration associated with the subject using a machine learning model comprising a support vector classification algorithm would have been considered to be suitable and predictable to a person of ordinary skill in the art to improve the accuracy of the Fritsche kit and methodology disclosed therein. The combination of familiar elements is likely to be obvious when it does no more than yield predictable results (see MPEP § 2143, A.). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to provide wherein the machine learning model comprises a support vector classification algorithm trained using training data comprising the detected amounts of the at least five polypeptide markers, the age of the subject, and the FIT concentration associated with the subject, and wherein analyzing the combination of weighted levels for each of the at least five polypeptide markers with the machine learning model on the computing device to determine if the subject has an increased risk of colorectal cancer classifies the subject into one of: low risk adenomatous polyps, high risk adenomatous polyps, stage I colorectal cancer, stage II colorectal cancer, stage III colorectal cancer, or stage IV colorectal cancer.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRIAN J. SINES whose telephone number is (571)272-1263. The examiner can normally be reached 9 AM-5 PM EST M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Elizabeth A Robinson can be reached at (571) 272-7129. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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BRIAN J. SINES
Primary Patent Examiner
Art Unit 1796
/BRIAN J. SINES/Primary Examiner, Art Unit 1796
Prosecution Insights