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 .
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 – 4, 6, 9, 11, 12 and 15 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.
Claim 1 recites the limitation "polypeptides" in lines 4 and 7. There is insufficient antecedent basis for this limitation in the claim. The polypeptides are the markers being detected. The term markers is not presently recited anywhere else in the claim, so it is unclear as to what the markers term is referring to. Claim 1 should read “[a] kit for detecting at least five polypeptide markers … .” The term “polypeptide markers” should be used in the claim for clarity, and the rest of the dependent claims amended correctly as appropriate.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 2, 4, 6, 9, 11, 12, 15, 18, 19, 21, 22, 26, 28, 30, 34 and 37 is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Fritsche et al. (WO 2020/010256 A1; hereinafter “Fritsche”).
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, each of the at least five reagents specifically binds to one of a plurality of polypeptides in a sample from the subject, the plurality of polypeptides 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 polypeptides (Abstract; paragraphs 14 – 17).
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 polypeptides 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 polypeptides, 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 polypeptides 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 polypeptides (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 polypeptides; 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 polypeptides 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 polypeptides (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).
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 polypeptides 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 polypeptides, 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 polypeptides is indicative of the presence of or an increased risk of the presence of colorectal cancer in the subject (abstract; claims 2 and 21).
Regarding claim 19, Fritsche teaches the method of claim 18, 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 the method of claim 18, 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 polypeptides (claim 24).
Regarding claim 22, Fritsche teaches the method of claim 21, wherein each of the at least five primary antibodies or antigen binding fragments thereof that specifically binds to one of the at least five polypeptides 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 polypeptides 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 the method of claim 18, wherein the at least five reagents are present in a single container (claim 29).
Regarding claim 28, Fritsche teaches the method of claim 18, further comprising; 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 polypeptides, 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 polypeptides 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 polypeptides (claim 32).
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 polypeptides (paragraph 14);
determining the amount of the at least one of the at least five polypeptides in the standard (paragraph 14); and
determining the accuracy of the measurement of the detected amounts of each of the at least five polypeptides by determining the percent coefficient of variation for each of the at least five polypeptides based on the detected amount of each of the at least five polypeptides in the standard (paragraph 17).
Regarding claim 34, Fritsche teaches the method of claim 18, further comprising;
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 the method of claim 18, wherein the at least five polypeptides further comprises at least one of: GDF 15, MIA, Hepsin, YKL-40, and NSE (claim 41).
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) 3 and 32 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 3, Fritsche teaches the kit of claim 2, wherein the risk assessment is generated by:
receiving the detected amount of each of the plurality of polypeptides (claim 3);
retrieving a coefficient for each of the detected amounts of each of the plurality of polypeptides from a database (claim 3);
multiplying each of the detected amounts of the plurality of polypeptides 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 polypeptides 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 polypeptides for normal subjects (paragraphs 19 and 25; claim 3).
However, Fritsche does not specifically teach 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.
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.
Regarding claim 32, Fritsche teaches the method of claim 18, wherein determining if the combination of the detected amounts of the at least five polypeptides 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 polypeptides on a computing device (claims 2 and 3);
retrieving a coefficient for each of the detected amounts of each of the at least five polypeptides 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 polypeptides on the computing device (claims 2 and 3); and
analyzing the combination of weighted levels for each of the at least five polypeptides 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 a change or lack thereof in the combination of weighted levels for each of the at least five polypeptides detected in the sample from the subject to the combination of predetermined weighted values of the polypeptides for normal subjects (paragraphs 19 and 25; claim 3).
However, Fritsche does not specifically teach 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.
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) 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 32, further comprising the step of transforming data associated with the detected amount of each of the at least five polypeptides, 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.
Conclusion
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