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 Status
Claim(s) 2-11 and 14-15 are currently pending and under examination herein.
Claim(s) 2-11 and 14-15 are rejected.
Priority
The instant application claims priority as a 371 of PCT/KR2022/007648 filed 30 May 2022 and foreign priority to KR10-2021-0068890 filed 28 May 2021. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. In this action, claims 2-11 and 14-15 are examined as though they had an effective filing date of 28 May 2021. In future actions, the effective filing date of one or more claims may change, due to amendments to the claims, or further analysis of the disclosure(s) of the priority application(s).
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 05 November 2023, 27 February 2025, and 05 July 2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings filed 05 November 2023 are accepted.
Specification
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code. A link (https://doi.org/10.1038/ng.3646) was found in paragraph 0109 of the published specification (US 20240233946 A1). Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http://, www., or other browser-executable code. See MPEP § 608.01.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Claim
Structure
Algorithm
Interpretation
a decoder configured to
14
0088-0089
0088-0090
Sequencing device and computer
an aligner configured to
14
None
None
Computer
(See 112 rejections)
a nucleic acid fragment selector configured to
14
None
None
Computer
(See 112 rejections)
a data producer configured to
14
None
None
Computer
(See 112 rejections)
a cancer diagnostic unit configured to
14
None
None
Computer
(See 112 rejections)
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof (see table above).
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claim 14 and 15 is rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
The aligner, nucleic acid fragment selector, data producer, and cancer diagnostic unit of claim 14 invoke 112(f) interpretation (see claim interpretation above). However, the required structure (and algorithms for computer implementation) of these system components were not found to be described within the disclosure.
Claim 15 recites a computer-readable storage medium including an instruction that includes obtaining a sequence information from extracted nucleic acids from a biological sample. This is interpreted as encompassing physical sequencing biological material to generate reads data. It is not disclosed how a computer-readable storage medium executed by a processor is capable of sequencing biological material. This rejection can be overcome by demonstrating the CRM is linked to a device that is capable of sequencing.
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.
Claims 5-6 and 14 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 5 recites selecting reads based “a cut-off value”. Claim 2 already recites a cut-off value in step e. If these values are the same, claim 5 should recite the cut off values. This issues is accentuated by claim 6, which is dependent to claim 5 and specifies “the cut-off value is 50 to 70”. It is unclear is this is limiting the cut-off value of claims 5, claim 2, or both. To overcome this rejection, the cut-off values should be referred to by different labels if the cut-off values of claims 2 and 5 are different. If they are the same, “a” should be changed to “the” in claim 5. For the purposes of examination, they do not need to be the same cut-off value. Claim 6 depends on claim 5 and this contains the issues through its dependence.
Limitations of claim 14 invokes 35 U.S.C. 112(f) (see claim interpretation section above). However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The required structure (and algorithms for computer implementation) were not found to be described within the disclosure (see 112(a) above). Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b). For the purposes of examination, the functions of nucleic acid fragment selector, data producer, and cancer diagnostic unit are interpreted to executed by generic computing systems.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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.
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claim 15 recites “A computer-readable storage medium” executed by a processor. The claims and specification do not define the computer readable medium as non-transitory. Therefore, the broadest reasonable interpretation encompass transitory medium. Transitory forms of signal transmission (often referred to as "signals per se") are not directed to any of the statutory categories (see MPEP 2106.03). Therefore, the claim is not directed to a statutory category. This rejection can be overcome by specifying that the CRM is non-transitory in the claim.
Claims 2-11 and 14-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea and a natural law without significantly more. In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea or natural law (Step 2A, Prong 1). Claims 2-11 are directed to a method and Claim 14 is directed to a system. Although claim 15 is not directed to a statutory category of invention (see above), it is included the subject matter eligibility analysis to facilitate compact prosecution. In the instant application, the claims recite the following limitations that equate to an abstract idea or natural law:
Claim 2 recite the limitation - aligning the sequence information (reads) with a reference genome database; selecting nucleic acid fragments of regulatory regions based on the aligned sequence reads; and producing image data from the selected nucleic acid fragments. Based on the broadest reasonable interpretation, aligning reads, selecting fragments, and producing image data could practically be done by the human mind. This draws the limitation to a mental process, which classifies the limitation as an abstract idea. The claim also recites inputting and analyzing the produced image data to an artificial intelligence model trained to distinguish a normal image from a cancer image, and then comparing an output value with a cut-off value, and determining that cancer develops when the output value is higher than the cut-off value. Based on the broadest reasonable interpretation, analyzing data with a generic machine learning model and comparing values encompasses equations and could practically be done by the human mind. This draws the limitation to a mathematical concept and a mental process, which classifies the limitation as an abstract idea. Additionally, the claim relies on using the amount of a biomarker (sequence reads information) to predict a condition (cancer). This describes a natural correlation which classifies the claim as a law of nature.
Claim 5 recites the limitation - selecting reads having a mapping quality score of the aligned nucleic acid fragments equal to or greater than a cut-off value prior to step (c). Based on the broadest reasonable interpretation, selecting reads and comparing values encompasses equations and could practically be done by the human mind. This draws the limitation to a mathematical concept and a mental process, which classifies the limitation as an abstract idea.
Claim 6 recites the limitation - wherein the cut-off value is 50 to 70. This limitation specifies the selecting judicial exception of claim 5. The refined limitation indicated still represents a judicial expectation.
Claim 7 recites the limitation - wherein the regulatory region in step (c) is a tissue-specific regulatory region. This limitation specifies the selecting judicial exception of claim 2. The refined limitation indicated still represents a judicial expectation.
Claim 8 recites the limitation - the tissue-specific regulatory region is characterized in that a length and/or amount of cell-free DNA detected for respective tissues is different. Based on the broadest reasonable interpretation, comparing values encompasses equations and could practically be done by the human mind. This draws the limitation to a mathematical concept and a mental process, which classifies the limitation as an abstract idea.
Claim 9 recites the limitation - wherein the image in step (d) is a one-dimensional image wherein the x-axis comprises the number of reads for each alignment position of the selected nucleic acid fragment. This limitation specifies the producing judicial exception of claim 2. The refined limitation indicated still represents a judicial expectation.
Claim 10 recites the limitation - wherein the artificial intelligence model in step (e) is an artificial neural network. This limitation specifies the analyzing judicial exception of claim 2. The refined limitation indicated still represents a judicial expectation.
Claim 11 recites the limitation - wherein the artificial neural network is a convolutional neural network (CNN) or a recurrent neural network (RNN). This limitation specifies the analyzing judicial exception of claim 2. The refined limitation indicated still represents a judicial expectation.
Claim 14 recites the limitation - align the decoded sequence with a reference genome database; select nucleic acid fragments of regulatory regions based on the aligned sequence reads; produce the selected nucleic acid fragments as image data. Based on the broadest reasonable interpretation, aligning reads, selecting fragments, and producing image data could practically be done by the human mind. This draws the limitation to a mental process, which classifies the limitation as an abstract idea. The claim also recites input the produced image data to an artificial intelligence model trained to distinguish a normal image from a cancer image, to compare an output value with a cut-off value and to determine that cancer develops when the output value is higher than the cut-off value. Based on the broadest reasonable interpretation, analyzing data with a generic machine learning model and comparing values encompasses equations and could practically be done by the human mind. This draws the limitation to a mathematical concept and a mental process, which classifies the limitation as an abstract idea. Additionally, the claim relies on using the amount of a biomarker (sequence reads information) to predict a condition (cancer). This describes a natural correlation which classifies the claim as a law of nature.
Claim 15 recites the limitation - aligning the sequence information (reads) with a reference genome database; selecting nucleic acid fragments of regulatory regions based on the aligned sequence reads; and producing image data from the selected nucleic acid fragments. Based on the broadest reasonable interpretation, aligning reads, selecting fragments, and producing image data could practically be done by the human mind. This draws the limitation to a mental process, which classifies the limitation as an abstract idea. The claim also recites inputting and analyzing the produced image data to an artificial intelligence model trained to distinguish a normal image from a cancer image, and then comparing an output value with a cut-off value, and determining that cancer develops when the output value is higher than the cut-off value. Based on the broadest reasonable interpretation, analyzing data with a generic machine learning model and comparing values encompasses equations and could practically be done by the human mind. This draws the limitation to a mathematical concept and a mental process, which classifies the limitation as an abstract idea. Additionally, the claim relies on using the amount of a biomarker (sequence reads information) to predict a condition (cancer). This describes a natural correlation which classifies the claim as a law of nature.
These limitations recite concepts of aligning, selecting, comparing, and producing information and values and the utilization of generic machine learning models that are so generically recited that they can be practically performed in the human mind as claimed, which falls under the “Mental processes” and “Mathematical concepts” grouping of abstract ideas. A mathematical concept need not be expressed in mathematical symbols, because words used in a claim operating on data to solve a problem can serve the same purpose as a formula (MPEP 2106.04(a)(2)). Additionally, both product claims and process claims may recite mental processes, which can include a claim that requires a computer (MPEP 2106.04(a)(2)). Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. Additionally, the limitations describe natural correlations between biomarkers and their corresponding disease, which fall under natural laws. This is similar to a correlation between the presence of myeloperoxidase in a bodily sample (such as blood or plasma) and cardiovascular disease risk (Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352, 1361, 123 USPQ2d 1081, 1087 (Fed. Cir. 2017)) that the courts have identified as a law of nature. As such, claims 2-11 and 14-15 recite an abstract idea and law of nature (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). These judicial exceptions are not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology (MPEP § 2106.04(d)(1)). Rather, the claims provide insignificant extra-solution activity (MPEP § 2106.05(g)) and provide mere instructions to apply a judicial exception (MPEP § 2106.05(f)). Specifically, the claims recite the following additional elements:
Claim 2 recites obtaining a sequence information from extracted nucleic acids from a biological sample.
Claim 3 recites obtaining nucleic acids from a biological sample; removing proteins, fats, and other residues from the obtained nucleic acids using a salting-out method, a column chromatography method, or a bead method to obtain purified nucleic acids; producing a single-end sequencing or paired-end sequencing library for the purified nucleic acids or nucleic acids randomly fragmented by enzymatic digestion, pulverization, or hydroshearing; reacting the produced library with a next-generation sequencer; and obtaining sequence information (reads) of the nucleic acids in the next-generation sequencer.
Claim 4 recites wherein the nucleic acid in step (a) is cell-free DNA.
Claim 14 recites a decoder configured to extract nucleic acids from a biological sample and decode sequence information; an aligner; a nucleic acid fragment selector; a data producer; and a cancer diagnostic unit.
Claim 15 recites a computer-readable storage medium including an instruction configured to be executed by a processor; and obtaining a sequence information from extracted nucleic acids from a biological sample.
There are no limitations that indicate that the claimed aligning, selecting, comparing, and producing information and values and the utilization of generic machine learning models require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible. There is no indication that these steps are affected by the judicial exception in any way and thus do not integrate the recited judicial exception into a practical application. As such, claims 2-11 and 14-15 are directed to an abstract idea and natural law (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite conventional additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment. The claims also recite conventional additional elements that represent insignificant extra-solution activities.
As discussed above, there are no additional limitations to indicate that the claimed aligning, selecting, comparing, and producing information and values and the utilization of generic machine learning models require anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea or natural law using a generic computer do not render an abstract idea or natural law eligible. MPEP 2106.05(f) discloses that mere instructions to apply the judicial exception cannot provide an inventive concept to the claims. As specified in MPEP 2106.05(g), extra-solution activities can be understood as incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Insignificant extra-solution activities include mere data gathering, selecting a particular data source or type of data to be manipulated, and displaying information. Additionally, Bennett et al. (2017, Oncotarget, Vol. 7: 1-23) teach the extraction, preparation, and sequencing of cell free DNA, including analysis of reads data with a computer, was well understood, routine, and conventional at the time of the effective filing date (Page 2, Table 1: Comparison of NGS panels and library preparation kits; Page 3, Figure 1: Rise of publications in cell-free DNA, next-generation sequencing, and personalized medicine; Page 13, Column 2, Paragraph 2: software facilitates data analysis, annotation, and visualization).
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, Claims 2-11 and 14-15 are not patent eligible.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 2, 4-5, 7-11, and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Curtis et al. (US 20190287654 A1), in view of Nicula et al. (US 20200005899 A1, IDS from 27 February 2025). Italicized text from reference art.
Applicable claims include:
Claim 2. A method for early diagnosis of cancer based on artificial intelligence, comprising: (Claim 2.i) (a) obtaining a sequence information from extracted nucleic acids from a biological sample; (Claim 2.ii) (b) aligning the sequence information (reads) with a reference genome database; (Claim 2.iii) (c) selecting nucleic acid fragments of regulatory regions based on the aligned sequence reads; (Claim 2.iv) (d) producing image data from the selected nucleic acid fragments; and (Claim 2.v) (e) inputting and analyzing the produced image data to an artificial intelligence model trained to distinguish a normal image from a cancer image, and then (Claim 2.vi) comparing an output value with a cut-off value, and determining that cancer develops when the output value is higher than the cut-off value.
Claim 4. The method according to claim 2, wherein the nucleic acid in step (a) is cell-free DNA.
Claim 5. The method according to claim 2, further comprising: selecting reads having a mapping quality score of the aligned nucleic acid fragments equal to or greater than a cut-off value prior to step (c).
Claim 7. The method according to claim 2, wherein the regulatory region in step (c) is a tissue-specific regulatory region.
Claim 8. The method according to claim 7, wherein the tissue-specific regulatory region is characterized in that a length and/or amount of cell-free DNA detected for respective tissues is different.
Claim 9. The method according to claim 2, wherein the image in step (d) is a one-dimensional image wherein the x-axis comprises the number of reads for each alignment position of the selected nucleic acid fragment.
Claim 10. The method according to claim 2, wherein the artificial intelligence model in step (e) is an artificial neural network.
Claim 11. The method according to claim 10, wherein the artificial neural network is a convolutional neural network (CNN) or a recurrent neural network (RNN).
Claim 14. A device for early diagnosis of cancer based on artificial intelligence, the device comprising: (Claim 14.i) a decoder configured to extract nucleic acids from a biological sample and decode sequence information; (Claim 14.ii) an aligner configured to align the decoded sequence with a reference genome database; (Claim 14.iii) a nucleic acid fragment selector configured to select nucleic acid fragments of regulatory regions based on the aligned sequence reads; (Claim 14.iv) a data producer configured to produce the selected nucleic acid fragments as image data; and (Claim 14.v) a cancer diagnostic unit configured to input the produced image data to an artificial intelligence model trained to distinguish a normal image from a cancer image, (Claim 14.vi) to compare an output value with a cut-off value and to determine that cancer develops when the output value is higher than the cut-off value.
Claim 15. A computer-readable storage medium including an instruction configured to be executed by a processor for conducting early diagnosis of cancer, through the following steps comprising: (Claim 15.i) (a) obtaining a sequence information from extracted nucleic acids from a biological sample; (Claim 15.ii) (b) aligning the sequence information (reads) with a reference genome database; (Claim 15.iii) (c) selecting nucleic acid fragments of regulatory regions based on the aligned sequence reads; (Claim 15.iv) (d) producing image data from the selected nucleic acid fragments; and (Claim 15.v) (e) inputting and analyzing the produced image data to an artificial intelligence model trained to distinguish a normal image from a cancer image, and then (Claim 15.vi) comparing an output value with a cut-off value, and determining that cancer develops when the output value is higher than the cut-off value.
Regarding Claims 2, 14, and 15, Curtis et al. teach (Claim 2.i) (a) obtaining a sequence information from extracted nucleic acids from a biological sample (Paragraph 0104: chromatin-derived nucleic acid sequences may be derived from cfNAs extracted from biological source). Curtis et al. teach (Claim 2.ii) (b) aligning the sequence information (reads) with a reference genome database (Paragraph 0104: chromatin-derived nucleic acid sequences are derived from databases; Paragraph 0105: Mapping can be performed with any appropriate annotated genome). Curtis et al. teach (Claim 2.iii) (c) selecting nucleic acid fragments of regulatory regions based on the aligned sequence reads (Paragraph 0097: Sequencing reads are processed, mapped, and aligned to reveal signals associated with chromatin-derived sequence reads (e.g., regulatory regions)). Curtis et al. teach (Claim 2.iv) (d) producing image data from the selected nucleic acid fragments (Paragraph 0112: constructing and compressing V-plots using frequency sequence signal maps). Curtis et al. teach (Claim 2.v) (e) inputting and analyzing the produced image data to an artificial intelligence model trained to distinguish a normal image from a cancer image (Paragraph 0108: a signal map having a disease can be compared with a signal map of healthy individuals to reveal signals particular to a disease; Paragraph 0138: computational machine-learning models can be trained to predict feature outcome; Paragraph 0139: features include disease vs. healthy, disease stage). Additionally, Curtis et al. teach the methods are performed by computing devices which include computers, memory, processors, and computer-readable storage medium (Paragraph 0149). Claims 14 recites the limitations of claim 2 directed to a system and claim 15 recite the limitations of claim 2 directed to a computer-readable storage medium.
Regarding Claim 4, Curtis et al. teach the nucleic acid in step (a) is cell-free DNA (Paragraph 0086: sequences of cell-free nucleic acid (cfDNA) molecules are used as the input sequence).
Regarding Claim 5, Curtis et al. teach selecting reads having a mapping quality score of the aligned nucleic acid fragments equal to or greater than a cut-off value prior to step (c) (Paragraph 0227: samples were discarded due to low alignment rates, poor peak call quality).
Regarding Claim 7, Curtis et al. teach the regulatory region in step (c) is a tissue-specific regulatory region (Paragraph 0095: Signal profiles can be weighted and/or filtered; Paragraph 0096: A feature is a biological description that can be used to describe a signature of signals. A feature is a tissue origin).
Regarding Claim 8, Curtis et al. teach the tissue-specific regulatory region is characterized in that a length and/or amount of cell-free DNA detected for respective tissues is different (Paragraph 0100: a signal profile derived from an individual's cfDNA extracted from plasma may be first inserted into models to determine tissue origin; Paragraph 0200: signals corresponding to ocular tissue would be expected to be very low in cfDNA samples).
Regarding Claim 9, Curtis et al. teach wherein the image in step (d) is a one-dimensional image wherein the x-axis comprises the number of reads for each alignment position of the selected nucleic acid fragment (Paragraph 0112: a 2-D V-Plot is plotted on top a 1-D sequence signal reads). Paragraph 0115 of published specification indicate Figure 5 is a 1D image for the instant application (see image below).
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Curtis et al. show their 1D plots in figure 5A (see image below).
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The images show equivalent images.
Regarding Claim 10, Curtis et al. teach the artificial intelligence model in step (e) is an artificial neural network (Paragraph 0098: convolutional neural networks (CNNs)).
Regarding Claim 11, Curtis et al. teach the artificial neural network is a convolutional neural network (CNN) (Paragraph 0098: convolutional neural networks (CNNs)).
Curtis et al. teach does not explicitly teach comparing an output value with a cut-off value, and determining that cancer develops when the output value is higher than the cut-off value (Claim 2.vi, Claim 14.vi, Claim 15.vi). Curtis et al. teach does not explicitly teach a sequencing device (Claim 14). Nicula et al. teach related methods for utilizing cell free DNA data and neural networks to predict cancer.
Regarding Claims 2, 14, and 15, Nicula et al. (Claim 2.vi) comparing an output value with a cut-off value, and determining that cancer develops when the output value is higher than the cut-off value (Paragraph 0015: feed values from the convolutional neural network path final layer into the scorer. Accordingly, scores are obtained from the scorer, each corresponding to a vector set and these scores are compared to the subject cancer conditions). Additionally, “determining that cancer develops when the output value is higher than the cut-off value” is interpreted as a contingent limitation, which requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met (MPEP 2111.04). Additionally, Nicula et al. teach sequencing devices (Paragraph 0130: Roche 454 platform).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to combine Nicula et al. with Curtis et al. Nicula et al. teach distinct methods with a highly related goal to Curtis et al., which is to use sequencing data from cell free DNA within neural networks to predict cancer attributes. Nicula et al. teach their modeling methods enhanced accuracy and were highly sensitive and specific (Paragraph 0012: ways of processing such data in order to derive accurate classifiers for cancer diagnosis are needed in the art. The present disclosure addresses the shortcomings identified in the background by providing robust techniques for classifying a cancer condition for a species; Paragraph 0302: Table 2 below provides a comparison of the performance of the network architecture of FIG. 3 and Example 6 (termed “CNN” in Table 2)). Furthermore, one of ordinary skill in the art would predict that the methods could be readily combined with a reasonable expectation of success because both are within the same technical field – using genetic data from cell free DNA and neural networks to predict cancer attributes.
Claims 2-11 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Curtis et al., in view of Nicula et al., as applied above to claims 2, 4-5, 7-11, and 14-15, and in further view of Cho et al. (US 20180357366 A1). Italicized text from reference art.
Applicable claims include:
Claim 2, 4-5, 7-11, and 14-15 are presented above.
Claim 3. The method according to claim 2, wherein step (a) to obtain sequence information comprises: (Claim 3.i) (a-i) obtaining nucleic acids from a biological sample; (Claim 3.ii) (a-ii) removing proteins, fats, and other residues from the obtained nucleic acids using a salting-out method, a column chromatography method, or a bead method to obtain purified nucleic acids; (Claim 3.iii) (a-iii) producing a single-end sequencing or paired-end sequencing library for the purified nucleic acids or nucleic acids randomly fragmented by enzymatic digestion, pulverization, or hydroshearing;(Claim 3.iv) (a-iv) reacting the produced library with a next-generation sequencer; and (Claim 3.v) (a-v) obtaining sequence information (reads) of the nucleic acids in the next-generation sequencer.
Claim 6. The method according to claim 5, wherein the cut-off value is 50 to 70.
Regarding Claims 2, 4-5, 7-11, and 14-15, the limitations are taught by Curtis et al. and Nicula et al. as indicated above.
Curtis et al. and Nicula et al. do not explicitly teach all of the specific sequencing techniques of claim 3 or the specific range of the cutoff value of claims 6. Cho et al. teach related methods for extracting and analyzing sequence data from cell free DNA.
Regarding Claim 3, Cho et al. teach (Claim 3.i) (a-i) obtaining nucleic acids from a biological sample (Paragraph 0008: obtaining reads from an extracted DNA from a maternal biological sample). Cho et al. teach (Claim 3.ii) (a-ii) removing proteins, fats, and other residues from the obtained nucleic acids using a salting-out method, a column chromatography method, or a bead method to obtain purified nucleic acids (Paragraph 0033: removing protein, fat and other residues from the obtained mixture of fetal and maternal nucleic acids by a salting-out method, a column chromatography method or a bead-based method, and collecting purified nucleic acids). Cho et al. teach (Claim 3.iii) (a-iii) producing a single-end sequencing or paired-end sequencing library for the purified nucleic acids or nucleic acids randomly fragmented by enzymatic digestion, pulverization, or hydroshearing (Paragraph 0034: constructing a single-end sequencing or pair-end sequencing library for the purified nucleic acids or nucleic acids randomly fragmented by an enzymatic cleavage, pulverization or hydroshear method). Cho et al. teach (Claim 3.iv) (a-iv) reacting the produced library with a next-generation sequencer (Paragraph 0035: subjecting the constructed library to a next-generation sequencer). Cho et al. teach (Claim 3.v) (a-v) obtaining sequence information (reads) of the nucleic acids in the next-generation sequencer (Paragraph 0036: obtaining nucleic acid reads from the next-generation sequencer).
Regarding Claim 5, Cho et al. teach selecting reads having a mapping quality score of the aligned nucleic acid fragments equal to or greater than a cut-off value prior to step (c) (Paragraph 0010: calculating Q-scores for the aligned reads, and selecting only reads which are equal to or lower than a cut-off value).
Regarding Claim 6, Cho et al. teach the cut-off value is 50 to 70 (Paragraph 0047: the mapping quality score may more preferably 50-70 scores).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date to combine Cho et al. with Nicula et al. and Curtis et al. Cho et al. teach methods for generating cell free DNA sequence data which are inputs to the modeling of Nicula et al. and Curtis et al. Cho et al. teach also teach their methods are highly accurate with enhanced sensitivity and reduced error utilizing cell free DNA (Paragraph 0002: a technology for correcting these false-positive and false-negative rates is urgently needed. Accordingly, the present inventors have made extensive efforts to solve the above-described problems and develop a method for detecting fetal chromosomal abnormalities with high sensitivity and low false-positive). Furthermore, one of ordinary skill in the art would predict that the methods could be readily combined with a reasonable expectation of success because both are within the same technical field – generate and/or utilize genetic data from cell free DNA to predict disease attributes.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 2, 3, 10, 11, and 15 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 13, and 18 of copending Application No. 17780813 in view of the specification of application 17780813.
Matching claims
Instant Application
Application 17780813
2*
1
3
2
10
13
11
13
15
18
All limitations of the cited claims of the instant application are anticipated by the cited claims of application 17780813. One exception (*) is the limitation of claim 2 of the instant application, which is “selecting nucleic acid fragments of regulatory regions based on the aligned sequence reads”. However, this is obvious over Paragraph 2 of the specification of application 17780813 - “These chromosomal regions are associated with tumor-related oncogene and tumor suppressor gene regions”. This is a provisional nonstatutory double patenting rejection.
Claim 2, 3, 10, 11, 14, and 15 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 2, 3, 7, 8, 13, and 14 of copending Application No. 18564601 in view of the specification of application 18564601.
Matching claims
Instant Application
Application 18564601
2*
2, 7
3
3
10
8
11
8
14
13
15
14
All limitations of the cited claims of the instant application are anticipated by the cited claims of application 18564601. One exception (*) is the limitation of claim 2 of the instant application, which is “selecting nucleic acid fragments of regulatory regions based on the aligned sequence reads”. However, this is obvious over Paragraph 60 of the specification of application 18564601 - “Template amplification methods such as PCR can be coupled with NGS platforms to target or enrich specific regions of the genome (e.g., exons)”. This is a provisional nonstatutory double patenting rejection.
Conclusion
No claims are allowed.
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/B.H.E./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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