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 .
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/11/2025 has been entered.
Claims 1-10, 14-17 are pending in this application. Claims 11-13 have been canceled. New claims 15-17 appear to be a reworking of previously pending Claims 11 and 13, and are accordingly accepted as being drawn to an examined embodiment.
Claim 1 has been amended to recite “complexity-control contigs.” The provisional application, filed 7/14/2020 fails to provide basis for this limitation. Therefore, the effective filing date for the claims as amended is 7/13/2021, the filing date of this application.
The rejections under 35 USC 103 have been withdrawn in view of applicant’s amendments and arguments, however, new prior art rejections are set forth below.
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 1-10 and 14-17 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 has been amended to recite that the generated sequence reads are aligned to a reference “that includes complexity-control contigs;”
The metes and bounds of the term “complexity control contigs” in claim 1 are entirely unclear. The specification does not provide a clear definition of this term, with respect to what such a sequence is intended to comprise, in carrying out the method. “Complexity-control contigs” does not appear to be a common term of the prior art. “Complexity-control” is abbreviated in the disclosure as “CC”. CC is used in the specification, beginning at p9, referring to “unique control sequences (CC-IS)” which appears to be a separate concept from the “complexity control contigs” of the claim limitation. P10 of the specification uses CC in reference to “unique complexity reads of the N region (CC-IS) …” which appears to be a separate concept from “complexity control contigs” of the claims. P12 of the specification references “the CC-IS” in the calculation of the target IS input level. It is unclear which CC-IS is being referred to in this context. The specification only mentions contigs, and complexity control together in the context of Example 3: which identifies that the reference sequence comprised “17 overlapping RNA contigs…” in the context of creating the DNA library. Example 3 does not clearly identify what a “complexity control contig” is intended to comprise. The only other reference to “CC” and “contigs” appears later in Example 3, after sequencing, in the alignment step:
“FASTQ sequence were aligned using BWA mem and a Wuhan SARS-CoV-2 reference sequence (MN908947.3) appended with the SNAQ-SEQ IS and CC contigs. An awk script was used to count IS and NT amplicons, extract the CC degenerate sequences and their flanking bases (positions 5531-5540, and 5753-5807) and count unique complexity sequences (Fig. 1, squares).” (p13).
The limitation added to claim 1, without the SNAQ-SEQ IS, and CC contigs (possibly containing predicted degenerate sequences) appended to a reference sequence, appears to be broader than the disclosure, and it is not clear what, in particular, the CC contigs must comprise to be operable in the claimed methods.
In claim 1, the use of “internal standard” “IS” “unique IS” “CC” and “complexity control” seemingly interchangeably in multiple contexts introduces indefiniteness as to what these terms actually mean, in the context of the claimed method. The examiner suggests carefully reviewing term selection, in comparison with the specification. For example, it would appear that “preparing synthetic internal standards (IS)” in claim 1 actually refers to “synthetic complexity control internal standards (CC-IS)” as used in the specification. One suggestion for clarification includes:
“preparing a set of synthetic complexity control internal standards (CC-IS) for at least one of said target regions,
wherein each CC-IS comprises the sequence of [[a target region, and
wherein, within the target region a number of adjacent bases (n) of the CC-IS are substituted with all 4 nucleic acid bases (N);”
Further in claim 1, the examiner suggests the following to clarify the “calculating” step, to clarify what the complexity refers to:
“calculating a complexity yield of the NGS library as a ratio between the number of unique CC-IS and the known copy number of the CC-IS in the combined sample; and”
The metes and bounds of the “quality control” step of claim 1 are unclear. In the newly added final step, the method intends to use the complexity yield to “perform quality control” by performing two further calculation steps. It is unclear how these calculations relate to the concept of “quality control” as there are no clear standards, consequences, or determination of “quality” of the original NGS library. The plain meaning of “quality control” is the process of inspecting, testing and evaluating products or services to ensure they meet predefined standards and customer requirements.
With respect to “(i) applying an acceptance criterion comprising a confidence interval established from reference samples to accept or reject the combined sample; and/or”
Limitation (i) fails to particularly point out and distinctly claim how the confidence interval / acceptance criterion is used to accept or reject “the combined sample”. The term “the combined sample” is not clearly the correct item that is being judged, as it appears that it is the complexity of the NGS library that is being judged for quality. (preamble: a method of evaluating the complexity yield of a prepared next generation library…”) It is further unclear how and when the “confidence interval established from reference samples” is generated/ calculated. Reference samples, and their complexity or quality are not clearly obtained or analyzed in claim 1, such that they could be used to compare to any NGS library complexity yield. Nor is it clear what a passing score should be, in reference to the values of the reference samples.
With respect to “(ii) calibrating an amount of the sDNA needed for preparation of a second NGS library to provide an adequate number of unique reads of the one or more endogenous target genes to provide variant allele frequency sensitivity.”
Limitation (ii) fails to particularly point out and distinctly claim how to calculate the calibrated amount required with the information at hand, and fails to provide consequences or actions to be taken as a result of the “quality control” calculation. The second library is not made in a positive active method step. Further it is entirely unclear how any information in claim 1 is to be used to “provide variant allele frequency sensitivity” as there is no assessment of any variant, or invariant alleles in the sample DNA. None of the sequencing, aligning, analyzing or calculating steps assess the sample DNA, the NGS library DNA or the endogenous target region in the NGS library for any variant alleles. No steps are provided for determining “frequency sensitivity”. The examiner suggests deleting the final clause “to provide variant allele frequency sensitivity.”
The term “adequate number of unique reads of the one or more endogenous target genes” in claim 1 is a relative term which renders the claim indefinite. The term “adequate” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is entirely unclear when a number of reads of a target region approaches “adequate”, as the adequacy appears to reside in the ultimate use of the NGS library: what is adequate in one context may not be adequate in another.
The metes and bounds of claim 2, in the context of the amendments to claim 1, are unclear. Claim 2 now appears to modify the “quality control” steps added to claim 1. However, claim 2 does not clearly indicate any standards, consequences, actions or other quality control steps with respect to the sample, “combined sample” or the first NGS library. It is unclear here what a “normal complexity yield” comprises, and on what basis this normal value was calculated.
The metes and bounds of claim 3, in the context of the amendments to claim 1, are unclear. The claim fails to particularly point out and distinctly claim where within claim 1 these steps are to be performed. It would appear these are related to both the “analyzing” step and the “calculating” steps, however, it is not clear how these calculations affect any of the steps of claim 1. How is the number of sDNA target templates in the NGS library affect the determination of quality, or complexity of the NGS library? Claim 1 does not clearly analyze depth of sequencing for the IS or NT aspects required for claim 3. It is further unclear how the “wherein” clause of claim 3 is to be added to amended claim 1, in calibration step (i). Step (i) does not clearly require “the number of sDNA templates in the NGS library”, it does not set forth how that number is to be used in the calibration, nor does it provide how to determine any “quality” of the NGS library based on that number or calculation. Claim 1 does not clearly attempt to distinguish between quality of the sDNA, and quality of the NGS library, making this limitation especially indefinite. The metes and bounds of “independent biochemical depth analysis” is entirely unclear with respect to the method of claim 1, and the quality control values calculated therein.
The metes and bounds of claim 4 are unclear, in that while a theoretical “second NGS library” is contemplated in claim 1, that is an intended use of the quality control calculations, and no actual second library is produced in claim 1, claim 3, or claim 4. Further it is entirely unclear how any information in claim 1, claim 3 or claim 4 is to be used to “provide variant allele frequency sensitivity” as there is no assessment of any variant, or invariant alleles in the sample DNA. None of the sequencing, aligning, analyzing or calculating steps assess the sample DNA, the NGS library DNA or the endogenous target region in the NGS library for any variant alleles. No steps are provided for determining “frequency sensitivity”. The examiner suggests deleting the final clause “to provide variant allele frequency sensitivity.”
The metes and bounds of claim 5, in the context of the amendments to claim 1, are unclear. It would appear that claim 5 modifies the “analyzing” step, however, the recitations in claim 5 would appear to be equally applicable to the reference information, and the sequence read information of the sample, and it is unclear where in amended claim 1 the required information is provided. Claim 1 does not clearly provide “the number of N needed”, “genome equivalence” or how to determine when “N positions are minimized to the degree possible based upon the size of the genome of the sample.” It is further unclear how these elements affect the complexity yield of the NGS library itself, and the newly added “quality control” steps of claim 1.
The metes and bounds of claim 7, in the context of the amendments to claim 1, are unclear. Claim 1 as amended does not clearly identify any differences or substitutions in the nucleotide sequences of the IS, or flanking regions. It is unclear if this is intended to modify the creation of the synthetic IS, or the analysis of the IS present in the NGS library. It is entirely unclear how any identified substitution “facilitates bioinformatics identification of IS sequences.” It is entirely unclear how this modifies the complexity calculation of the NGS library, or the newly added quality control steps.
The metes and bounds of claim 9, in the context of the amendments to claim 1, are unclear. Claim 9 refers to gDNA as the sample, however the sample is identified in claim 1 as sDNA. Further, it is entirely unclear how the “more accurate limit… can be made” based on the number of templates captured in the NGS library. Claim 1 does not clearly identify the number of templates.
The term “more accurate limit” in claim 9 is a relative term which renders the claim indefinite. The term “more accurate limit” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Claim 1 does not identify any limits, to which any more or less accurate calculations could be compared. Further, the phrasing “can be made” renders the entire limitation optional, such that any prior art meeting claim 1, would also meet claim 9.
The metes and bounds of claim 10, in the context of the amendments to claim 1, are unclear. Claim 1 does not clearly determine “the complexity yield which is significantly lower than a previously established normal complexity yield”. This limitation appears to modify claim 2. Further it is entirely unclear what consequences, actions or other quality control steps should be with respect to the sample, “combined sample” or the first NGS library based on “stochastic errors”. It is unclear here what a “normal complexity yield” comprises, and on what basis this normal value was calculated.
The metes and bounds of new claim 14 are unclear with respect to the amendments to claim 1. The claim fails to particularly point out and distinctly claim in step (iii) where the “multiple measurements of the duplication rate” are obtained in claim 1 nor does claim 1 provide any centroid calculations. It is entirely unclear how these measurements of step (iii) are to be used in the quality control steps of claim 1, and it is entirely unclear how these calculations “support a deduplication process” as required. Claim 1 does not clearly provide a deduplication rate or step, other than counting unique IS. This counting of the unique IS does not provide multiple measurements, or any centroid calculations. The claim further fails to point out and distinctly claim how step (iv) is to be integrated into claim 1. Step (iv) refers to downsampling the sequence reads, based on the calculations of step (iii) however, it is unclear what is to be downsampled, how much it is to be downsampled, and it is further unclear how the downsampling affects any of the quality control steps. It is unclear if the downsampling is intended to be of the initial NGS library, or the theoretical second library.
The metes and bounds of the term “complexity control contigs” in newly added claim 15 are entirely unclear. The specification does not provide a clear definition of this term, with respect to what such a sequence is intended to comprise, in carrying out the method. “Complexity-control contigs” does not appear to be a common term of the prior art. As set forth above, the specification only mentions contigs, and complexity control together in the context of Example 3: which identifies that the reference sequence comprised “17 overlapping RNA contigs…” in the context of creating the DNA library. Example 3 does not clearly identify what a “complexity control contig” is intended to comprise. The only other reference to “CC” and “contigs” appears later in Example 3, after sequencing, in the alignment step:
“FASTQ sequence were aligned using BWA mem and a Wuhan SARS-CoV-2 reference sequence (MN908947.3) appended with the SNAQ-SEQ IS and CC contigs. An awk script was used to count IS and NT amplicons, extract the CC degenerate sequences and their flanking bases (positions 5531-5540, and 5753-5807) and count unique complexity sequences (Fig. 1, squares).” (p13).
The limitation added to claim 15, without the SNAQ-SEQ IS, and CC contigs (possibly containing predicted degenerate sequences) appended to a reference sequence, appears to be broader than the disclosure, and it is not clear what, in particular, the CC contigs must comprise to be operable in the claimed methods.
In claim 15, the use of “internal standard” “IS” “unique IS” and “complexity control” seemingly interchangeably in multiple contexts introduces indefiniteness as to what these terms actually mean, in the context of the claimed method. The examiner suggests carefully reviewing term selection, in comparison with the specification. For example, it would appear that “preparing a set of synthetic internal standards (IS)” in claim 1 actually refers to “synthetic complexity control internal standards (CC-IS)” as used in the specification. One suggestion for clarification includes:
“preparing a set of synthetic complexity control internal standards (CC-IS) for at least one of the endogenous target regions,
wherein the internal standards [[ CC-IS comprise the [[region with degenerated bases, and within which a number of adjacent bases (n) of the CC-IS are substituted with all 4 nucleic acid bases (N) [[
Further in claim 15, it is unclear where “altered unique read counts” are obtained within the method. It appears this could be a part of the “deduplication process” performed, however, that recited process has no positive active method steps setting forth how it is to be carried out, nor the alteration of any read counts. The “quality assessment” of claim 15 is unclear in that the claim fails to particularly point out how the quality is assessed, based on the comparison. No conclusions are drawn as to the “deduplication efficiency” as recited in the preamble. This is underscored by new claim 16 adding a further step of “calculating a deduplication efficiency”, which indicates this critical limitation should be a part of claim 15.
The metes and bounds of new claim 16 are entirely unclear with respect to 1) how the calculation of efficiency is “a function of the deduplication quality assessment”. The Quality assessment of claim 14 is not necessarily a calculated value, but a comparison, which could provide a qualitative answer, such as “poor, adequate, excellent”. It is entirely unclear how a function is generated utilizing the breadth of possible “quality assessments” to “calculate deduplication efficiency” as required.
The metes and bounds of new claim 16 are entirely unclear with respect to 2) “detecting method drift when the deduplication efficiency deviates from a pre-established range;” The function of the calculation of efficiency does not clearly provide ranged data, nor does it provide any reference or “pre-established” information. It is entirely unclear what Applicant intends “method drift” to mean, with respect to the sample, the library, or the calculated efficiency. It is unclear which method needs to be adjusted: the experimental method steps, or the bioinformatic analysis steps.
The metes and bounds of new claim 16 are entirely unclear with respect to 3) “and/or adjusting one or more deduplication process parameters and one or more library preparation parameters to minimize loss of sequence complexity and improve variant detection sensitivity,” It is entirely unclear what “process parameters” are to be adjusted, as claim 15 does not recite any particular parameters related to “performing a deduplication process” or “library preparation parameters.” It is unclear how any potential parameter should be adjusted as a result of the method of claim 15, as the “and/or” adds the possibility that neither 1) nor 2) of step 16 are performed prior to 3) “and/or adjusting….” It is entirely unclear how to adjust any potential parameter “to minimize loss of sequence complexity” as “sequence complexity” is not clearly analyzed in claim 15. It is further unclear how one of skill is to determine when the deduplication process should be modified by claim 16, and when the library preparation step should be modified by claim 16.
Further it is entirely unclear how any information in claim 16 is to be used to “improve variant detection sensitivity” as there is no assessment of any variant, or invariant alleles in the sample DNA. None of the sequencing, aligning, analyzing or calculating steps assess the sample DNA, the NGS library DNA or the endogenous target region in the NGS library for any variant alleles. No steps are provided for determining “detection sensitivity”. The examiner suggests deleting the final clause “to improve variant detection sensitivity.”
Further in claim 16, it is unclear whether 4) “and preparing a second NGS library using an adjusted parameter” is linked only to 3) “and/or adjusting”; or whether the second library is prepared after 1) or 2) or 3).
The metes and bounds of new claim 17 are entirely unclear. Claim 17 modifies new claim 15. However, claim 15 does not address stochastic sampling, and it is unclear what step of claim 15 is being modified. It appears this may modify the preparation of the set of internal standards, but duplication and added complexity controls are not provided until the alignment/ deduplication steps. Claim 15 does not clearly provide unique genome sequencing reads for the sDNA sample, as now needed for claim 17.
A broad range or limitation together with a narrow range or limitation that falls within the broad range or limitation (in the same claim) may be considered indefinite if the resulting claim does not clearly set forth the metes and bounds of the patent protection desired. See MPEP § 2173.05(c). In the present instance, claim 17 recites the broad recitation “at least log(x)/log (4)”, and the claim also recites “but preferably 10-fold greater” which is the narrower statement of the range/limitation. The claim(s) are considered indefinite because there is a question or doubt as to whether the feature introduced by such narrower language is (a) merely exemplary of the remainder of the claim, and therefore not required, or (b) a required feature of the claims.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 6 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Claim 6 recites that the complexity yield is calculated by dividing the unique IS by the known copy number. This limitation is already present in amended claim 1, and claim 6 does not further limit that method.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation (BRI) 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.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10 and 14-17 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of mental steps, mathematic concepts, organizing human activity, or a natural law without significantly more.
Applicant is directed to MPEP 2106 for the most current and complete guidelines in the analysis of patent- eligible subject matter. The current MPEP is the primary source for the USPTO’s patent eligibility guidance.
With respect to step (1): YES, the claims are drawn to statutory categories: Processes.
With respect to step (2A) (1): YES, the claims recite an abstract idea, law of nature and/or natural phenomenon. The claims explicitly recite elements that, individually and in combination, constitute one or more judicial exceptions (JE).
Mathematic concepts, Mental Processes or Elements in Addition (EIA) in the claim(s) include:
1. (Currently Amended) A method of evaluating the complexity yield of a prepared next generation sequencing (NGS) library, comprising
(Preamble, identifying a method, and a goal of the method.)
obtaining an amount of sample DNA (sDNA) comprising one or more endogenous target regions genes;
(EIA- Data Gathering- obtaining a sample of DNA, by any means, of any type, and a description of the sample gathered. MPEP 2106.05(g))
preparing a set of synthetic internal standards (IS) for at least one of said target regions with degenerated bases, wherein the internal standards are the sequence of the target gene within which a substitution of a number (n) of adjacent bases with all 4 nucleic acid bases (N) is made;
(EIA- a step related to data gathering, preparing a reagent, and a description of the reagent. MPEP 2106.05(g))
comingling a known copy number of the internal standards with the sDNA sample to create a combined sample;
(EIA- a step related to data gathering, combining a reagent with a sample. MPEP 2106.05(g))
preparing a NGS library from the combined sample for sequencing;
(EIA- data gathering, carrying out steps of creating a DNA library for the purpose of next generation sequencing, the library is prepared in any manner. MPEP 2106.05(g).)
sequencing the combined sample to generate sequence reads;
(EIA- data gathering, performing next generation sequencing to provide sequence read data. MPEP 2106.05(g))
aligning the sequence reads to a reference sequence that includes complexity-control contigs;
(Mental process: observing a sequence read, comparing it to a reference sequence dataset, making a judgement as to whether they align, and a description of the reference sequence. MPEP 2106.04(a)(2) section III).
analyzing sequencing data generated from the sequence reads to measure a number of unique reads corresponding to the synthetic internal standards (unique IS) and calculating a complexity yield as a ratio between the unique IS and the known copy number of the synthetic internal standards in the combined sample; and
(Mathematic Concept of counting unique reads meeting a condition, and using the number of unique reads, and the known copy number from above, to calculate a yield. MPEP 2106.05(a)(2) Section I.)
using the calculated complexity yield to perform quality control by
(i) applying an acceptance criterion comprising a confidence interval established from reference samples to accept or reject the combined sample; and/or
(Mathematic concept of a data value falling within a confidence interval; alternatively, a mental process of observing a data value, comparing it to a confidence interval, and making a judgement as to whether it falls within the interval. MPEP 2106.05(a)(2) I and III).
(ii) calibrating an amount of the sDNA needed for preparation of a second NGS library to provide an adequate number of unique reads of the one or more endogenous target genes to provide variant allele frequency sensitivity.
(Mathematic concept of calculating an amount of sample needed to meet a condition. MPEP 2106.04(a)(2) I. Note: the second library is not actually created, but is the intended use of the calibrated amount.)
2. (Mental process, in a computing environment, of comparing data values, and describing what the comparison could mean.)
3.(Mathematic concept of calculation of sDNA target templates, and intended use of this value in “independent biochemical depth analysis” for “a second NGS library.”)
4. (Mental step in a computing environment, of observing an inadequate amount, followed by data annotation or adjustment.)
5. (Mathematic concept of calculating the number of unique synthetic IS.)
6. (Mathematic concept of calculating the complexity yield.)
7. (EIA- data gathering limitation modifying how the substitution is made, and an intended use of the substitution)
8. (EIA- data gathering limitations modifying the preparation of the library using known procedures.)
9. (Mathematic concept of counting the number of templates captured in the library.)
10. (Mental step in a computing environment, of observing a low complexity yield, and determining what may have caused it)
14.(New) The method of claim 1, wherein the method further comprises using the calculated complexity yield to (iii) support a deduplication process on the sequence reads by obtaining multiple measurements of the duplication rate of each unique internal-standard read count, combining the multiple measurements by one or more centroid calculation, and(iv) down sample the sequence reads based on a combined complexity control duplication rate obtained from step (iii).
(Mathematic concept of counting, calculating, measuring values and adjusting data.)
15. (New) A method of evaluating deduplication efficiency of a next generation sequencing (NGS) library, comprising:
(Preamble, stating a method, and the goal of the method.)
obtaining sample DNA (sDNA) comprising one or more endogenous target regions;
(EIA- a step of data gathering, and a description of the sample; MPEP 2106.05(g).)
preparing a set of synthetic internal standards for at least one of the endogenous target regions, wherein the synthetic internal standards are a sequence of the endogenous target gene with degenerated bases and within which a substitution of a number (n) of adjacent bases with all 4 nucleic acid bases (N) is made;
(EIA- a step related to data gathering: preparing a reagent, and a description of the reagent. MPEP 2106.05(g))
comingling a known copy number of the synthetic internal standards with the sDNA to create a combined sample;
(EIA- a step related to data gathering: combining reagents MPEP 2106.05(g).)
preparing an NGS library from the combined sample and sequencing the combined sample to generate sequence reads;
(EIA- routine data gathering steps, preparing a library, and sequencing the library to generate sequence read data, by any means. MPEP 2106.05(g).)
aligning the sequence reads to a reference sequence that includes complexity-control contigs;
(Mental process: observing a sequence read, comparing it to a reference sequence dataset, making a judgement as to whether they align, and a description of the reference sequence. MPEP 2106.04(a)(2) section III).
performing a deduplication process on the sequence reads;
(Mental process and mathematic concepts: deduplication is a process of observation of numbers of sequence reads, judging whether the number may be incorrect, or reflect duplication in the library preparation process, and mathematically adjusting that number based on various factors. MPEP 2106.04(a)(2) I and III)
performing a deduplication quality assessment by comparing altered unique read counts before and after the deduplication process.
(Mental process of observation and comparison of altered counts, and judgement as to an aspect of quality. MPEP 2106.04(a)(2)(III).)
16. (New) The method of claim 15, wherein the method further comprises calculating a deduplication efficiency as a function of the deduplication quality assessment; detecting method drift when the deduplication efficiency deviates from a pre-established range; and/or adjusting one or more deduplication process parameters and one or more library preparation parameters to minimize loss of sequence complexity and improve variant detection sensitivity, and preparing a second NGS library using an adjusted parameter.
(Mathematic concepts and mental processes, further calculations based on the quality, observing method drift based on calculations, (MPEP 2106.04(a)(2) II, III) and EIA, a step of preparing a second library. (MPEP 2106.05(g).)
17. (New) The method of claim 15, wherein minimizing the stochastic sampling duplication of added complexity controls, the number of N needed for the sDNA sample is at least log (X)/log(4), but preferably 10-fold greater, wherein X is the unique genome sequencing reads for the sDNA sample.
(Mathematic concept- further calculations performed. MPEP 2106.04(a)(2) I.)
With respect to step 2A (2): NO, the claims do not integrate the JE into a practical application (MPEP 2106.04(d)):
“Examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more of the considerations introduced in subsection I supra, and discussed in more detail in MPEP §§ 2106.04(d)(1), 2106.04(d)(2), 2106.05(a) through (c) and 2106.05(e) through (h).”
Claim(s) 1, 7, 8, 15-16 recite the additional non-abstract element(s) of data gathering, or a description of the data gathered.
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data necessary to carry out the JE. MPEP 2106.05(g).
The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. MPEP 2106.05(g).
The data gathering steps constitute a general link to a technological environment: the trait prediction methods are intended to be applied to plant populations. (MPEP 2106.05(h), citing Mayo, Bilski, electric Power Group, Genetic Techs Ltd v Merial LLC.)
The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception to provide integration into a practical application. (MPEP 2106.05(g) citing Mayo, PerkinElmer, Inc. v. Interna Ltd, Intellectual Ventures LLC v. Erie Indem. Co., Electric Power Group LLC v. Alstom S.A.).
NOTE: Claim(s) 17 recite the additional non-abstract element (EIA) of a creating a second library.
This claim, if clarified to be clear that the second library is made, regardless of the 3 other steps performed in claim 17, would be a practical application of the JE.
Currently, due to the indefiniteness of claim 17, it is unclear whether the claim always results in the preparation of a second library.
Dependent claim(s) 2-6, 9-10, 16, 17 recite(s) an abstract limitation to the JE reciting additional mathematic concepts, or mental processes. Additional abstract limitations cannot provide a practical application of the JE as they are a part of that JE.
In combination, the limitations of data gathering, for the purpose of carrying out the JE, using a general-purpose computer merely provide extra-solution activity, and fail to integrate the JE into a practical application.
With respect to step 2B: NO, the claims do not recite a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05).
“… an "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim, as a whole, amounts to significantly more than the judicial exception itself. Alice Corp…”
With respect to claim(s) 1, 7, 8, 15-16: The limitation(s) identified above as non-abstract elements (EIA) related to data gathering do not rise to the level of significantly more than the judicial exception.
Blomquist et al (2013) provides steps of obtaining sample DNA, for example at page 3, Fig 1A. Blomquist provides steps of creating synthetic internal standards meeting the requirements of the limitation, for example at pages 3-4, Fig 1, 2. Blomquist provides combining the sDNA and the IS for example in Figs 1 and 2, and pages 3-5. Blomquist provides preparing a library, and sequencing the library at pages 5-6 and Figs 1-3. Substitution, and amplicon capture are provided as meeting claims 7 and 8.
Blomquist (2015) provides steps of obtaining sample DNA, at page 31, Methods, Sample preparation. Blomquist provides steps of creating synthetic internal standards meeting the requirements of the limitation, at page 31, hypothesis 1 and hypothesis 2, and in the methods section, section 2.3. Blomquist provides combining synthetic IS with sDNA in known proportions in the methods section, section 2.3. Blomquist provides creating a NGS library using the combined sample, and sequencing the library in the method section, p32, section 2.3. Blomquist provides amplification of target regions (amplicon capture).
Craig et al. (2019) provides steps of obtaining sample DNA at page 3, Methods. Craig provides steps of creating internal standards and mixing them with the sDNA in the methods section, pages 3-4. Craig provides creating a NGS library from the combined sample, and sequencing that library at pages 5-6. Craig provides amplicon capture PCR.
Yeo (2016) provides steps of obtaining sample DNA, at page S53, Methods section. Yeo provides steps of creating internal standards and mixing them with the sDNA at page s53, Methods. Yeo provides preparing a library and sequencing the library at ps53, Methods. Yeo provides unique substitution as required for dependent claim 7. Yeo provides amplicon capture as required to meet claim 8.
SEQC/MAQC-III Consortium (2014) provides sample DNA in the method section. SEQC provides steps of creating internal standards and mixing them with sample DNA in the methods section. SEQC provides creating NGS libraries from the mixed samples, and sequencing those libraries in the methods section. SEQC performs both RNA-seq and qPCR as amplification. See Results, study design, Fig 1, and the like.
Morrison (US2015/0291999 A1) provides obtaining sample DNA at [0012, 0023, 0093]. Morrison provides adding targeted internal standards to the sDNA at [0020-0021, 0047, 0048, 0081-0083]. Morrison (US2015/0267260 A1) provides obtaining sample DNA at [0006, 0010, 0022]. Morrison provides adding internal standards to the sDNA at [0018-0020, 0032, 0044-0047, 0052, 0075-0084]. The purpose of Morrison ‘260 is to reduce a difference in yield between amplification reactions. [0069, 0086-0088]
Zheng (US10,385,475 B2) provides obtaining sDNA (col 6-7), preparing oligonucleotides with insertions of wildcard or N bases adjacent to the target (col 5-6) preparing a low complexity library (col 1-2, col 9-10), and sequencing the library (Col 3, col 11).
These elements meet the BRI of the identified data gathering limitations, individually and in combination. As such, the prior art recognizes that this data gathering element is routine, well understood and conventional in the art. MPEP 2106.05(d): “If, however, the additional element (or combination of elements) is no more than well-understood, routine, conventional activities previously known to the industry, which is recited at a high level of generality, then this consideration does not favor eligibility.”
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data necessary to carry out the JE. MPEP 2106.05(g).
The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. MPEP 2106.05(g).
The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception to provide an inventive concept. (MPEP 2106.05(g) citing Mayo, PerkinElmer, Inc. v. Interna Ltd, Intellectual Ventures LLC v. Erie Indem. Co., Electric Power Group LLC v. Alstom S.A.)
The data gathering steps constitute a general link to a technological environment: the trait prediction methods are intended to be applied to plant populations. (MPEP 2106.05(h), citing Mayo, Bilski, electric Power Group, Genetic Techs Ltd v Merial LLC.)
Therefore, simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more (as discussed in Alice Corp.,).
Dependent claim(s) 2-6, 9-10, 16, 17 each recite a limitation requiring additional mathematic concepts or mental processes. Additional abstract limitations cannot provide significantly more than the JE as they are a part of that JE (MPEP 2106.05).
In combination, the data gathering steps providing the information required to be acted upon by the JE, performed in a generic computer or generic computing environment fail to rise to the level of significantly more than that JE. The data gathering steps provide the data for the JE, which is carried out by the general-purpose computers. No non-routine step or element has clearly been identified.
The claims have all been examined to identify the presence of one or more judicial exceptions. Each additional limitation in the claims has been addressed, alone and in combination, to determine whether the additional limitations integrate the judicial exception into a practical application. Each additional limitation in the claims has been addressed, alone and in combination, to determine whether those additional limitations provide an inventive concept which provides significantly more than those exceptions. For these reasons, the claims, when the limitations are considered individually and as a whole, are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Newly cited: Blomquist et al. (2015) Control for stochastic sampling variation and qualitative sequencing error in next generation sequencing. Biomolecular Detection and Quantification. Vol 5, p30-37, and some supplemental material.
Craig et al. (2019) Technical advance in targeted NGS analysis enables identification of lung cancer risk associated low frequency TP53, PIK3CA, and BRAF mutations in airway epithelial cells. BMC Cancer, vol 19:1081, 14 pages.
SEQC/MACQ-III Consortium (2014) A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the sequencing Quality control consortium. Nature Biotechnology, vol 32 no 9, p903-914 and online methods.
Applicant’s arguments:
Applicant’s arguments have been carefully considered, but are not completely persuasive.
With respect to the argument that the methods provide “engineered, instrument bound steps and concrete QC actions” it is noted that no particular instruments are required for either independent claim, nor the dependent claims. As noted above, the preparation of a second library as a result of the JE are either an intended use of the result of the JE, or it is unclear if the preparation of the second library concretely occurs in a positive active method step. Were both independent claims to be amended to clearly recite the preparation of the second library, as adjusted by some element of the JE, that could incorporate the JE into a practical application depending on the form of the amendment.
With respect to the steps related to data gathering, it remains unclear whether the preparation of the internal standards is materially different from the prior art known processes cited. The steps of preparing the IS, with a target region, some number of bases, and some number of added N appear to be fully disclosed by the prior art cited. If the preparation of the IS, or CC-IS is a non-routine step, which materially alters the library generated, and the resulting data, that may be enough to incorporate the JE into a practical application, as in the CellzDirect decision, depending on how that limitation is amended to specifically point out the non-routine elements/steps.
With respect to the arguments related to the QC steps amended into claim 1, the step of “accept or reject” is a step of judgement, a mental process, and not a physical step of throwing away a sample. Applicant’s various arguments regarding the dependent claims providing critical, or improvement providing information, these arguments are not persuasive. These claims provide additional abstract ideas in addition to the JE identified in the independent claims. Additional abstract ideas cannot provide a practical application, or provide significantly more, as they are a part of the judicial exception.
Further, with respect to the arguments regarding the alleged improvement, it is unclear that the independent claims recite all the necessary and sufficient steps required to achieve that improvement. MPEP 2106.05(a): “An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. McRO, 837 F.3d at 1314-15, 120 USPQ2d at 1102- 03; DDR Holdings, 773F.3d at 1259, 113 USPQ2d at 1107.”
The MPEP sets forth that “if the examiner concludes the disclosed invention does not improve technology, the burden shifts to applicant to provide persuasive arguments supported by any necessary evidence to demonstrate that one of ordinary skill in the art would understand that the disclosed invention improves technology. Any such evidence submitted under 37 CFR 1.132 must establish what the specification would convey to one of ordinary skill in the art and cannot be used to supplement the specification.” Applicant’s arguments cannot take the place of evidence.
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, 6-10 is/are rejected under 35 U.S.C. 102a1 as being anticipated by Craig (2019).
Craig et al. (2019) Technical advance in targeted NGS analysis enables identification of lung cancer risk associated low frequency TP53, PIK3CA, and BRAF mutations in airway epithelial cells. BMC Cancer, vol 19:1081, 14 pages, and some supplemental information.
Craig et al. is directed to the design and use of a set of synthetic DNA internal standards, added to sample DNA prior to library generation. SNAQ-SEQ (Standardized Nucleic Acid Quantification for SEQuencing) was shown to be able to measure low frequency mutations, increasing the sensitivity and selectivity of certain cancer screening tests, and provide a reproducible measure of technical error, and assessing quality and complexity of the library.
With respect to claim 1 and “A method of evaluating the complexity yield of a prepared next generation sequencing (NGS) library, comprising
obtaining an amount of sample DNA (sDNA) comprising one or more endogenous target regions;”
Craig obtains samples of DNA from patients as set forth at p3, Specimen acquisition. Genomic DNA was extracted, and quantified. gDNA contains endogenous target regions, as it encompasses the whole genome. Craig selects seven endogenous regions, as set forth at p3-4, “recently reported by The Cancer Genome Atlas (TCGA) project to be the most commonly mutated in non-small cell lung cancer.”
With respect to claim 1 and “preparing a set of synthetic internal standards (IS) for at least one of said target regions with degenerated bases, wherein the internal standards are the sequence of the target gene within which a substitution of a number (n) of adjacent bases with all 4 nucleic acid bases (N) is made;”
Craig prepares synthetic internal standards, for the seven target regions. P4, Reagent synthesis.
“Primers and synthetic internal standard mixtures were prepared for SNAQ-SEQ at Accugenomics, Inc. (Wilmington, NC) for each of the selected targets (Additional file 2: Table S2).”
The competitive synthetic DNA internal standards were designed according to p4, “synthetic internal standard mixture preparation” and include degenerate or specific dinucleotide substitution mutations relative to the native target sequence over the length of the target. This appears to meet the BRI of this limitation.
“Competitive synthetic DNA internal standard (IS) molecules for TCGA targets described above were designed with known dinucleotide substitution mutations relative to target analyte native template (NT) every 50 bases. This enabled separation of NT and IS reads during postsequencing data processing of either PCR amplicon libraries used in this study, or of random fragment hybrid capture libraries in other ongoing studies not reported here.” P4
With respect to claim 1 and “comingling a known copy number of the internal standards with the sDNA sample to create a combined sample;
Craig comingles a known mix of known CN of IS with a known mix of sDNA, as set forth at p4-5.
“An internal standard mixture (ISM) containing equal concentrations (per genome copy) of each linearized target analyte IS molecule was prepared.”
“For each subject, an aliquot of AEC DNA was combined with equal genome copies of ISM to control for nucleotide-specific substitution error occurring during library preparation and/or sequencing.”
Craig further barcodes the amplified products, as set forth at p5. Craig pools samples at approximately a 1:1 ratio “to optimize the percentage of sequencing reads that each library would eventually receive.” P5.
With respect to claim 1 and “preparing a NGS library from the combined sample for sequencing;
sequencing the combined sample to generate sequence reads;”
Craig creates the libraries, and sequences the libraries of the combined samples to generate sequence reads as set forth at page 5.
“The combined sequencing library was purified using gel electrophoresis on a 2% w/v agarose gel… The purified sequencing library was sent to the University of Michigan Genomics core facility for Next Generation Sequencing on an Illumina NextSeq 550 sequencing instrument.”
With respect to claim 1 and “aligning the sequence reads to a reference sequence that includes complexity-control contigs;”
Craig provides reference data comprising the endogenous (NT) target regions, and the IS sequences, which are used by Craig in the alignment step. The presence of the IS sequences meets the BRI of the “complexity control contig” which represent a sequence differing from the NT, to which only IS related sequences will match during the mapping/ alignment process. p5.
“FASTQ data files generated by the University of Michigan Genomics core facility were processed using a custom Perl script to separate the internal standard (IS) and native template (NT) reads into separate NT and IS files (Additional file 7: File 1), followed by parallel analysis using the Qiagen CLC Genomics Workbench 12 software suite for quality-trimming, alignment, and variant calling (Additional file 7: File 1).”
Further details are provided as to the reference data, comprising complexity control contigs is set forth in Additional File 7:
“# Introduction
# Spike-In Separation Toolbox (SIST) is developed for separate Accugenomics sequencing spike
#in controls (IS reads) from original sample (NT reads).
# The separation is based on the unique characteristics of spike-in controls, which contains
#several di-nucleotides inside the target region.
#
# NOTE: SIST produces IS and NT sequence read files. Downstream pipeline analysis should use
# the control reference file (e.g., hg19_IS) when
# processing IS files and regular native reference genome when processing NT files.”
“# #### Updates: ####
# 04/11/2019: Added ability to use file or paths with space in name.
# Reduced score for bases with low qscore.
# Provide 'strict=true' option to partition IS and NT recombinant reads into SUS bin.
# Until more detailed study is performed, recommend using regular reference genome
#(e.g., hg19), and create control reference genome substituting control bases (e.g., hg19_IS).#”
“# 08/02/2018: provide an option to use customized spike-in reference. (Ver. 1.10 -> 1.20)”
With respect to claim 1 and “analyzing sequencing data generated from the sequence reads to measure a number of unique reads corresponding to the synthetic internal standards (unique IS) and calculating a complexity yield as a ratio between the unique IS and the known copy number of the synthetic internal standards in the combined sample; and”
Craig analyzes the sequence read data, as set forth at p5-6. The pipeline of Craig is set forth in Additional file 7. The sequence read data is split, after alignment to the reference containing IS sequences, or NT sequences. The counts/target are identified for both IS and NT pipelines. Craig calculates ratios of the sequence reads mapped to IS sequences and the known input copy number of IS, as set forth in File 7, and p5-6.
With respect to claim 1 and “using the calculated complexity yield to perform quality control by
(i) applying an acceptance criterion comprising a confidence interval established from reference samples to accept or reject the combined sample; and/or
(ii) calibrating an amount of the sDNA needed for preparation of a second NGS library to provide an adequate number of unique reads of the one or more endogenous target genes to provide variant allele frequency sensitivity.
Craig provides acceptance criterion, including a confidence interval established from reference samples, to accept or reject the results of the sequence analysis pipeline, meeting (i). As the second condition is not required, Craig anticipates the invention. Note: Craig does analyze variant allele frequency sensitivity at length, at pages 5-6, and the Results.
With respect to claim 2, comparison of IS scores and REF scores between the NGS library and normal yield expectancies is set forth in additional file 7.
With respect to claim 6, this limitation is met at the same place as for claim 1.
With respect to claim 7, base changes, such as those set forth for primer barcoding, et al, “facilitate bioinformatics identification of IS sequences…” as required.
With respect to claim 8, Craig provides amplicon capture library preparation.
With respect to claim 9, accuracy is discussed by Craig at length in the Results section. The conditional phrasing of this limitation does not require higher accuracy.
With respect to claim 10, Craig discloses that a high error rate is related to stochastic errors, throughout.
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.
Claim(s) s 3-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Craig (2019) as applied to claims 1-2, 6-10 above, in view of Yeo (2016).
Craig et al. (2019) Technical advance in targeted NGS analysis enables identification of lung cancer risk associated low frequency TP53, PIK3CA, and BRAF mutations in airway epithelial cells. BMC Cancer, vol 19:1081, 14 pages, and some supplemental information.
Yeo (2016) Control for stochastic sampling variation and qualitative sequencing error in next generation sequencing analysis of KRAS actionable mutations. Journal of Thoracic Oncoloy, Vol 11, no 25, pS53-s54. Of record, PTO-892.
Claims 3-4 are directed to steps for calculating the number of sDNA target templates, and adjusting reads to provide variant allele frequency.
As set forth above, Craig obtains sDNA, prepares a set of synthetic internal standards, comingles a known copy number of IS with the sDNA, amplifies the combined sample, creates a library, sequences the library, and aligns the sequence reads to reference sequences which include IS complexity control contigs.
Craig provides with respect to claim 3, sDNA target templates calculated using the number of IS reads, and the number of NT reads, providing independent biochemical depth analysis for the target regions in the sDNA, as set forth in the Analysis and Results sections. See also Files 7 and 8.
Craig does not specifically provide multiplying the ratios.
Yeo et al. teaches the relevant variables to derive a formula capable of finding the limit to lower
detection of a target gene (Conclusion). "The limit to lower detection of KRAS mutation fraction is
determined by a) number of amplifiable mutated copies loaded into library preparation, b) number of
library products loaded into sequencer, c) ratio of sequencing space/sample, and d) frequency of
polymerase error at the nucleotide site bearing the mutation. In targeted NGS, synthetic competitive
IS control for stochastic sampling at input of both target into library preparation and of target library
product into sequencer, enable reduced sequencing space requirement, and control for qualitative
errors generated during library preparation and sequencing. These controls enable accurate clinical
diagnostic reporting of confidence limits and limit of detection for copy number measurement, and
reduce sequencing space required for analysis."
It would have been further prima facie obvious to have used the information and variables
provided by Yeo in the methods of determining or evaluating a level of complexity of a polynucleotide
library, such as those provided by Craig. Yeo taught that the use of synthetic IS tags or molecules in library preparation provide important data and parameters for the evaluation of the level of a target, and the level of complexity of a polynucleotide library containing the target. One of skill would have had a reasonable expectation of success at arriving at the limitation of claim 3.
Claim 4 is directed to the method of Claim 1, wherein the amount of sDNA in the second NGS
library is adjusted to provide an adequate number of unique reads of one or more endogenous target genes to provide variant allele frequency sensitivity.
Yeo et al. teaches the existence of a formula for the limit to lower detection of a target gene for
the purpose of increasing sensitivity to particular variant alleles (Conclusion). It would have been further obvious to one of ordinary skill in the art before the effective filing date to have combined the method of measuring library complexity using synthetic internal standards as disclosed by Craig with the relevant variables to determine a lower limit of detection for a particular target gene outlined in Yeo et al. because this would allow a researcher to optimize the library preparation process based on the characteristics of the target gene thereby allowing for reduction of various types of bias and error ( Yeo et al. Background) One would have a reasonable expectation of success because Craig et al. shows the use of synthetic internal standards meeting the BRI of the claims and a method for measuring library complexity that employs a polynucleotide spike in approach and Yeo et al. shows the relevant variables to derive a formula capable of finding the limit to lower detection of a target gene. Such a combination is merely a "predictable use of prior art elements according to their
established functions." KSR Int'l 7, 127 S. Ct. at 1740.
Claim(s) 14-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Craig (2019) as applied to claims 1-2, 6-10 above, in view of Ebbert (2016).
Craig et al. (2019) Technical advance in targeted NGS analysis enables identification of lung cancer risk associated low frequency TP53, PIK3CA, and BRAF mutations in airway epithelial cells. BMC Cancer, vol 19:1081, 14 pages, and some supplemental information.
Ebbert et al (2016) Evaluating the necessity of PCR duplicate removal from next-generation sequencing data and a comparison of approaches. BMC Bioinformatics, vol 17(suppl 7): 239, 10 pages. Of record, PTO-892.
Claim 14 depends from claim 1, and utilizes the calculated information to support deduplication of sequence read data, and downsample sequence reads.
Claims 15-17 are drawn to a slightly different method than claim 1, where the use of synthetic internal standards is applied to “evaluating deduplication efficiency” of an NGS library.
As set forth above, Craig obtains sDNA, prepares a set of synthetic internal standards, comingles a known copy number of IS with the sDNA, amplifies the combined sample, creates a library, sequences the library, and aligns the sequence reads to reference sequences which include IS complexity control contigs. Craig indicates that duplicate removal may be a desired process of the pipeline, as set forth in additional file 7, p7.
“#Sort FASTQ file into native: control: suspect.
#best fit of fragments to ISREF or NTREF (NT+ IS counts) because alignment better.
##native #:0:# or #:0:0 or 0:0:0 or 0:0:#
#control 0:#:# or 0:#:0
#suspicious #:#:0, qscore and count of each will resolve this.
#possible improvement: track POS instead +1, allows duplicate removal thereby read overlap
sites don't get double counted.”
Craig does not specifically add deduplication or duplicate removal in their computerized pipeline. However, as shown by Ebbert, deduplication of sequence reads is a known process commonly performed in the analysis of sequence read data.
Ebbert teaches a method of determining deduplication efficiency (Methods section duplicate removal) in the analysis of sequence read data. Ebbert teaches that the
“Analyzing next-generation sequencing data is difficult because datasets are large, second generation sequencing platforms have high error rates, and because each position in the target genome (exome, transcriptome, etc.) is sequenced multiple times. Given these challenges, numerous bioinformatic algorithms have been developed to analyze these data. These algorithms aim to find an appropriate balance between data loss, errors, analysis time, and memory footprint… One step in many pipelines is PCR duplicate removal, where PCR duplicates arise from multiple PCR products from the same template molecule binding on the flowcell. These are often removed because there is concern they can lead to false positive variant calls. Picard (MarkDuplicates) and SAMTools (rmdup) are the two main softwares used for PCR duplicate removal.”
In a process where false positive counts of a target gene are to be avoided, deduplication is a routine step in the workflow for analyzing sequence read data.
“PCR duplicates are sequence reads that result from sequencing two or more copies of the exact same DNA fragment, which, at worst, may contain erroneous mutations introduced during PCR amplification, or, at the very least, make the occurrence of the allele(s) sequenced in duplicates appear proportionately more often than it should compared to the other allele (assuming a non-haploid organism) … These duplicates occur for two reasons: (1) we cannot control exactly which sequences from the pool of PCR products hybridize to the flowcell, and (2) not all of the original DNA molecules are amplified without bias (PCR amplification bias). PCR amplification bias and increasing the number of PCR cycles both increase the likelihood of PCR duplicates during sequencing” P2.
“Many analysis pipelines remove PCR duplicates to mitigate potential biases on variant calling algorithms. For example, a large number of PCR duplicates containing an amplification-induced error may cause a variant calling algorithm to misidentify the error as a true variant. Several programs exist to remove or mark PCR duplicates (e.g. SEAL [8], elPrep [9], FastUniq [10], etc.), but in this work
we focus on the two most commonly used approaches: Picard MarkDuplicates (http:// broadinstitute.github.io/ picard/) and SAMTools rmdup [11, 12].
SAMTools and Picard use similar approaches for duplicate marking or removal, but with some differences. SAMTools (rmdup) identifies PCR duplicates by identifying pairs of reads where multiple reads align to the same exact start position in the genome, and the reverse read on the 3’ end maps at the exact same location (i.e. external mapping coordinates are identical) … There will also be unexpected results if multiple libraries are present in the same BAM file since rmdup assumes all reads in the BAM file originated from the same library [11, 12]. Picard (MarkDuplicates) is similar to rmdup. MarkDuplicates identifies read pairs with the same orientation that have the exact same 5′ start position in the mapping. It takes into account clipping on the 5’ end of the read and makes calculations based on where the 5’ start position would be if the entire read had mapped to the reference. In contrast to rmdup, MarkDuplicates handles interchromosomal read pairs, and considers the library for each read pair and keeps a read pair from each library. MarkDuplicates also does not remove reads, but sets the SAM flag 1024 for all but the best read pair. The best read pair is the read pair with the highest sum of base qualities with Q≥ 15 (http:// broadinstitute.github.io/ picard/).” P2
Ebbert uses the analysis of the quality of the library, to accept or reject a sample, as set forth at p2: “During the analysis process, one sample was removed due to low quality data and was not replaced.”
The deduplication pipelines of Ebbert, using SAMTools or Picard are set forth beginning at page 3.
“Three versions of each BAM file in our dataset were generated: (1) a BAM where PCR duplicates were left intact, (2) a BAM where PCR duplicates were removed using SAMTools (rmdup),
and (3) a BAM where PCR duplicates were marked (and subsequently ignored) using Picard (MarkDuplicates). Subsequent steps are identical in each pipeline and all steps were performed with the Genome Analysis Toolkit (GATK, version 3.2). Following duplicate removal (or not) we refined the mappings using GATK’s IndelRealigner and BaseRecalibrator (BQSR), and joint called/refined variants using the HaplotypeCaller and variant quality score recalibration (VQSR).”
A variety of statistics were compared between SAMTools, Picard, and no-duplicate-removal.
“We calculated the percentage of duplicates removed by both Picard MarkDuplicates and SAMTools rmdup to quantify approximately how many reads were considered duplicates by both softwares, by comparing the number of reads in the BAM files before and after duplicate marking/removal. For MarkDuplicates, specifically, we counted the number of reads not marked as duplicates.” (p4-5). See also Table 2.
“The number of duplicates identified by both softwares was comparable, though Picard removed more reads on average. The average percentage of reads marked by Picard was 1.8 % and the average removed by SAMTools was 1.1 %.” P7
The effects of duplicate removal on variant identification and annotation are discussed. P5-6. The effects of duplicate removal on the study of “clinically important genes” is discussed beginning at page 6.
In KSR Int 'l v. Teleflex, the Supreme Court, in rejecting the rigid application of the teaching, suggestion, and motivation test by the Federal Circuit, indicated that “The principles underlying [earlier] cases are instructive when the question is whether a patent claiming the combination of elements of prior art is obvious. When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.” KSR Int'l v. Teleflex lnc., 127 S. Ct. 1727, 1740 (2007).
Applying the KSR standard of obviousness to Craig and Ebbert we conclude that the combination of the use of internal standards to determine quality and complexity of an NGS library as taught by Craig, with the routine deduplication processes discussed by Ebbert, represents a combination of known elements which would have yielded the predictable result of a sequence read set which has less noise due to artifactual amplification of targets. The use of Picard or another duplicate removal program as taught by Ebbert in this combination would further serve to achieve the predictable result of marking but keeping duplicate reads for further analysis, so that no data is lost through the deduplication. Ebbert provided sources for deduplication software, and typical parameter selection for analysis of NGS library sequence read data. One of skill would have looked to a program such as Picard or SAMTools as disclosed by Ebbert, as Craig suggests that downstream duplicate removal is a desired process, to be incorporated into the pipeline. Such a combination is merely a "predictable use of prior art elements according to their established functions." KSR Int’l 7, 127 S. Ct. at 1740.
Conclusion
Applicant is reminded of their duty to disclose.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Accugenomics SNAQ-SEQ related webpages: overview, white-paper, slides and publications (publication dates from 2020-2024, downloaded 2026). Accugenomics.com.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARY K ZEMAN whose telephone number is 5712720723. The examiner can normally be reached on 8am-2pm M-F. Email may be sent to mary.zeman@uspto.gov if the appropriate permissions have been filed.
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/MARY K ZEMAN/ Primary Examiner, Art Unit 1686
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