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 .
Information Disclosure Statement
The IDS filed 9/19/2023 and 6/26/2026 have been considered by the Examiner.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged. Priority of a 371 of PCT/CN2022/095696 filed 05/27/2022 is acknowledged.
Claim Status
Claims 10 and 12 are cancelled.
Claims 1-9, 11 and 13-22 are pending and are examined on the merits.
Claim Objections
Claim 13 is objected to because of the following informalities: claim 13 recites “a non-transient computer-readable medium”, which should read as “a non-transitory computer-readable medium”. Claim 22 has a similar problem. Appropriate correction is required.
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 1-9, 11 and 13-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1: Process, Machine, Manufacture or Composition
Claims 1-9 are to a method for identifying a source primer of a nonspecific amplification sequence. So a process.
Claims 11 and 14-21 are to a computing processing device. So a machine or a manufacturer.
Claims 13 and 22 are to a non-transient computer-readable medium. So a machine-.
Step 2A Prong One: Identification of Abstract Ideas
The claim(s) recite(s):
Aligning the amplification sequence data to the source gene sequence data, and taking the amplification sequence data that does not match the source gene sequence data as nonspecific amplification sequence data; and
--This step recites mapping of two sequences, followed by a judgement (specific amplification or nonspecific amplification). Under a broadest reasonable interpretation (BRI) and at its simplest embodiment, the comparison of two piece of sequences can be accomplished in the human mind. Therefore, this step equates to an abstract idea of mental processes.
Aligning the nonspecific amplification sequence data to the primer sequence data, and taking a primer with the primer sequence data being matched with the nonspecific amplification sequence data as an amplification source primer of the nonspecific amplification sequence.
--This step recites mapping of two sequences, followed by a judgement (amplification source or not). Under a broadest reasonable interpretation (BRI) and at its simplest embodiment, the comparison of two piece of sequences can be accomplished in the human mind. Therefore, this step equates to an abstract idea of mental processes.
Dependent claims further describe different aspects of sequence data analysis, as well as the sequence sources.
Step 2A Prong Two: Consideration of Practical Application
The claims result in a process of Aligning the nonspecific amplification sequence data to the primer sequence data, and taking a primer with the primer sequence data being matched with the nonspecific amplification sequence data as an amplification source primer of the nonspecific amplification sequence, which is directed to an abstract idea of mental processes. The claims do not recite any additional elements that integrate the abstract idea/judicial exception into a practical application.
This judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than
a drafting effort designed to monopolize the exception.
Step 2B: Consideration of Additional Elements and Significantly More
The claimed method also recites "additional elements" that are not limitations drawn to an abstract idea. The recited additional elements are drawn to:
Acquiring amplification sequence data of an amplified gene obtained by primer amplification of a target gene fragment, source gene sequence data of a source gene to which the target gene fragment belongs, and primer sequence data used in the primer amplification (claim 1);
Acquiring the amplification sequence data of the amplified gene obtained by primer amplification of the target gene fragment comprises: acquiring raw data obtained by primer amplification of the gene fragment (claims 2, 14, and 22);
A computing processing device, comprising: a memory with computer-readable code stored therein; one or more processors (claim 11);
A non-transient computer-readable medium (claim 13).
The claims do not include additional elements that are sufficient to amount of significantly more than the judicial exception because it is routine and conventional to perform the acts of acquiring sequence data. Other elements of the method include an apparatus/A computing processing device/A non-transient computer-readable medium, which is a recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea recited in the instantly presented claims into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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.
Claims 1, 4-5, 11, 13 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over BEAN et. al.: (“Process for aligning targeted nucleic acid sequencing data,” US20190325990A1, published Oct. 24, 2019; filed Jan. 7, 2019. Newly cited).
Claim 1 is “a method for identifying a source primer of a nonspecific amplification sequence”. Regarding claim 1, BEAN provides ([006]) “aligning, using a microprocessor, sequence reads generated from a test sample including RNA amplicon molecules to the modified reference genome”, which teaches amplicon-read input from primer-based target amplifications.
BEAN provides ([006]) “receiving onto a data storage unit a plurality of primer sequences and a plurality of transcript sequences from a reference genome”, which teaches both primer sequence data and source/reference transcript sequence data.
BEAN provides (claim 1 4th step) “aligning, using a microprocessor, sequence reads generated from a test sample comprising RNA amplicon molecules to the modified reference genome”, and the “reference genome based on the plurality of target sequences” is “amplified from a combination of the plurality of primer sequences and the plurality of transcript sequences”. BEAN teaches read-to-reference/source alignment. Because the recited “source gene” is obvious over the “modified reference genome”.
BEAN provides ([003]) “amplicon data contain unique primer artifacts, are affected by false-positive (off-target) amplifications” ([062]) “selection of primers for multiplex synthesis and amplifying of DNA corresponding to a test sample's RNA determines on-target and off-target sequences”, which teaches classifying off-target/nonspecific amplificon targets; and classifying unmatched reads as nonspecific is a routine consequence of alignment-based target classification.
BEAN teaches detecting ([097]) “In some cases, off-target matches may also occur, whether in conjunction with a primer in the same pair or another pair (e.g., an inter-locus off-target match). In a multiplex scenario, the candidate primer sequences 110 can be targeted to multiple locations of the transcript sequence 180, resulting in higher computational complexity when finding off-target matches”, which teaches off-target primer matching as part of off-target amplification detection. The exact workflow “aligning the nonspecific
amplification sequence data to the primer sequence data, and taking a primer with the primer sequence data being matched with the nonspecific amplification sequence data as an amplification source primer of the nonspecific amplification sequence” is not expressly taught, but using the nonspecific sequence as query against primer data is a predictable equivalent sequence-comparison implementation.
Regarding claim 4, BEAN aligns reads to a modified reference genome and discusses candidate matching locations on a reference genome/transcript sequence ([012]). BEAN teaches read/reference alignment for amplicon/off-target analysis.
BEAN’s alignment profile includes “placement” and detects matching locations on reference/transcript sequences ([012]). BEAN further provides (097]) “In some cases, off-target matches may also occur, whether in conjunction with a primer in the same pair or another pair (e.g., an inter-locus off-target match). In a multiplex scenario, the candidate primer sequences 110 can be targeted to multiple locations of the transcript sequence 180, resulting in higher computational complexity when finding off-target matches”. Hence position information is a direct output of reference-genome alignment.
Regarding claim 5, BEAN’s alignment profile includes “placement, a quality score, and sequence integrity” ([012]). Counting/reporting source, position, and features from an alignment result is a routine summary operation; BEAN provides placement/quality/integrity information.
Regarding claim 11, BEAN teaches a computer-implemented method and a computer system with microprocessors, memories, and stored instructions for primer/reference/read processing ([013]). Obvious system/device counterpart to claim 1.
Regarding claim 13, BEAN teaches stored instructions in memories causing processors to perform the alignment method ([013]). Obvious CRM counterpart to claim 1.
Regarding claim 16, BEAN supplies computer implementation plus reference-genome alignment and placement ([013]). Other than that, the art applied to claims 4 and 11 also teaches claim 16.
Regarding claim 17, BEAN supplies alignment profile including placement/quality/integrity ([010-011]). Other than that, the art applied to claims 5 and 11 also teaches claim 17.
It would have been prima facie obvious to modify BEAN’s on-targeted amplicon detection, to detect off-target primers. The motivation would have been to extend the existing functions so to identify and troubleshoot nonspecific/off-target amplification products in complicated sequencing where off-target amplification happens.
One would reasonably expect success as BEAN already discloses methods for off-target match detection (“Example 1—Example System Implementing Off-Target Matching Detection” @[096-107]) and separating primer sequence from reference genome in sequence mapping would be obvious. BEAN itself provides the problem and motivation: amplicon data contain primer artifacts and false-positive/off-target amplifications, and primers producing off-target sequences may be identified.
Claims 6-7, are rejected under 35 U.S.C. 103 as being unpatentable over BEAN, as applied to claims 1, 4-5, 11, 13 and 16-17 above, and further in view of Heiden et. al.: (“pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires,” Bioinformatics, 2014, 30(13):1930-1932. Newly cited)
Regarding claim 6, BEAN teaches alignment profile include “quality score” ([012]), but BEAN does not teach a filter based on quality or a filter based on “abundance of duplicate reads”.
Heiden teaches duplicate/quality filtering (page 1931, col 2, 2nd para); The exact repeated-base-proportion / low-complexity threshold is not verbatim in Heiden. It is a routine NGS QC criterion.
Regarding claim 7, Heiden filters by “Phred quality scores” (page 1931, col 2, 2nd para); Heiden teaches removing low-quality sequence data.
It would have been prima facie obvious to modify the combined pipeline for targeted amplicon/off-target primer-detection process for use in immune-gene repertoire sequencing by BEAN, with Heiden’s quality assurance methods for paired-end read preprocessing. The motivation would have been to improve primer-panel specificity, reduce primer-caused artifacts, and obtain more reliable classification of immune-gene reads.
One would reasonably expect success as BEAN and Heiden are all in the same field endeavor. BEAN itself provides the problem and motivation: amplicon data contain primer artifacts and false-positive/off-target amplifications, and primers producing off-target sequences may be excluded or redesigned. Heiden provides the raw-read processing pipeline needed before germline segment assignment. Heiden compensates BEAN without interfering BEAN.
Claims 2-3, 14-15, 18-19 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over BEAN and Heiden, as applied to claims 1, 4-7, 11, 13 and 16-17 above, and further in view of Ye et. al.: (“IgBLAST: an immunoglobulin variable domain sequence analysis tool,” Nucleic Acids Research, 2013, 41(Web Server issue): W34-W40. Newly cited).
Regarding claim 2, neither BEAN nor Heiden teaches the immune V/D/J genes. Ye analyzes immunoglobulin V/D/J genes (page W34, col 1, Section “Abstract”), which teaches the immune-gene amplicon/repertoire sequencing. However, neither BEAN nor Ye teach paired-end reads. Heiden teaches paired-end reads.
Heiden supports “single- or paired-end reads” and “de novo assembly of overlapping paired-end reads” (page 1931, col 2, 4th para), which teaches paired-end overlap classification/handling of sequence.
Heiden processes “raw sequences” (page 1930, col 1, section “Abstract/Summary”) and supports “multiplexed primer pools” (page 1930, col 1, section “Abstract/Summary”). Raw primer-amplified repertoire reads are taught.
Heiden provides de novo assembly of overlapping paired-end reads (page 1931, col 2, 4th para); Heiden support the operation of overlapping sequences. Although Heiden does not teach two length thresholds, it would be routine quality control to ensure good overlapping operation.
Heiden teaches paired-end overlap assembly/merging (page 1931, col 2, 4th para); Reads failing overlap/length thresholds would predictably remain unmerged/non-overlapping or be separately processed.
Regarding claim 3, neither BEAN nor Heiden teaches the immune V/D/J genes. Ye provides “matches to the germline V, D and J genes” (page W34, col 1, Section “Abstract”), which teaches the source gene sequence data comprises the VDJ gene family. However, neither BEAN nor Ye teach paired-end reads. Heiden teaches paired-end reads.
Heiden handles paired-end repertoire reads (page 1931, col 2, 4th para); Ye teaches V/D/J matching/alignment (page W34, col 1, Section “Abstract”), Heiden and Ye Combination supplies paired-end preprocessing followed by V/D/J source-gene alignment.
Ye offers IgBLAST (BLAST-based) that provides matches to germline V/D/J genes (page W34, col 1, Section “Abstract”). The exact phrase not used, but alignment identity/score/consistency values are routine outputs of sequence alignment.
Ye teaches V/D/J matches and sequence analysis (page W34, col 1, Section “Abstract”). The exact comparable-length formula is not quoted verbatim, but it is a routine thresholding/coverage calculation for determining whether an immune read sufficiently maps to V/D/J source segments.
BEAN recognizes on-target/off-target classification ([009]); Ye teach V/D/J matching (page W34, col 1, Section “Abstract”). Once reads are aligned to source V/D/J genes, classifying poor/insufficient matches as nonspecific would have been routine.
Regarding claim 14, BEAN supplies processor/memory device ([013]). Other than that, the art applied to claims 2 and 11 also teaches claim 14.
Regarding claim 15, supplies computer implementation ([013]). Other than that, the art applied to claims 3 and 11 also teaches claim 15.
Regarding claim 18, BEAN supplies device ([013]). Other than that, the art applied to claims 6 and 11 also teaches claim 18.
Regarding claim 19, BEAN supplies device ([013]). Other than that, the art applied to claims 7 and 11 also teaches claim 19.
Regarding claim 22, BEAN supplies stored-instruction computer implementation ([013]). Other than that, the art applied to claims 2 and 13 also teaches claim 22.
It would have been prima facie obvious to modify combined BEAN/Heiden pipeline of targeted amplicon/off-target primer-detection process with quality assurance, with immune-gene repertoire sequencing by using Ye’s germline V/D/J matching. The motivation would have been to extend the capability of the pipeline to multiplex immune-repertoire sequencing.
One would reasonably expect success as BEAN, Heiden and Ye are all in the same field endeavor. BEAN itself provides the problem and motivation: amplicon data contain primer artifacts and false-positive/off-target amplifications, and primers producing off-target sequences may be excluded or redesigned by Heiden’s teaching. Ye provides the biological source-gene databases ordinarily used for V/D/J immune sequence interpretation. Ye compensates BEAN/Heiden without interfering BEAN/Heiden.
Claims 9 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over BEAN, Ye and Heiden, as applied to claims 1-7, 11, 13-19 and 22 above, and further in view of Bolger et. al.: (“Trimmomatic: a flexible trimmer for Illumina sequence data,” Bioinformatics, 2014, 30(15):2114-2120. Newly cited).
Regarding claim 9, BEAN, Ye and Heiden teach general and immune-specific gene mapping, as well as paired-end reads mapping. However none of BEAN, Ye and Heiden teaches filtering reads based on sequencing quality. Bolger performs quality filtering and trimming (page 2116, col 1, penultimate para through page 2117, col 1, 2nd para), which teaches trimming low-quality sections is taught.
Bolger supports read preprocessing and post-trimming filtering such as read-length thresholds (page 2114, col 2, penultimate para through page 2115, col 1, 1st para). Discarding too-short reads after trimming is a routine Trimmomatic-type QC step.
Regarding claim 21, BEAN supplies device ([013]). Other than that, the art applied to claims 9 and 11 also teaches claim 21.
It would have been prima facie obvious to modify the combined pipeline for targeted amplicon/off-target primer-detection process for use in immune-gene repertoire sequencing by BEAN and Ye, Heiden, with Bolger’s teaching paired-end-aware NGS preprocessing, adapter/technical sequence removal, quality filtering, low-quality trimming, and length filtering. The motivation would have been to improve primer-panel specificity, reduce primer-caused artifacts, and obtain more reliable classification of immune-gene reads.
One would reasonably expect success as BEAN, Ye, Heiden and Bolger are all in the same field endeavor. BEAN itself provides the problem and motivation: amplicon data contain primer artifacts and false-positive/off-target amplifications, and primers producing off-target sequences may be excluded or redesigned. Bolger supplies supports paired-end workflow. Bolger compensates Heiden in quality assurance without interfering BEAN/Ye/Heiden.
Claims 8 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over BEAN, Ye, Heiden and Bolger, as applied to claims 1-7, 9, 11, 13-19 and 21-22 above, and further in view of Martin (“Cutadapt removes adapter sequences from high-throughput sequencing reads,” EMBnet.journal, 2011, 17(1):10-12. Newly cited)
Regarding claim 8,combined BEAN, Ye, Heiden and Bolger teach general as well as immune-specific sequence mapping with quality improvement based on paired-end reads and quality-based filtering. However, none of BEAN, Ye, Heiden and Bolger teaches removing of adapter sequences. Martin teaches adapter “must be found and removed, error-tolerantly from each read before read mapping” (page 10, col 1, section “Abstract”). Hence Martin teaches adapter removal
Bolger detects technical sequences and removes contaminant regions when alignment score/overlap criteria are met; Trimmomatic documentation recognizes minimum adapter-length parameters (page 2114, col 2, last para through page 2115, col 1, 1st para). Specific end-length thresholds are routine adapter-trimming parameters.
Heiden filters by Phred quality scores (page 1931, col 2, 2nd para); Bolger performs quality filtering (page 2116, col 1, penultimate para through page 2117, col 1, 2nd para). Average quality threshold filtering is routine NGS preprocessing. |
Regarding claim 20, BEAN supplies device ([013]). Other than that, the art applied to claims 8 and 11 also teaches claim 20.
It would have been prima facie obvious to modify the combined pipeline for targeted amplicon/off-target primer-detection process for use in immune-gene repertoire sequencing by BEAN, Ye, Heiden and Bolger, with Martin’s teaching that adapter sequences in high-throughput sequencing reads must be found and removed before read mapping. The motivation would have been to improve primer-panel specificity, reduce adapter-caused artifacts, and obtain more reliable classification of immune-gene reads.
One would reasonably expect success as BEAN, Ye, Heiden, Bolger and Martin are all in the same field endeavor. BEAN itself provides the problem and motivation: amplicon data contain primer artifacts and false-positive/off-target amplifications, and primers producing off-target sequences may be excluded or redesigned. Martin supplies adapter removal, Heiden/Bolger supply quality filtering, low-quality trimming, and post-trimming length filtering before or during the alignment workflow. Martin compensates Heiden/Bolger without interfering BEAN/Ye/Heiden/Bolger.
Conclusion
No claims are allowed.
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/GL/
Patent Examiner
Art Unit 1686
/Anna Skibinsky/
Primary Examiner, AU 1635
Prosecution Insights