DETAILED ACTION
Comments
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . 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.
Claims 1-7, 9-12, 17-27, 29, and 44-46 are pending and examined in the instant Office action.
Information Disclosure Statements
The IDSs submitted have been considered.
Claim Rejections - 35 USC § 112(b) - Indefiniteness
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 4, 24, and 44-46 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.
The term “high confidence” in each of claims 4 and 24 is a relative term which renders the claim indefinite. The term “high confidence” 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 unclear as to what causes a threshold detection error rate to be associated with high confidence as to the veracity of variants observed in sequencing data versus what causes a threshold detection error rate to be associated with low confidence as to the veracity of variants observed in sequencing data. For the purpose of examination, it is interpreted that any threshold detection error rate is associated with high confidence as to the veracity of variants observed in sequencing data.
Claim 44 recites the limitation "the kit" in line 6. There is insufficient antecedent basis for this limitation in the claim. The term “kit” is not previously recited in the claim. For the purpose of examination, it is interpreted that “the kit” corresponds to “a kit”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-7, 9-12, 17-27, 29, and 44-46 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea/law of nature/natural phenomenon without significantly more. Claims 1-7, 9-12, and 17-18 are drawn to methods, and claims 19-27, 29, and 44-46 are drawn to systems comprising processors.
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1 : YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claims 1 and 19 recite the mental step of receiving a sequence read, wherein the sequencing read comprises a basecall and a base-wise error score associated with a base within the sequencing read.
Claims 1 and 19 recite the mental step of receiving a locus-specific error profile for an allele, wherein the locus-specific error profile comprises a threshold detection error rate,
Claims 1 and 19 recite the mental step of comparing the base-wise error score associated with the base to the threshold detection error rate for the base.
Claims 1 and 19 recite the mental step of filtering the base based on the comparison, wherein the base is accepted as a true variant allele or discarded as a false positive allele based on the comparison.
Claims 2 and 22 recite the mathematical limitation of accepting the base as a true variant allele when the base-wise error score associated with the base is greater than or equal to the threshold detection error rate for the base.
Claims 3 and 23 recite the mathematical limitation of discarding the base as a false positive allele when the base-wise error score associated with the base is less than the threshold detection error rate for the base.
Claims 4 and 24 recited the mental step of associating the threshold detection error rate with confidence as to the veracity of variants observed in sequencing data.
Claims 5 and 25 recite the mental step of reading the locus-specific error profile for the allele from a lookup table.
Claims 6 and 26 recite the mental step of the lookup table storing a plurality of sets of locus-specific error profiles for the allele.
Claims 7 and 27 recite the mental step of associating each set of locus-specific error profiles with a different model or algorithm.
Claim 9 recites the mental step of associating a locus-specific error profile with a location of an allele in a reference genome.
Claim 10 recites the mental step of association the locus-specific error profile with a model or algorithm.
Claim 11 recites the mental step of receiving a model or algorithm.
Claims 12 and 29 recite the mental step of associating the locus-specific error profile with a directionality of basecalling.
Claim 17 recites the mental steps of detecting a true variant allele and diagnosing a patient with a disease or condition.
Claim 18 recites the mental step of constraining the disease to be AML.
Claim 44 recites the mental step of receiving sequence reads, performing a basecalling algorithm on the sample, and performing an algorithm to diagnose ITD.
Claim 46 recites mental and mathematical limitations for performing the detection algorithm to diagnose ITD.
These recitations are similar to the concepts of collecting information, analyzing it and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind or mathematical relationships. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then if falls within the “Mental processes” grouping of abstract ideas. As such, claim(s) 1-7, 9-12, 17-27, 29, and 44-46 recite(s) an abstract idea/law of nature/natural phenomenon (Step 2A, Prong 1 : YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to affect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a generic treatment.
While claim 17 recites performing a generic therapy to a diseased patient, claim 17 does not recite a particular therapy.
As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. As such, claims 1-7, 9-12, 17-27, 29, and 44-46 is/are directed to an abstract idea/law of nature/natural phenomenon (Step 2A, Prong 2 : NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment.
The prior art of Huang et al. [Bioinformatics, volume 28, 2012, pages 593-594; on attached 892 form] teaches that performing next generation sequencing is routine and conventional in the prior art.
As discussed above, there are no additional limitations to indicate that the claimed analysis engine requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. MPEP 2106.05(f) discloses that mere instructions to apply the judicial exception cannot provide an inventive concept to the claims. The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B : No). As such, claims 1-7, 9-12, 17-27, 29, and 44-46 is/are not patent eligible.
Claim Rejections - 35 USC § 102
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.
Claim(s) 44-45 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Platt [US PGPUB 2016/0340722 A1; on IDS].
Paragraphs 8 and 11 of Platt teach methods for detecting genetic mutations in samples. Paragraph 41 and Figure 18B of Platt teach detection of the sample FLT-3 region in MV-4-11 cancer cell line, which has 30 bp FLT3 internal tandem repeat duplication. Paragraphs 8 and 87 of Platt teach a processor configured to receive sequencing data. Paragraphs 65 and 156 of Platt teach a sequence comparison algorithm test wherein reference sequences are put into a computer, subsequence coordinates are designated, and sequencing algorithm programming parameters are designated. Paragraph 12 of Platt teaches a kit for detecting genetic mutations.
With regard to claim 45, paragraph 54 of Platt teaches a next-generation sequencing instrument.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
35 U.S.C. 103 Rejection #1:
Claim(s) 1-4 and 19-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Newman et al. [Nature Biotechnology, volume 34, 2016, pages 546-555; on IDS] in view of Platt [US PGPUB 2016/0340722 A1; on IDS].
With regard to claims 1 and 19, Newman et al. teaches a computer-implemented method for detecting alleles in a sample. Specifically, Newman et al. teaches that by demonstrating biopsy-free tumor genotyping and disease monitoring of NSCLC patients, page 2, final paragraph of Newman et al. teaches that iDES can significantly improve the sensitivity and specificity of the detection of low frequency alleles in ctDNA. The abstract of Newman et al. teaches an in silico algorithm for overcoming limitations in genetic analysis of DNA (iDES) by elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules.
The methods section of Newman et al. teaches a computational approach for “background polishing” by modeling position-specific errors in a training cohort of control samples to allow error suppression in independent samples. The methods section of Newman et al. teaches that by applying a zero-inflated statistical model to capture a broad range of background distributions, the methods section of Newman et al. addresses each type of recurrent background error in a position-specific and data-driven manner.
Figure 2 and page 18, first partial paragraph of Newman et al. teach designing a larger ~200kB NSCLC “tumor genotyping” selector, which contains the entire cfDNA selector and targets additional regions (including complete exon coverage of selected genes and the addition of other regions of clinical or biological interest). Figure 2 of Newman et al. teaches development of iDES wherein the top of the figure illustrates a heat map showing position-specific selector-wide error rates, and the bottom of the figure illustrates selector-wide error metrics.
The paragraph bridging pages 21-22 of Newman et al. teaches a general genotyping approach that adaptively considers local and global variation in background error rates, enabling automatic determination of position-specific variant calling thresholds in each sample. Page 5, second paragraph of Newman et al. teaches that error-prone bases are not indiscriminately eliminated, but are only removed if the error-prone bases are indistinguishable from their corresponding null distributions in normal controls. The final full paragraph on page 7 of Newman et al. teaches that most errors in cfDNA sequencing data are introduced ex vivo, and any significantly detectable variants after iDES are likely to reflect true genetic heterogeneity.
Newman et al. does not teach the computer limitations of the claims.
Paragraphs 86-87 of Platt teach the computer limitations used to perform an analogous sequence analysis algorithm.
With regard to claims 2-4 and 22-24, while Newman et al. does not explicitly teach the mathematical limitations recited in the claims, it would have been obvious to compare the error-rate to a threshold to discriminate true variants from falser positives as one of the purposes of Newman et al. is to eliminate artifacts and increase the sensitivity of the sequencing data. Absent a limiting description of high confidence and veracity, the results of Newman et al. are interpreted to have high confidence and veracity.
With regard to claims 20-21, the first partial paragraph of page 12 of Newman et al. teaches that sequencing and next-generation sequencing are performed on an Illumina MiSeq, NextSeq, or HiSeq 2000, 2500, or 4000.
It would have been obvious to someone of ordinary skill in the art at the time of the effective filing date of the instant application to modify the sequencing error analysis of Newman et al. by use of the computer equipment of Platt wherein the motivation would have been that the computer equipment of Platt would automate the analysis of Newman et al. (i.e. making the analysis more efficient and accurate) [paragraphs 86-87 of Platt].
35 U.S.C. 103 Rejection #2:
Claim(s) 5-7, 9-12, 25-27, and 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Newman et al. in view of Platt, applied to claims 1-4 and 19-24 above, in further view of Bruand et al. [AU 2015318017 B2; on attached 892 form].
Claims 5-7 and 25-27 recite analysis of locus-specific errors and data manipulations pertaining to lookup tables.
Claims 9-11 recite associating locus-specific error profile with a location on the gene.
Newman et al. and Platt make obvious automated sequencing error analysis, as discussed above. The documents of Newman et al. and Platt. teach a plurality of sequencing analysis models.
Newman et al. and Platt do not teach use of lookup tables to analyze sequencing errors.
The document of Bruand et al. teaches analysis of nucleic acid sequencing data [title]. Paragraph 69 of Bruand et al. teaches analysis of sets of sequencing data using data stored in lookup tables that can associate a nucleic acid base with its locus on the gene.
With regard to claims 12 and 29, paragraph 62 of Bruand et al. teaches sequencing results based on a directionality of sequencing.
It would have been obvious to someone of ordinary skill in the art at the time of the effective filing date of the instant application to modify the sequencing error analysis of Newman et al. and the computer analysis of sequencing data of Platt by use of the sequencing analysis techniques of Bruand et al. wherein the motivation would have been that the lookup tables of Bruand et al. facilitate the analysis of sequence data [paragraph 69 of Bruand et al.].
35 U.S.C. 103 Rejection #3:
Claim(s) 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Newman et al. in view of Platt, applied to claims 1-4 and 19-24 above, in further view of Rubenstein et al. [US PGPUB 2018/0226153; on attached 892 form].
Claim 17 is further limiting comprises detecting a true variant allele, diagnosing a patient with a disease or condition based on the true variant allele, and delivering a therapy to the patient with the disease or condition.
Claim 18 is further limiting wherein the disease or condition is AML.
Newman et al. and Platt make obvious automated sequencing error analysis, as discussed above. Newman et al. uses sequencing analysis to detect variants and assess NSCLC in patients.
Newman et al. and Platt do not teach providing therapy and the assessment of AML.
The document of Rubenstein et al. pertains to using machine learning algorithms to predict treatment outcomes to therapies for diseases [abstract and cover figure]. Paragraph 25 of Rubenstein et al. teaches that the algorithms are applicable to NSCLC and AML.
It would have been obvious to someone of ordinary skill in the art at the time of the effective filing date of the instant application to modify the sequencing error analysis of Newman et al. and the computer analysis of sequencing data of Platt by use of the therapy and therapy algorithms of Rubenstein et al. wherein the motivation would have been that Rubenstein et al. treats the diseases that are detected and uses analogous machine learning algorithms to analyze the results [abstract and cover figure of Rubenstein et al.].
35 U.S.C. 103 Rejection #4:
Claim(s) 44-46 is/are rejected under 35 U.S.C. 103 as being unpatentable over Platt [US PGPUB 2016/0340722 A1; on IDS] in view of Abdueva [US PGPUB 2019/0352695 A1; on IDS] in view of Nik-Zainal et al. [US PGPUB 2019/0119759 A1; on IDS].
Platt teaches the limitations of claims 44-45, as discussed above.
Platt does not teach the detection algorithm of claim 46.
Paragraph 5 of Abdueva teaches a computer-implemented method for determining aberrations in cfDNA from a subject from a multi-parametric distribution of DNA fragments over a plurality of base positions in a genome. Paragraph 5 of Abdueva teaches that elements of the distribution comprise genetic loci. Paragraph 152 of Abdueva teaches that elements of the distribution comprise genetic loci. Paragraph 20 teaches properties of selected peaks, including width, size, distribution, and area. Paragraph 204 of Abdueva teaches peak filtering techniques. Paragraph 345 of Abdueva teaches heuristic tuning. Paragraphs 7 and 141 of teaches finding consensus sequencing.
Nik-Kainal et al. teaches updating consensus reference sequences with insertions mapping tandem duplication events [abstract and paragraphs 40, 99, and 104 of Nik-Zainal et al.].
It would have been obvious to someone of ordinary skill in the art at the time of the effective filing date of the instant application to modify the computer sequencing analysis of ITDs of Platt by use of the peak analysis of Abdueva and the consensus sequencing of Nik-Zainal et al. wherein the motivation would have been that the mathematical data manipulation techniques of Abdueva and Nik-Zainal et al. facilitate the sequence variant analysis of Platt [paragraph 20 of Abdueva and paragraphs 40, 99, and 104 of Nik-Zainal et al.].
E-mail Communications Authorization
Per updated USPTO Internet usage policies, Applicant and/or applicant’s representative is encouraged to authorize the USPTO examiner to discuss any subject matter concerning the above application via Internet e-mail communications. See MPEP 502.03. To approve such communications, Applicant must provide written authorization for e-mail communication by submitting the following statement via EFS-Web (using PTO/SB/439) or Central Fax (571-273-8300):
Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.
Written authorizations submitted to the Examiner via e-mail are NOT proper. Written authorizations must be submitted via EFS-Web (using PTO/SB/439) or Central Fax (571-273-8300). A paper copy of e-mail correspondence will be placed in the patent application when appropriate. E-mails from the USPTO are for the sole use of the intended recipient, and may contain information subject to the confidentiality requirement set forth in 35 USC § 122. See also MPEP 502.03.
Conclusion
No claim is allowed.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Russell Negin, whose telephone number is (571) 272-1083. This Examiner can normally be reached from Monday through Thursday from 8 am to 3 pm and variable hours on Fridays.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s Supervisor, Larry Riggs, Supervisory Patent Examiner, can be reached at (571) 270-3062.
/RUSSELL S NEGIN/ Primary Examiner, Art Unit 1686 21 December 2025