DETAILED ACTION
Applicant’s response filed 08/14/2025 has been fully considered. The following rejections and/or objections are either reiterated or newly applied.
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 08/14/2025 has been entered.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status
Claims 3-5, 9, 14 and 16-20 are cancelled by Applicant.
Claim 22 is newly added.
Claims 1-2, 6-8, 10-13, 15 and 21-22 are currently pending.
Claims 6 and 8 are withdrawn by Applicant as discussed in the Election of Species section in the Office action mailed 12/11/2024.
Claims 1-2, 7, 10-13, 15 and 21-22 are herein under examination.
Claims 1-2, 7, 10-13, 15 and 21-22 are rejected.
Claims 1, 12 and 21 are objected.
Priority
The instant application claims domestic benefit to U.S. Provisional Application No. 63/022,296 filed 05/08/2020. The claim to domestic benefit is acknowledged for claims 1-2, 7, 10-13, 15 and 21-22. As such, the effective filing date for claims 1-2, 7, 10-13, 15 and 21-22 is 05/08/2020.
Information Disclosure Statement
The IDSs filed 09/02/2025 and 08/14/2025 follow the provisions of 37 CFR 1.97 and have been considered in full. A signed copy of the list of references cited from these IDSs is included with this Office Action.
Claim Objections
The objection to claims 1 and 21 are withdraw in view of Applicant’s claim amendments.
Claims 1, 12 and 21 are objected to because of the following informalities:
Claim 1, line 25, should have a “;” after the phrase “second threshold” to correct the grammar of the claim.
Claim 12, line 6, recites the phrase “initialized control” which should recite “initialized with control” to correct the grammar of the clause.
Claim 12, lines 21-22, recites the phrase “based on on one” which should recite “based on one”.
Claim 12, line 26, recites “being-above” which should recite “being above”.
Claim 21, line 8, recites the phrase “a a plurality” which should recite “a plurality”.
Appropriate correction is required.
Withdrawn Rejection
35 USC 101
The rejection of claim 3 under 35 USC 101 is withdrawn in view of Applicant’s claim amendments cancelling claim 3.
35 USC 112(b)
The rejection of claims 12-13 and 15 under 35 USC 112(b) is withdrawn in view of Applicant’s claim amendments.
35 USC 112(d)
The rejection of claim 3 under 35 USC 112(d) is withdrawn in view of Applicant cancelling claim 3.
Claim Rejections - 35 USC § 112
35 USC 112(b)
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 1-2, 7, 10-13, 15 and 21-22 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.
This rejection is newly recited and is necessitated by claim amendment.
Claim 1, lines 16-17, recites the following phrase the renders the claim indefinite: “wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer”. It is unclear if “the exact match” refers to the phrase “exact match” recited in line 5 or line 12. For examination purposes, this phrase is being interpreted to limit line 5.
Claim 1, lines 16-17, recites the phrase “wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer” which renders the claim indefinite. It is unclear how this phrase further limits the claim because an exact match inherently means that any k-mer that differs by even 1 nucleotide is not exact. It is also unclear if the phrase intends to mean that if a k-mer differs by 1-3 bases then it is not exact, but if a k-mer differs by more than 4 bases then it is exact. For examination purposes, this phrase is being interpreted to mean that a k-mer in the subset of k-mers in the pathogen genome have no exact match and have no matches that differ by at least 1 nucleotide in k-mers of a human control genome.
Furthermore, claims 2, 7 and 10-11 are also rejected because they depend on claim 1, which is rejected, and because they do not resolve the issue of indefiniteness.
Claim 2 recites the phrases “the first set” and “the second set” which lack antecedent basis. To overcome this rejection, it is suggested to delete the phrases or amend claim 1 such that the phrases have antecedent basis.
Claim 7 recites the phrases “the first set” and “the second set” which lack antecedent basis. To overcome this rejection, it is suggested to amend claim 1 such that the phrases have antecedent basis.
Claim 12, lines 16-17, recites the following phrase that renders the claim indefinite: “wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer”. It is unclear if “the exact match” refers to the phrase “exact match” recited in line 5 or line 12. For examination purposes, this phrase is being interpreted to limit line 5.
Claim 12, lines 16-17, recites the phrase “wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer” which renders the claim indefinite. It is unclear how this phrase further limits the claim because an exact match inherently means that any k-mer that differs by even 1 nucleotide is not exact. It is also unclear if the phrase intends to mean that if a k-mer differs by 1-3 bases then it is not exact, but if a k-mer differs by more than 4 bases then it is exact. For examination purposes, this phrase is being interpreted to mean that a k-mer in the subset of k-mers in the pathogen genome have no exact match and have no matches that differ by at least 1 nucleotide in k-mers of a human control genome.
Claim 12, lines 18-19, recites the phrase “a second hash table” which renders the claim indefinite. It is unclear if there are two distinct second hash tables in claim 12, or if the phrase “a second hash table” in lines 18-19 should recite “the second hash table” in order to refer to the second hash table in line 6. For examination purposes, this phrase will be interpreted as if it recited “the second hash table” in order to refer to line 6. As a result of this interpretation, claim 13 has been rejected below under 35 USC 112(d) for failing to further limit claim 12, because claim 12 already requires the limitations of claim 13.
Claim 12, line 24, recites the phrase “the respective individual target regions in the pathogen genome” which lacks antecedent basis. To overcome this rejection, it is suggested to provide antecedent basis for the phrase.
Furthermore, claims 13 and 15 are also rejected because they depend on claim 12, which is rejected, and because they do not resolve the issue of indefiniteness.
Claim 21, lines 17-18, recites the following phrase that renders the claim indefinite: “wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer”. It is unclear if “the exact match” refers to the phrase “exact match” recited in line 4 or lines 13-14. For examination purposes, this phrase is being interpreted to limit line 4.
Claim 21, lines 17-18, recites the phrase “wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer” which renders the claim indefinite. It is unclear how this phrase further limits the claim because an exact match inherently means that any k-mer that differs by even 1 nucleotide is not exact. It is also unclear if the phrase intends to mean that if a k-mer differs by 1-3 bases then it is not exact, but if a k-mer differs by more than 4 bases then it is exact. For examination purposes, this phrase is being interpreted to mean that a k-mer in the subset of k-mers in the pathogen genome have no exact match and have no matches that differ by at least 1 nucleotide in k-mers of a human control genome.
Claim 21, lines 19-20, recites the phrase “a second hash table” which renders the claim indefinite. It is unclear if there are two distinct second hash tables in claim 21, or if the phrase “a second hash table” in lines 19-20 should recite “the second hash table” in order to refer to the second hash table in line 5. For examination purposes, this phrase will be interpreted as if it recited “the second has table” in order to refer to line 5.
35 USC 112(d)
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 13 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.
This rejection is newly recited and is necessitated by claim amendment.
Claim 13 is rejected for failing to further limit claim 12. As discussed in the rejection above under 35 USC 112(b), the phrase in claim 12, lines 18-19 of “a second hash table” is being interpreted to mean “the second hash table”. Claim 12 already requires identifying control k-mers in the sequence data that have an exact match with k-mers of a human control genome, as recited in lines 6 and 18-19.
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 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 1-2, 7, 10-13, 15 and 21-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Any newly recited portions herein are necessitated by claim amendment.
Step 2A, Prong 1:
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 phenomena (Step 2A, Prong 1). In the instant application, claims 1-2, 7, 10 and 22 recite a method, claims 12-13 and 15 recite a method, and claim 21 recites a method. The instant claims recite the following limitations that equate to one or more categories of judicial exception:
Claim 1 recites “identifying, in real-time, first k-mers in the sequence data that have an exact match in the first hash table and wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer; identifying second k-mers in the sequence data that have an exact match in the second hash table; providing a positive detection output for a subset of the plurality of biological samples
Claim 2 recites “wherein the k-mers in the sequence data, the first set, and the second set are of a fixed size that is greater than 24 nucleotides.”
Claim 7 recites “wherein the first set is larger than the second set.”
Claim 10 recites “comprising identifying sequence variants of the pathogen in aligned sequence data.”
Claim 12 recites “identifying first k-mers in the sequence data, in real-time, that have an exact match in the first hash table and wherein the exact match excludes k-mers that differ by 1-3 bases within the k-mer; identifying second k-mers in the sequence data that have an exact match in a second hash table; determining, for a subset of biological samples of the plurality of biological samples, a positive detection output for the pathogen based on one or both of a count of the identified first k-mers or a number of sequence reads in the sequence data comprising the identified first k-mers that correspond to the respective individual target regions in the pathogen genome being above a threshold count and that a count of the identified second k-mers is above a threshold count; and terminating analysis of the sequence data for biological samples not in the subset”
Claim 13 recites “comprising identifying control k-mers in the sequence data that have an exact match with a control set of k-mers of a control genome.”
Claim 15 recites “comprising identifying sequence variants of the pathogen in the sequence data.”
Claim 21 recites “identifying, in real-time, first k-mers in the sequence data that have an exact match in the first hash table comprising control k-mers from a human control genome, wherein the subset is selected based on k-mers with no exact match in the control genome and wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer; identifying second k-mers in the sequence data that have an exact match in a second hash table; providing a positive detection output for a subset of the plurality of biological samples based at least in part on, for an individual biological sample of the subset, a first count of exact matches of the first k-mers in the sequence data being above a threshold and a second count of exact matches of the second k-mers in the sequence data being above a threshold; initiating sequence alignment with the genome of the pathogen upon providing the positive detection output for each individual biological sample of the subset; and not performing sequencing alignment with the genome of the pathogen for biological samples of the plurality of biological samples not in the subset.”
Claim 22 recites “wherein the positive detection output is provided for the individual biological sample of the subset while sequence data is still being generated by the sequence device and based on detection of 1-5% of a total number of the amplicons of the individual biological sample of the subset.”
Limitations reciting a mental process.
The above cited limitations in claims 1, 10, 12-13, 15 and 21-22 are recited at such a high level of generality that they equate to a mental process because they 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)), which the courts have identified as concepts that can be practically performed in the human mind or by a human using pen and paper. The paragraphs below discuss the limitations in these claims that recite a mental process under their broadest reasonable interpretation (BRI).
The BRI of identifying k-mers in a hash table includes performing operations of a hash function and looking up a value associated with a hash code. The BRI of terminating counting k-mers upon a positive detection includes a human stopping counting k-mers from the sequence data. The BRI of aligning sequence data with a genome of a pathogen includes aligning small reads with a pathogen genome, wherein the pathogen may be Human Hepatitis Delta Virus which contains a genome of about 1.7 kb. The BRI of identifying sequence variants in the aligned sequenced data to the pathogen genome includes identifying differences in nucleotide bases. The BRI of determining that k-mers are above a threshold includes making a determination that a number is above a threshold number. The BRI of providing a positive detection output includes writing on paper a final result of the data analysis steps of counting k-mers above a threshold.
Limitations reciting a mathematical concept.
The above cited limitations in claims 1, 12 and 21 equate to a mathematical concept because they are similar to the concept of 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)), which the courts have identified as mathematical concepts. The paragraph below discusses the limitations in these claims that recite a mathematical concept under their broadest reasonable interpretation (BRI).
The BRI of identifying k-mers from sequence data in a hash table initialized with k-mers includes performing a hash function to perform lookup in a hash table.
Limitations included in the judicial exception.
Regarding the above cited limitations in claims 2 and 7, these limitations are included in the recited judicial exception in claim 1 because they limit the following components in claim 1 that have been identified as reciting a judicial exception but do not change the fact that the components recite a judicial exception: the k-mers and the first set of k-mers.
As such, claims 1-2, 7, 10-13, 15 and 21-22 recite an abstract idea (Step 2A, Prong 1: Yes).
Step 2A, Prong 2:
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). The judicial exception is not integrated into a practical application because the claims do not recite additional elements that reflect an improvement to a computer, technology, or technical field (MPEP § 2106.04(d)(1) and 2106.5(a)), require a particular treatment or prophylaxis for a disease or medical condition (MPEP § 2106.04(d)(2)), implement the recited judicial exception with a particular machine that is integral to the claim (MPEP § 2106.05(b)), effect a transformation or reduction of a particular article to a different state or thing (MPEP § 2106.05(c)), nor provide some other meaningful limitation (MPEP § 2106.05(e)). Rather, the claims include limitations that equate to an equivalent of the words “apply it” (MPEP § 2106.05(f)) and insignificant extra-solution activity (MPEP § 2106.05(g)). The instant claims recite the following additional elements:
Claim 1 recites “generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome; generating a second hash table initialized with control k-mers of the human control genome; receiving streaming sequence data from a sequence device operating to conduct a sequencing run on a plurality of biological samples, wherein the sequence data comprises amplicon sequences from amplicons generated from the plurality of biological samples;”
Claim 11 recites “comprising administering a treatment for the pathogen responsive to the positive detection output for the pathogen detection, wherein the pathogen is SARS-CoV-2, and wherein the treatment is a SARS-CoV-2 treatment.”
Claim 12 recites “generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome; generating a second hash table initialized control k-mers of the human control genome; generating sequence data from a sequence device operating to conduct a sequencing run on a sequencing library prepared from a plurality of biological samples wherein the sequence data comprises amplicon sequences from amplicons generated from the plurality of biological samples;”
Claim 21 recites “generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome; generating a second hash table initialized with control k-mers of the human control genome; receiving streaming sequence data from a sequence device operating to conduct a sequencing run on a plurality of biological samples, wherein the sequence data comprises amplicon sequences from amplicons generated from the plurality of biological samples; using a processor comprising a reconfigurable field-programmable gate array to execute steps comprising:”
Regarding the above cited limitations in claims 1, 12 and 21 of generating hash tables, receiving streaming sequence data, and generating sequence data. These limitations equate to data gathering and outputting which the courts have established as insignificant-extra solution activity in Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Specifically, these limitations collect data that is used in the recited judicial exception of identifying k-mers, terminating counting k-mers, and initiating sequence alignment. These limitations then output the result of the judicial exception.
Regarding the above cited limitation in claim 11 of administering a SARS-CoV-2 treatment, this limitation equates to the words “apply it” because it generally recites an effect of the judicial exception and claims every mode of accomplishing that effect (MPEP 2106.05(f)(3)). Specifically, the “treatment” is so generically recited that it encompasses all types of treatments. This also means that the generically recited “treatment” is not a particular treatment because it encompasses all applications of the judicial exception (MPEP2106.04(d)(2)(a)).
Regarding the above cited limitation in claim 21 of using a processor comprising an FPGA to perform the judicial exception of identifying k-mers and initiating sequence alignment, this limitation equates to the words “apply it”, which does not integrate a judicial exception into a practical application. MPEP 2106.05(f) recites “As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do ‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’". Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965).
As such, claims 1-2, 7, 10-13, 15 and 21-22 are directed to an abstract idea (Step 2A, Prong 2: No).
Step 2B:
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). These claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because these claims recite additional elements that equate to instructions to apply the recited exception in a generic way and/or in a generic computing environment (MPEP § 2106.05(f)) and to well-understood, routine and conventional (WURC) limitations (MPEP § 2106.05(d)). The instant claims recite the following additional elements:
Claim 1 recites “generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome; generating a second hash table initialized with control k-mers of the human control genome; receiving streaming sequence data from a sequence device operating to conduct a sequencing run on a plurality of biological samples, wherein the sequence data comprises amplicon sequences from amplicons generated from the plurality of biological samples;”
Claim 11 recites “comprising administering a treatment for the pathogen responsive to the positive detection output for the pathogen detection, wherein the pathogen is SARS-CoV-2, and wherein the treatment is a SARS-CoV-2 treatment.”
Claim 12 recites “generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome; generating a second hash table initialized control k-mers of the human control genome; generating sequence data from a sequence device operating to conduct a sequencing run on a sequencing library prepared from a plurality of biological samples wherein the sequence data comprises amplicon sequences from amplicons generated from the plurality of biological samples;”
Claim 21 recites “generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome; generating a second hash table initialized with control k-mers of the human control genome; receiving streaming sequence data from a sequence device operating to conduct a sequencing run on a plurality of biological samples, wherein the sequence data comprises amplicon sequences from amplicons generated from the plurality of biological samples; using a processor comprising a reconfigurable field-programmable gate array to execute steps comprising:”
Regarding the above cited limitations in claims 1, 12 and 21 of generating hash tables, receiving streaming sequence data, and generating sequence data. The BRI of these limitations include that they are computer-implemented, especially because the specification states that the instant claims can be performed on a computer [7] [38] [47]. Therefore, these limitations equate to receiving/transmitting data over a network, which the courts have established as WURC limitation of a generic computer in buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014).
Regarding the above cited limitation in claims 11 and 21 of administering a SARS-CoV-2 treatment and using a FPGA to perform the judicial exception of identifying k-mers and initiating sequence alignment, these limitations equate to the words “apply it”. MPEP 2106.05(f)(1) recites that limitations that equate to the words “apply it” do not provide significantly more under Step 2B.
Regarding the above cited limitation in claim 12 of generating sequence data, this limitation equates to a WURC limitation because the specification discloses various commercially available sequencing techniques such as Ion Torrent [37].
Regarding the above cited limitations in claims 1, 12 and 21 of generating hash tables, the BRI of these limitations include storing data in a generic computer because hash tables are data structures that store data in memory. As such, generating hash tables is being identified as storing information in memory, which the courts have established as a WURC function of a generic computer in Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Furthermore, regarding the data being stored in the hash tables (i.e., k-mers of a pathogen and human genome), these limitations further limit the type of data being stored, but do not alter the fact that data is being stored. Additionally, the k-mers of the pathogen and human genome equate to field of use limitations because it limits a data gathering step to a particular data source (i.e., genomes) and data type (i.e., k-mers). Limitations that equate to a field of use do not provide an inventive concept (MPEP 2106.05(h)). Nonetheless, the paragraphs below discuss the WURC nature of generating hash tables using genomic data in combination with a generic computer and FPGA.
Regarding the above cited limitations in claims 1, 12 and 21 of generating hash tables comprising genomic data in combination with a FPGA and a generic computer, these limitations equate to be WURC as taught by Aluru et al. (“Aluru”; A review of hardware acceleration for computational genomics. IEEE Design & Test 31, no. 1 (2013): 19-30; newly cited) and Donato et al. (“Donato”; BWaveR: an FPGA-accelerated genomic sequence mapper leveraging succinct data structures. (2018); newly cited). Aluru provides a survey on the use of hardware accelerators such as FPGAs in the area of biological sequence analysis, particularly in computational genomics, as well as in the field of high-throughput sequencing (abstract). Aluru teaches generating hash tables with genomic data (pg. 7, col. 1, para. 1) to perform mapping between a genome of an individual and a template genome, wherein the mapping is performed using the FPGA (pg. 6, col. 2, last para.).
Donato teaches “k-mers are used as keys for indexing a hash table, whose elements store the positions of the occurrences of the correspondent k-mers in the reference sequence, together with the symbols that precede and succeed the k-mers in those positions” (pg. 69, last para.). Donato also teachings using a CPU and FPGA together, where the CPU performs Burrows-Wheeler Transformation of the reference genome and the FPGA performs read mapping (pg. 4, para. 2).
When Aluru and Donato are taken together, they demonstrate that storing genomic data in a hash table is WURC when viewed in combination with a generic computer and a FPGA.
When these additional elements are considered individually and in combination, they do not provide an inventive concept because they equate to WURC functions/components of a generic computer and/or generic computing system and to mere instructions to apply an exception, which cannot provide significantly more. These additional elements also equate to WURC limitations of hash tables in combination with genomic data, FPGAs, and CPUs. Therefore, these additional elements do not transform the claimed judicial exception into a patent-eligible application of the judicial exception and do not amount to significantly more than the judicial exception itself (Step 2B: No).
As such, claims 1-2, 7, 10-13, 15 and 21-22 are not patent eligible.
Response to Arguments under 35 USC 101
Applicant's arguments filed 08/14/2025 have been fully considered but they are persuasive only in part.
Applicant argues that the limitations in claims 1, 12 and 21 of “generating a first hash table” and “generating a second hash table” do not recite a mental process (pg. 11, para. 2 of Applicant’s remarks). Applicant’s argument is persuasive. These newly recited limitations in claims 1, 12 and 21 do not recite a mental process and have been identified as reciting additional elements.
Applicant argues that none of the limitations in the claims equate to a mental process. Applicant also appears to specifically reference the limitations of “identifying k-mers in the sequence data” by using the hash tables as being a computer-based process and thus cannot be a mental process (pg. 11, last para. – pg. 12, last para.). Applicant’s argument is not persuasive for the following reasons:
Claims 1, 12 and 21 do recite mental processes. For example, a human is capable of performing sequence alignment, especially when there is no requirement for parallel read mapping.
Furthermore, regarding using a hash table to identify matching k-mers. A human could practically perform the operations of a hash function, as stated by Coffin (“Doing a Hash by Hand/Mathematically.” Stack Overflow; published online 2010; newly cited) on pg. 1. Also, there is no requirement for the amount of data being stored within the hash table, nor is there a requirement for a number of k-mers to be identified. As such, the BRI of identifying k-mers includes identifying at least 2 k-mers in a hash table that contains at least 2 k-mers. A human could practically perform a hash table look up with a minimal amount of data.
Applicant appears to argue that their method improves computer efficiency as a result of identifying k-mers in real-time in the sequence data (pg. 12, para. 2 – pg. 14, para. 3 of Applicant’s remarks). Applicant’s argument is not persuasive for the following reason:
It appears that Applicant argues for claim 1 that the following limitations confer the alleged improvement: “identifying, in real-time, first k-mers in the sequence data that have an exact match in the first hash table and wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer; identifying second k-mers in the sequence data that have an exact match in the second hash table; providing a positive detection output for a subset of the plurality of biological samples
However, these limitations recited directly above in claim 1 recite a judicial exception. MPEP 2106.05(a) recites “It is important to note, the judicial exception alone cannot provide the improvement.” Thus, these limitations cannot provide the improvement because they recite the judicial exception.
These limitations are similarly recited in claims 12 and 21, and thus do not provide a practical application for the same reasons recited above for claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-2, 7, 12-13 and 22 are rejected under 35 USC 103 as being unpatentable over Wu et al. (“Wu”; US 2019/0172553 A1; newly cited) in view of Panyukov et al. (“Panyukov”; International Journal of Molecular Sciences 21, no. 3 (2020): 944; newly cited), Saingam et al. (“Saingam”; Journal of microbiological methods 149 (2018): 73-79; newly cited), Kraken Manual (Kraken Taxonomic Sequence Classification System; published online 2015; newly cited), and Breitwieser et al. (“Breitwieser”; Genome biology 19, no. 1 (2018): 198; newly cited).
This rejection is newly recited and is necessitated by claim amendment.
The bold and italicized text below are the limitations of the instant claims, and the italicized text serves to map the prior art onto the instant claims.
Claim 1:
generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome;
Wu discloses generating k-mers from one or more nucleic acid sequences, wherein the k-mers are stored in a database and annotated with information such as which organism the k-mer was generated from (Figure 1) [32-37]. Para. [47] shows a k-mer associated with a specific species.
Wu teaches “if only certain regions of a sequencing output will undergo downstream analysis, only these certain regions may be targeted for quality control and thus the quality control system may be instructed or designed to generate k-mers only for these certain regions” [33] and “extracted k-mers may be mapped to annotated k-mers in the hash table using a hash function” [70] [84] (generating a first hash table that is initialized with a set of reference k-mers comprising a subset of all k-mers in a genome of a …).
Wu teaches that these k-mers are used to determine a quality control metric which is used as “a measurement of contamination of the reads … and/or an identification of one or more species from which the plurality of reads were generated” [14]. The contamination in a read refers to a contaminating organism in a sample [34] [74]. The identification of one or more species from which the plurality of reads was generated equates to a control.
However, Wu does not teach that the contaminating organisms is a pathogen, wherein the subset is selected based on k-mers with no exact match in a human control genome.
Panyukov discloses using unique k-mers as strain-specific barcodes for phylogenetic analysis and natural microbiome profiling (title). Panyukov teaches “we evaluated the ability of genus-specific k-mers to distinguish eight phylogroups of Escherichia coli (A, B1, C, E, D, F, G, B2) and assessed the presence of their unique 22-mers in clinical samples from microbiomes of four healthy people and four patients with Crohn’s disease” (abstract). Because the 22-mers are strain-specific for E. coli (abstract), they have no exact match in a human genome (wherein the subset is selected based on k-mers with no exact match in a human … genome).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Wu for detecting contaminating k-mers in a sample with the method of Panyukov by detecting pathogens such as E. coli in a human sample with pathogen-specific k-mers because the pathogen-specific k-mers would have increased the likelihood of detecting a contaminating organism. One of ordinary skill in the art would have had a reasonable expectation of success because both Wu and Panyukov are directed toward using k-mers to identify species in nucleic acid samples.
generating a second hash table initialized with control k-mers of the human control genome;
Wu teaches “extracted k-mers may be mapped to annotated k-mers in the hash table using a hash function” [70] [84], wherein the annotated k-mers are “annotated with information about the k-mer, such as species, location, and/or other information” [30]. Wu teaches using control k-mers when stating that quality metrics allow detection of a species from which the sequence reads were generated (control) and allows for detection of a contaminating species (pathogen). The hash tables are stored in the annotation database 350, which comprises one or more data tables such as that shown in Table 1, wherein the data tables can be separate hash tables [80] [84].
However, Wu does not recite detecting k-mers in human samples.
Panyukov teaches detecting strains of E. coli in human samples (abstract).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Wu for identifying a species of origin for a plurality of reads while also detecting contaminating organisms in the plurality of reads by detecting E. coli in human microbiome samples, wherein human k-mers are used to detect the species of origin and pathogen-specific k-mers are used to detect E. coli, as taught by Panyukov, because Panyukov states that E. coli is a potential pathogen in the microbiota of the human intestine (pg. 10, para. 2) and was found to be the only Enterobacteriaceae significantly increased in abundance specific to Crohn’s disease (pg. 7, last para.). This motivation from Panyukov algins with Wu because Wu states that their method can be used for diagnostic purposes [3-4]. One of ordinary skill in the art would have had a reasonable expectation of success because Wu states that k-mers can be species specific [14] [47] and because the samples used in Wu can contain multiple species [34] [65].
receiving streaming sequence data from a sequence device operating to conduct a sequencing run on a plurality of biological samples, wherein the sequence data comprises amplicon sequences from amplicons generated from the plurality of biological samples;
Wu shows in Figure 3 a sequencing input 400, which receives a plurality of sequence reads [84]. The system in Figure 3 receives reads in real-time as they are generated [89]. The plurality of sequence reads may be from one or more organisms [65].
However, Wu does not teach that the sequence data comprises amplicons.
Saingam discloses using amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogens in environmental samples. Amplicons derived from PCR (sec. 2.2) and qPCR (sec. 2.3) were sequenced with an Illumina sequences (sec. 2.6).
An invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the instant invention if there was a finding that the prior art contained a method/system that differed from the instant invention by the substitution of some components with other components, wherein the results of the substitution would have been predictable. Thus, it would have been prima facie obvious to substitute the method of generating sequence reads using any next-generation sequencing method, as taught by Wu, with using amplicon sequencing for generating sequencing reads, as taught by Saingam. The result of substituting these components would have yielded predictable results because Wu states that any next-generation sequencing method can be used [65] and because k-mers can be derived from the sequence reads of amplicon sequencing.
identifying, in real-time, first k-mers in the sequence data that have an exact match in the first hash table and wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer; identifying second k-mers in the sequence data that have an exact match in the second hash table;
Wu teaches “K-mers are extracted from reads generated during sequencing, and these extracted k-mers are used to find matching annotated k-mers in a quality control analysis” [8] and “extracted k-mers may be mapped to annotated k-mers in the hash table using a hash function” [70].
The quality control metrics are “a measurement of contamination of the reads” (first hash table) and “an identification of one or more species from which the plurality of reads were generated” (second hash table) [14]. Extracting k-mers and matching them occurs in real-time [66] [75] [89]. The match between k-mers must be an exact match (wherein the exact match excludes k-mers that differ by only 1-3 bases within the k-mer) [85].
providing a positive detection output for a subset of the plurality of biological samples based at least in part on, for an individual biological sample of the subset, a first count of exact matches of the first k-mers in the sequence data being above a first threshold and a second count of exact matches of the second k-mers in the sequence data being above a second threshold;
Wu teaches in Figure 2 that after the quality control metrics are reported 250, which includes indicating that there is a high level of contamination (positive detection output), that the system responds to the quality control metrics [76]. The reported metrics can be for at least some of the plurality of reads, wherein a sample contains DNA/RNA from one or more multiple organisms (a subset of the plurality of biological samples, for an individual biological sample of the subset) [65] (Figure 3).
However, Wu does not teach that the quality metrics of a measure of contamination (exact matches of the first k-mers in the sequence data) or an identification of one or more species from which the plurality of reads were generated (exact matches of the second k-mers in the sequence data) are above a first/second threshold.
Breitwieser discloses the software KrakenUniq that perform metagenomic classification using unique k-mer counts (abstract), and states “For the discovery of pathogens in human patients, discussed in the next section, a read count threshold of 10 and unique k-mer count threshold of 1000 eliminated many background identifications while preserving all true positives, which were discovered from as few as 15 reads” (a first count … being above a first threshold) (pg. 5, col. 2, para. 2).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the instant invention to have modified the method of Wu for detecting a high presence of a contaminating organism by requiring that a k-mer specific to the contaminating organisms, which may be a pathogen, is above a threshold count as taught by Breitwieser. The motivation for doing so is taught by Breitwieser who states that the threshold count eliminates background identification while preserving true positives pg. 5, col. 2, para. 2). One of ordinary skill in the art would have had a reasonable expectation of success for the combination because Wu permits detecting a high level of contaminating organisms [76], which would be in the form of a threshold count as taught by Breitwieser.
However, neither Breitwieser nor Wu teach detecting human k-mers based on a threshold.
The Kraken manual discusses a taxonomic classifier called Kraken that assigns taxonomic labels to short DNA reads by using k-mers within a read (pg. 1, sec. Introduction). A read may be categorized as derived from a human based upon a threshold (a second count … being above a second threshold) (pg. 3, sec. Custom Databases) (pg. 6, sec. Confidence Scoring).
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Wu and Panyukov for using k-mers to detect a pathogen in a human sample by requiring that the k-mers for the human be above a threshold, as taught by The Kraken manual, in order to verify that the human was the species of origin and that the pathogen was the contaminating organism. One of ordinary skill in the art would have had a reasonable expectation of success for the combination because these references all refer to detecting species using k-mers, wherein the combination would have resulted in detecting a pathogen in a human sample using k-mer thresholds.
terminating counting k-mers upon providing the positive detection output for each individual biological sample of the subset, wherein the positive detection output is provided while sequence data for the plurality of biological samples is still being generated by the sequence device; and
Wu discloses terminating sequencing in real time based upon the quality control metrics, particularly when the sequencing data indicates a contaminating species [89].
initiating sequence alignment of the sequence data with the genome of the pathogen of only biological samples in the subset.
Wu teaches that generated quality control metrics are used to determine whether sequence alignment should be performed [88], wherein the alignment is of the reads to a genomic sequence (claim 8).
However, Wu does not teach that the reads are aligned against a pathogen genome.
Breitwieser teaches to confirm metagenomic classification, they re-aligned all pathogen reads to individual genomes (pg. 7, col. 1, para. 1).
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Wu by requiring an alignment step of reads to a pathogen genome when the contaminating organism is detected in order to confirm a metagenomic classification, as taught by Breitwieser. One of ordinary skill in the art would have had a reasonable expectation of success because both Wu and Breitwieser are directed towards sequencing alignment.
Claim 12:
generating a first h