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 .
Status of Claims
Claims 1-23 are pending. All have been examined on the merits.
Priority
Acknowledgement is made of the provisional application filed November 29th, 2021. This date is considered the effective filing date.
Information Disclosure Statement
The information disclosure statements filed September 20th, 2023 are acknowledged. A signed copy of the corresponding 1449 form has been included with this Office action.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 11 is 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 following terms render the claims indefinite:
“…at least some of the target locations…”, claims 5, 11, and 20.
“…at least some of the target locations”, as claimed is not explicitly defined and is a relative term that amounts to an approximation. See MPEP 2173.05(b). Paragraph 0012 of the specification states:
“In these and other embodiments, methods can also include: computing, for each of a plurality of pairs of locations in the genetic sequence, a linkage disequilibrium parameter; and selecting at least some of the target locations based on the linkage disequilibrium parameter. For example, the target locations can be selected such that each target location has a linkage disequilibrium with respect to at least one other target location that is above a threshold.”
Therefore, for the purposes of speedy examination, “at least some of the target locations” is interpreted as at least one target location.
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 1-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea and law of nature without significantly more.
As stated in the above 35 U.S.C. 112(b) claim rejection, for the purposes of speedy examination, “at least some of the target locations” is interpreted as at least one target location.
Step 2A, Prong 1
In accordance with MPEP § 2106, claims found to recite statutory subject matter (claim 1-23 are drawn to a method) (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 limitations that equate to an abstract idea, and law of nature.
The law of nature and natural phenomenon exceptions reflect the Supreme Court's view that the basic tools of scientific and technological work are not patentable, because the "manifestations of laws of nature" are "part of the storehouse of knowledge," "free to all men and reserved exclusively to none." Funk Bros. Seed Co. v. Kalo Inoculant Co., 333 U.S. 127, 130, 76 USPQ 280, 281 (1948). Thus, "a new mineral discovered in the earth or a new plant found in the wild is not patentable subject matter" under Section 101. Diamond v. Chakrabarty, 447 U.S. 303, 309, 206 USPQ 193, 197 (1980). "Likewise, Einstein could not patent his celebrated law that E=mc2; nor could Newton have patented the law of gravity." Id. Nor can one patent "a novel and useful mathematical formula," Parker v. Flook, 437 U.S. 584, 585, 198 USPQ 193, 195 (1978); electromagnetism or steam power, O’Reilly v. Morse, 56 U.S. (15 How.) 62, 113-114 (1853); or "[t]he qualities of ... bacteria, ... the heat of the sun, electricity, or the qualities of metals," Funk, 333 U.S. at 130, 76 USPQ at 281; see also Le Roy v. Tatham, 55 U.S. (14 How.) 156, 175 (1853). See MPEP 2106.04.
The enumerated groupings of abstract ideas are defined as:
1) Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations (see MPEP § 2106.04(a)(2), subsection I);
2) Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) (see MPEP § 2106.04(a)(2), subsection II); and
3) Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III).
In the instant application, the claims recite the following limitations that equate to an abstract idea or law of nature:
Claim 1 and 12 recite:
“…determining, for each of a plurality of target locations in the genetic sequence, a location-specific probability score for each of a plurality of synonymous codons…”, which is a mental process, i.e., the steps can be completed with pen and paper,
“selecting, based on the location-specific probability scores for the target location, a replacement codon”, mental step.
“replacing, in a genomic molecule, an existing codon at the target location with the replacement codon.”, mental step.
Claim 2 states:
“determining a fraction of the samples of the genetic sequence that include the particular synonymous codon at the target segment”, mental step.
Claim 3 states: “the replacement codon has a highest probability score among the synonymous codons at the target segment.”, which further limits claim 1.
Claim 4 states: “the replacement codon has a lowest probability score among the synonymous codons at the target segment.”, which further limits claim 1.
Claim 5 states:
“computing, for each of a plurality of pairs of locations in the genetic sequence, a linkage disequilibrium parameter”, which is a mathematical process: a mathematical calculation.
“selecting at least some of the target locations based on the linkage disequilibrium parameter.”, mental step.
Claim 6 states: “the target locations are selected such that each target location has a linkage disequilibrium with respect to at least one other target location that is above a threshold.”, which further limits claim 5
Claim 7 states: “the target locations include every location for which two or more synonymous codons exist”, which further limits claim 1.
Claim 8 and 23 state: “the target organism is a pathogen.”, which is a law of nature, i.e. pathogens naturally exist in nature; this claim further limits claim 1 and 12 respectively.
Claim 9 states:
“the location-specific probability scores are determined based on samples of the virus genetic sequence obtained from host organisms belonging to a first species”, which limits claim 1.
Claim 10 states:
“determining a global probability score for each of a plurality of synonymous codons based on samples of the virus genetic sequence obtained from host organisms belonging to a second species,” mental step.
“…wherein the replacement codon is selected based in part on the location-specific probability scores and based in part on the global probability scores,” which further limits claim 9.
Claim 11 states:
“computing, for each of a plurality of pairs of locations in the genetic sequence, a linkage disequilibrium parameter;”, mental step,
“selecting at least some of the target locations based on the linkage disequilibrium parameter.”, mental step.
Claim 12 states:
“obtaining a plurality of samples of a genetic sequence of a target organism…”, which further limits claim 12,
“determining, for each of a plurality of target segments in the genetic sequence, a probability score for each of a set of synonymous segments…”, which is a mathematical concept of a mathematical calculation
“…wherein a synonymous segment is a segment obtained by replacing a k-mer in the target segment with a different k-mer without affecting a corresponding amino acid sequence, wherein each target segment has a length s and…”, which further limits claim 12,
“…selecting, based on the probability scores for the target segment, a replacement segment from the set of synonymous segments…”, mental step
“replacing, in a genomic molecule, the target segment with the replacement segment…”, JE?
Claim 13 states: “…determining a sum of available k-mers in the segment, weighted by the k-mer frequencies observed in the samples.”, mathematical calculation.
Claims 14-19 further limit claim 12 and state (clm. Number adjacent):
“…the replacement segment has a highest probability score among the synonymous segments at the target segment…” (14)
“…the replacement segment has a lowest probability score among the synonymous segments at the target segment.” (15)
“…k = 3 and each k-mer corresponds to a codon… (16)
“…k = 2 and each k-mer corresponds to a dinucleotide…” (17)
“…k = 6…” (18)
“…each k-mer corresponds to a pair of adjacent codons…” (19)
Claim 20 states:
“… computing, for each of a plurality of pairs of segments in the genetic sequence, a linkage disequilibrium parameter…”, mathematical calculation
“…selecting at least some of the target segments based on the linkage disequilibrium parameter…”, mental step.
Claim 21 states: “…the target segments are selected such that each target segment has a linkage disequilibrium with respect to at least one other target segment that is above a threshold…” , which further limits claim 12.
Claim 22 states: “…the target segments include every segment for which two or more synonymous segments exist…”, which further limits claim 12.
The claims recite an abstract idea of analyzing and modifying genomic sequences (See MPEP 2106.07(a)).
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. Additionally, some limitations such as claim 8, disclose a law of nature as described above.
Furthermore, there are no additional limitations that indicate that the disclosed methods require anything other than carrying out the recited mental process or mathematical concept in a generic computer environment. 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) 1-23 recite(s) an abstract idea/law of nature/natural phenomenon (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). 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. Specifically, the claims recite the following additional elements:
Claim 1 and 12 recite:
“…obtaining a plurality of samples of a genetic sequence of a target organism…”, which further limit claims 1 and 12
Claim 3 states: “the replacement codon has a highest probability score among the synonymous codons at the target segment.”, which further limits claim 1.
Claim 4 states: “the replacement codon has a lowest probability score among the synonymous codons at the target segment.”, which further limits claim 1.
Claim 6 states: “the target locations are selected such that each target location has a linkage disequilibrium with respect to at least one other target location that is above a threshold.”, which further limits claim 5
Claim 7 states: “the target locations include every location for which two or more synonymous codons exist”, which further limits claim 1.
Claim 8 and 23 state: “the target organism is a pathogen.”, this claim further limits claim 1 and 12 respectively.
Claim 9 states:
“the target organism is a virus”, further limiting claim 1.
“the location-specific probability scores are determined based on samples of the virus genetic sequence obtained from host organisms belonging to a first species”, which further limits claim 1.
Claim 10 states:
“…wherein the replacement codon is selected based in part on the location-specific probability scores and based in part on the global probability scores,” which further limits claim 9.
Claim 12 states:
“obtaining a plurality of samples of a genetic sequence of a target organism…”, which further limits claim 12,
“…wherein a synonymous segment is a segment obtained by replacing a k-mer in the target segment with a different k-mer without affecting a corresponding amino acid sequence, wherein each target segment has a length s and…”, which further limits claim 12,
“replacing, in a genomic molecule, the target segment with the replacement segment…”, which further limits claim 12.
Claims 14-19 further limit claim 12 and state (clm. Number adjacent):
“…the replacement segment has a highest probability score among the synonymous segments at the target segment…” (14)
“…the replacement segment has a lowest probability score among the synonymous segments at the target segment.” (15)
“…k = 3 and each k-mer corresponds to a codon… (16)
“…k = 2 and each k-mer corresponds to a dinucleotide…” (17)
“…k = 6…” (18)
“…each k-mer corresponds to a pair of adjacent codons…” (19)
Claim 21 states: “…the target segments are selected such that each target segment has a linkage disequilibrium with respect to at least one other target segment that is above a threshold…” , which further limits claim 12.
Claim 22 states: “…the target segments include every segment for which two or more synonymous segments exist…”, which further limits claim 12.
There are no limitations that indicate that the claimed analysis engine or the formats of the provided data require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. As such, claims 1-20 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). 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 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 1-23 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 7, 8, 12, 14-16, 18, 19, 22 and 23 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kuznetsov et al (WO 2017218727A1). as evidenced by Barendt et al ( ACS Chem Biol. 2013 May 17;8(5):958-66.).
In regards to claim 1 (re: determining, for each of a plurality of target locations in the genetic sequence, a location-specific probability score for each of a plurality of synonymous codons; and for each target location: selecting, based on the location-specific probability scores for the target location, a replacement codon; and replacing, in a genomic molecule, an existing codon at the target location with the replacement codon.), Kuznetsov et al. discloses method for designing genomes implemented by a computing platform, the method comprising: receiving, as an input at a computing platform, data for a known genome and a list of alleles to be replaced in the known genome (clm. 1, Spec: as relates to E. Coli genome (“As an example, Tables 1 and 2 provide further examples of rules and constraints that may be implemented for genome design (e.g., for design and synthesis of a radically recoded E. coli genome)”), re: obtaining a plurality of samples of a genetic sequence of a target organism).
Kuznetsov et al. further discloses generating alternative gene sequences for a genome design, applying rules to the alternative gene sequences, defining scores for each alternative gene sequence based on a weighted combination of the scores, and selecting at least one alternative gene sequence as the genome design based on the scoring (Abstract, clm. 1). Kuznetsov et al. additionally states that the scoring and genome modifications to the genome design will satisfy a predetermined design objective and to increase probability of viability (clm. 24), inclusive of synonymous codon replacements as disclosed in claims 30, 42, and Fig. 22 (which discloses ribosomal binding site strength success post-codon replacement. Under the broadest reasonable interpretation, a score associated with metrics for modifying a genomic sequence at a specific location (an allele, as disclosed in clm. 1, or a codon as disclosed I clm. 36) in an organism (E. Coli) such that the organism increases its viability probabilistically reads on a location-specific probability score. Kuznetsov et al. additionally discloses embodiments in which a scoring sub-module maintains biological constraints, stating in the specification:
“The genome design module 201 may also utilize a scoring sub-module 208, and the genome design module 201 may be configured to select synonymous codons that allow the resulting sequence to best adhere to biological constraints 205 and/or synthesis constraints 206.” Biological constraints are described in Table 1. Genome Design Rules (re: clm. 1, determining, for each of a plurality of target locations in the genetic sequence, a location-specific probability score for each of a plurality of synonymous codons…).
Kuznetsov et al. further discloses selecting a replacement codon for a location in a genome (based on the scoring for probability of viability as previously disclosed in claim 24) in claim 36 (re: clm. 1, or each target location: selecting, based on the location-specific probability scores for the target location, a replacement codon; and replacing, in a genomic molecule, an existing codon at the target location with the replacement codon.). Therefore, Kuznetsov et al. anticipates claim 1.
Regarding claim 2 (determining the probability score for a particular synonymous codon includes determining a fraction of the samples of the genetic sequence that include the particular synonymous codon at the target segment.), Kuznetsov et al. states in the specification experiments of genetically modified E. Coli. using the gene sequence modification method disclosed in claim 1. In the specification Kuznetsov states: “Each randomized population was amplified using PCR primers allowing for specific amplification of strains incorporating the CRISPR-site modifications. For each gene and each data point, reads were aligned to the reference genome and frequencies of each codon were computed.” “Frequences of codons” (derived from modified bacterial strains) read on fractions of the samples of the genetic sequence including a synonymous codon at the target segment. Kuznetsov et al. anticipates claim 2.
Regarding claim 3 (…the replacement codon has a highest probability score among the synonymous codons at the target segment.), Kuznetsov et al. states the genetic modification viability probability scoring metric is based on assigning scores in which higher scores indicate less deviation from the plurality of rules or constraints or conditions or parameters or features, which reads on a replacement codon having the highest probability score amongst target synonymous codons (clm. 9). Therefore, Kuznetsov et al. anticipates claim 3.
Regarding claim 4, (re: …the replacement codon has a lowest probability score among the synonymous codons at the target segment.), Kuznetsov et al. states the genetic modification viability probability scoring metric scoring is further based on assigning scores in which lower scores indicate less deviation from the plurality of rules or constraints or conditions or parameters or features, which reads on a replacement codon having a lowest probability score amongst synonymous codons. Therefore, Kuznetsov et al. anticipates claim 4.
Regarding claims 7 and 12 (re: …the target locations/[segments] include every location/[segment] for which two or more synonymous codons exist.), Kuznetsov et al. states in their specification a detail from experimental design in validation of their method as applied to E.Coli in which Kuznetsov et al. designs oligonucleotides, stating: “The design phase involved identification of 123 AGR codons in the essential genes of Escherichia coli. MAGE oligos were designed to replace all instances of these AGR codons with the synonymous CGU codon. ” As Kuznetsov et al. discloses target locations including all instances of specific regions where synonymous codons could exist, and additionally states the replacement could occur genome wide, stating:
“The present disclosure provides an engineered organism comprising a recoded genome wherein a particular sense codon in a template genome is changed genome-wide to alternative codons.”, this method reads on claim 7. Kuznetsov et al. anticipates claim 7.
Regarding claim 8 and 23 (re: … wherein the target organism is a pathogen. ), Kuznetsov et al. discloses the known genome sequence comprises a wild-type E. coli genome, a pathogen (clm. 2). Kuznetsov et al. anticipates claims 8 and 23.
Regarding claim 12 (re: obtaining a plurality of samples of a genetic sequence of a target organism; determining, for each of a plurality of target segments in the genetic sequence, a probability score for each of a set of synonymous segments, wherein a synonymous segment is a segment obtained by replacing a k-mer in the target segment with a different k-mer without affecting a corresponding amino acid sequence, wherein each target segment has a length s and s >=k; and selecting, based on the probability scores for the target segment, a replacement segment from the set of synonymous segments; and replacing, in a genomic molecule, the target segment with the replacement segment.), Kuznetsov et al. teaches obtaining a plurality of samples in a genetic sequence of a target organism as disclosed in the regard of claim 1 above. Kuznetsov et al. additionally discloses replacing a k-mer in a target segment with a different k-mer without affecting a corresponding amino acid sequence, as Kuznetsov et al. discloses in their specification:
“The disclosure provides an engineered organism comprising a recoded genome wherein a particular sense codon at all instances within a gene or non-coding motif in a template genome is changed to alternative codons. “, which addresses codon replacement and;
“According to one aspect, the particular sense codon is a member selected from the group consisting of AGG, AGA, AGC, AGU, UUG, and UUA. “, which is a group of k-mers. Synonymous codons as disclosed in claim 42, do not affect the corresponding amino acid sequence as Kuznetosov et al. disclose rules for genome modifications in claim 6, stating:
“the plurality of rules or constraints or conditions or parameters or features comprises at least one of: preserving one or more ribosome binding site (RBS)-like motifs in the genome design;
removing forbidden restriction enzyme sites for the genome design; preserving 5 ' mRNA secondary structure of genes in the known genome; preserving RNA secondary structure in the known genome; preserving regulatory motifs in the genome design; preserving known sequence motifs in the genome design; applying phylogenetic conservation for the genome design; and satisfying GC requirements for the genome design.” Kuznetsov et al. also discloses in the specification that the scoring sub-module assigns scores to changes in genes, ranking changes by desired outcomes (viability):
“ In some embodiments, the scoring sub-module 208 may assign a quantitative score to every possible change to a gene or genome. This scoring may allow ranking and prioritizing designs that achieve a desired genotypic or phenotypic outcome. The scoring, ranking, and prioritization features may comprise core features of the software for the genome design module 201.” As previously disclosed, Kuznetsov et al. discloses an embodiment in the specification that accounts for bioilogcial constraints leading to increased probability of viability in a genetically modified sample (Table 1, Specification, re: clm. 12…, wherein a synonymous segment is a segment obtained by replacing a k-mer in the target segment with a different k-mer without affecting a corresponding amino acid sequence, wherein each target segment has a length s and s >=k; and selecting, based on the probability scores for the target segment, a replacement segment from the set of synonymous segments; and replacing, in a genomic molecule, the target segment with the replacement segment.). As Kuznetsov et al. discloses synonymous codons that are selected such that they do not affect an amino acid sequence, Kuznetsov et al. anticipates claim 12.
Regarding claims 14 and 15 (re: wherein the replacement segment has a highest/lowest probability score among the synonymous segments at the target segment.), Kuznetsov et al. discloses on claims 9 and 10:
“…the scoring is further based on assigning scores in which [higher]/[lower] scores indicate less deviation from the plurality of rules or constraints or conditions or parameters or features.” Therefore, Kuznetsov et al. anticipates claims 14 and 15.
Regarding claims 16 and 18 (re: clm. 16, … wherein k = 3 and each k-mer corresponds to a codonm clm. 18, …wherein k = 6.), as disclosed in regard to claim 12, Kuznetsov et al.’s specification states: ““According to one aspect, the particular sense codon is a member selected from the group consisting of AGG, AGA, AGC, AGU, UUG, and UUA. “, which is a group of k-mers and codons (re: clm. 16). Additionally, Kuznetsov et al. claims on claim 30: “An engineered organism comprising a recoded genome wherein a particular sense codon at all instances within a gene or non-coding motif in a template genome is changed to alternative codons”, and then further claims “The engineered organism of claim 30 wherein the non-coding motif is a ribosome binding site motif” (clm. 33). A ribosome binding site motif is six bases long, as evidenced by Barendt et al., who state:
“The 5′ untranslated region (5′ UTR) of messenger RNA (mRNA) is one of the major determinants of translational efficiency. This region often contains ribosome binding sites (RBSs), binding sites for inhibitory or stimulatory trans-acting factors, and secondary structural features that may affect access to the start codon. In prokaryotes, the 5′ UTR frequently contains some variation of the Shine-Dalgarno (SD) consensus sequence, 5′-GGAGGU-3′, …”
Therefore, Kuznetsov et al. teaches selecting a codon for replacement which may be a ribosome binding motif which is six bases long, reading on k = 6. Kuznetsov et al. anticipates claims 16 and 18.
In regard to claim 19, Kuznetsov et al. discloses an experiment in the specification, stating:
“The candidate set contains targets with at least one problem in the design (i.e. the worst design is bad). At least two of these targets introduce non-synonymous mutations into overlapping genes, allowing testing the aspect of the software that balances amino acid sense against preservation of regulatory gene expression signals. Plate 2: Combos of codon changes and adjacent degenerate tests
From among the single changes, those that occur adjacent to others within a 90-basepair oligonucleotide size were combined into a new set of sub-experiments that tested all combinations of adjacent oligos. There were 62 such targets. “
Kuznetsov discloses in the aforementioned experiment codon changes that occurred adjacent to others. Therefore, Kuznetsov et al. anticipates claim 19.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 5, 6, 20, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Kuznetsov et al. as evidenced by Barendt et al. as applied to claims 1-4, 7, 8, 12, 14-16, 18, 19, 22 and 23, above in view of Venkata Kishore et al. (US 8170805B2).
Kuznetsov et al. as evidenced by Barendt et al. is applied to claims 1-4, 7, 8, 12, 14-16, 18, 19, 22 and 23 above.
Regarding claims 5 and 20, for the purposes of speedy examination, “at least some of the target locations” is interpreted as at least one target location.
Regarding claims 5 and 20, Kuznetsov et al. does not teach computing a linkage disequilibrium parameter (re: clm. 5, 20 … computing, for each of a plurality of pairs of segments in the genetic sequence, a linkage disequilibrium parameter; and selecting at least some of the target segments based on the linkage disequilibrium parameter.)
Kishore et al. teaches a method of identifying a genetic marker associated with a trait of interest in a nested population of non-human organisms. In specification, Kishore et al. discloses a genome-wide association analysis, stating:
“The methods of the present invention comprise identifying or validating a candidate marker by performing genome-wide association analysis (GWA) on a population of organisms (e.g., plant or animal), and comparing any positively-correlated markers in the GWA analysis with markers determined to have a positive correlation with the trait of interest in the same species of the organism using one or both of nested association mapping (NAM) and expression QTL (eQTL) analysis.”
Kishore et al. explicitly defines the utility of linkage disequilibrium (re: clm. 5,20…computing, for each of a plurality of pairs of locations in the genetic sequence, a linkage disequilibrium parameter; and selecting at least some of the target locations based on the linkage disequilibrium parameter) at locations in a genome (single nucleotide polymorphisms) which are selected for further analysis, stating in the specification:
“Genetics data have been used in the field of trait analysis in order to attempt to identify the genes that affect such traits. A key development in such pursuits has been the development of large collections of molecular/genetic markers, which can be used to construct detailed genetic maps of species. These maps are used in Quantitative Trait Locus (QTL) mapping methodologies such as single-marker mapping, interval mapping, composite interval mapping and multiple trait mapping. QTL mapping methodologies provide statistical analysis of the association between phenotypes and genotypes for the purpose of understanding and dissecting the regions of a genome that affect traits.
Association mapping makes use of markers within candidate genes, which are genes that are thought to be functionally involved in development of the trait because of information such as biochemistry, physiology, transcriptional profiling and reverse genetic experiments in model organisms. In the simplest definition, association mapping is the utility of linkage disequilibrium, also known as gametic phase disequilibrium, in natural populations to identify markers with significant allele frequency differences between individuals with the trait of interest and individuals not exhibiting the trait of interest. “ Therefore, Kishore et al. teaches computing, for each of a plurality of pairs of locations in the genetic sequence, a linkage disequilibrium parameter; and selecting at least some of the target locations based on the linkage disequilibrium parameter.
In KSR Int 'l v. Teleflex, the Supreme Court, in rejecting the rigid application of the teaching, suggestion, and motivation test by the Federal Circuit, indicated that “The principles underlying [earlier] cases are instructive when the question is whether a patent claiming the combination of elements of prior art is obvious. When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.” KSR Int'l v. Teleflex lnc., 127 S. Ct. 1727, 1740 (2007).
Applying the KSR standard to Kishore et al. and Kuznetsov et al. the examiner concludes that the combination of the method of identifying a genetic marker associated with a trait of interest in a nested population of non-human organisms according to Kishore et al. with the method for designing genomes implemented by a computing platform as disclosed by Kuznetsov et al. represents some teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to predictably lead to a method of identifying a genetic marker associated with a trait of interest and designing a genome using a linkage disequilibrium parameter, selecting at least some of the target locations based on the linkage disequilibrium parameter.
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have been motivated to combine the teachings of Kuznetsov et al. and Kishore et al. because contributing Kishore et al’s teaching to Kuznetsov et al.’s teaching would have made Kuznetsov et al.’s method stronger by providing more data via annotation of linked genomic loci. In support of this motivation, Kuznetsov et al. explicitly invites additional modifications to genome design in the future vis their disclosure in the specification: “Aspects described herein may also include providing information about designed genomes based on a set of constraints and/or rules and recommending modifications that may yield phenotypic improvements in future genome design.”
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because Kuznetsov et al. and Kishore et al. are both computational methods of analyzing and quantitatively assessing genomes. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Regarding claims 6 and 21, Kishore et al. explicitly defines the utility of linkage disequilibrium at locations in a genome (single nucleotide polymorphisms) which are selected for further analysis (specification), and additionally quantitatively assesses genetic markers-trait relationships in consideration of linkage disequilibrium via a single marker regression model (clm. 1, re: clm. 6, 21 … target locations are selected such that each target location has a linkage disequilibrium…).
Applying the KSR standard to Kishore et al. and Kuznetsov et al. the examiner concludes that the combination of the method of identifying a genetic marker associated with a trait of interest in a nested population of non-human organisms according to Kishore et al. with the method for designing genomes implemented by a computing platform as disclosed by Kuznetsov et al. represents some teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to predictably lead to a method of identifying a genetic marker associated with a trait of interest and designing a genome using a linkage disequilibrium parameter, and targeting locations in a genetic sequence with linkage disequilibrium in respect to one other target genomic location above a threshold.
One of ordinary skill in the art of bioinformatics would be motivated to combine the teachings of Kishore et al. with the teachings of Kuznetsov et al. because the combination would result in a stronger method capable of providing more data and/or selections of target loci with respect to specific genomic loci.
In support of this motivation, Kuznetsov et al. invites additional modifications to genome design in the future via their disclosure in the specification: “Aspects described herein may also include providing information about designed genomes based on a set of constraints and/or rules and recommending modifications that may yield phenotypic improvements in future genome design.”
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because both methods, as taught by Kishore et al. and Kuznetsov et al., utilize genome analysis, and in the process provide complementary sequence-annotation data to each other. Kishore et al. states in their specification that their method could be used “for genome-based diagnostic and selection techniques…” Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Claim(s) 9 and 10, 11, are rejected under 35 U.S.C. 103 as being unpatentable over Kuznetsov et al. as evidenced by Barendt et al. as applied to claims 1-8, 12, 14-16, 18, 19, 20-23 above, in view of Kishore et al. as applied to claim 5, 6, 20, and 21 above, and in view of Richards et al. (US20140024541A1)
Kuznetsov et al. as evidenced by Barendt et al. and in view of Kishore et al. is applied to claims 1-8, 12, 14-16, 18, 19, 20-23 above.
Regarding claims 9 and 10, Kuznetsov et al. teaches a location-specific probability score as related to a replacement codon (as addressed in the above 35 U.S.C. 102(a)(2) rejection) (re: clm. 9), and determining a global probability score for synonymous codons. Kuznetsov et al. discloses in their specification that: “a total score for an alternative gene sequence comprising an allele choice may be computed”, and “ The weights and scoring may also be applied globally or may be context-specific.” This reads on a replacement codon being selected based on location-specific and global probability scores (re: clm. 10, …determining a global probability score for each of a plurality of synonymous codons…, wherein the replacement codon is selected based in part on the location-specific probability scores and based in part on the global probability scores).
Regarding claims 9 and 10, Kuznetsov et al. does not teach a method examining a virus or on samples of a virus genetic sequence obtained from host organisms belonging to a first species (re: clm. 9, …the target organism is a virus and the location-specific probability scores are determined based on samples of the virus genetic sequence obtained from host organisms belonging to a first species, … clm. 10, …based on samples of the virus genetic sequence obtained from host organisms belonging to a second species).
Richards et al. teaches a method for sequencing a plurality of different target polynucleotides in one or more samples from one or more subjects. Richards et al. states in their specification that target polynucleotides can come from viruses, stating:
“Samples from which the target polynucleotides are derived can comprise multiple samples from the same individual, samples from different individuals, or combinations thereof. In some embodiments, a sample comprises a plurality of polynucleotides from a single individual. In some embodiments, a sample comprises a plurality of polynucleotides from two or more individuals. An individual is any organism or portion thereof from which target polynucleotides can be derived, non-limiting examples of which include plants, animals, fungi, protists, monerans, viruses, mitochondria, and chloroplasts.” This reads on obtaining a virus sample from a host organism belonging to a first or second species, as target polynucleotides can comprise multiple samples from combinations of the same or different individuals. (re: clm. 9, … the target organism is a virus…samples of the virus genetic sequence obtained from host organisms belonging to a first species, … clm. 10, … samples of the virus genetic sequence obtained from host organisms belonging to a second species…)
Applying the KSR standard to Richards et al., Kishore et al. and Kuznetsov et al. the examiner concludes that the combination of the method for sequencing a plurality of different target polynucleotides in one or more samples from one or more subjects according to Richards et al. with the method for designing genomes implemented by a computing platform as disclosed by Kuznetsov et al. represents some teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to predictably lead to a method of identifying a genetic marker associated with a trait of interest and designing a genome using a virus genetic sequence obtained from a host organism belonging to a first species.
One of ordinary skill in the art of bioinformatics would be motivated to combine the teachings of Kishore et al. with the teachings of Kuznetsov et al. and Richards et al. because the combination would result in a stronger method of identifying a genetic marker associated with a trait of interest and designing a genome.
In support of this motivation, As previously stated, Kuznetsov et al. invites additional modifications to genome design in the future.
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because contributing Richard et al’s teaching to Kuznetsov et al.’s teaching would have made Kuznetsov et al.’s method stronger via the provision of a method to examine virus genomic loci obtained from a host, which may contain codons for non-standard amino acids.
In support of this expectation, Richards et al. states in the specification:
“ The following are non limiting examples of polynucleotides: coding or non-coding regions of a gene or gene fragment, intergenic DNA, loci (locus) defined from linkage analysis, exons, introns, messenger RNA (mRNA), transfer RNA, ribosomal RNA, short interfering RNA (siRNA), short-hairpin RNA (shRNA), micro-RNA (miRNA), small nucleolar RNA, ribozymes, cDNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, adapters, and primers. “
Kuznetsov et al. additionally discloses in claim 14:
“…wherein the genome design comprises one of a genetic code with minor modifications from a canonical genome code, a radically redefined genetic code, a novel genetic code, or a genetic code wherein codons map to non-standard amino acids.”
Therefore, one of ordinary skill in the art of bioinformatics could modify the high-throughput polynucleotide sequencing method of Richards et al. as Kuznetsov et al. details methods to analyze and score codons related to non-standard amino acids, and said method could be applied to the plurality of examples, including viruses, discloses by Richards et al. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Regarding claim 11, for the purposes of speedy examination, “at least some of the target locations” is interpreted as at least one target location.
Regarding claim 11, Kuznetsov et al. does not teach computing a linkage disequilibrium parameter (re: clm. 11, … computing, for each of a plurality of pairs of segments in the genetic sequence, a linkage disequilibrium parameter; and selecting at least some of the target segments based on the linkage disequilibrium parameter.)
Kishore et al. teaches a method of identifying a genetic marker associated with a trait of interest in a nested population of non-human organisms. In specification, Kishore et al. discloses a genome-wide association analysis, stating:
“The methods of the present invention comprise identifying or validating a candidate marker by performing genome-wide association analysis (GWA) on a population of organisms (e.g., plant or animal), and comparing any positively-correlated markers in the GWA analysis with markers determined to have a positive correlation with the trait of interest in the same species of the organism using one or both of nested association mapping (NAM) and expression QTL (eQTL) analysis.”
Kishore et al. explicitly defines the utility of linkage disequilibrium (re: clm. 11…computing, for each of a plurality of pairs of locations in the genetic sequence, a linkage disequilibrium parameter; and selecting at least some of the target locations based on the linkage disequilibrium parameter) at locations in a genome (single nucleotide polymorphisms) which are selected for further analysis, stating in the specification:
“Genetics data have been used in the field of trait analysis in order to attempt to identify the genes that affect such traits. A key development in such pursuits has been the development of large collections of molecular/genetic markers, which can be used to construct detailed genetic maps of species. These maps are used in Quantitative Trait Locus (QTL) mapping methodologies such as single-marker mapping, interval mapping, composite interval mapping and multiple trait mapping. QTL mapping methodologies provide statistical analysis of the association between phenotypes and genotypes for the purpose of understanding and dissecting the regions of a genome that affect traits.
Association mapping makes use of markers within candidate genes, which are genes that are thought to be functionally involved in development of the trait because of information such as biochemistry, physiology, transcriptional profiling and reverse genetic experiments in model organisms. In the simplest definition, association mapping is the utility of linkage disequilibrium, also known as gametic phase disequilibrium, in natural populations to identify markers with significant allele frequency differences between individuals with the trait of interest and individuals not exhibiting the trait of interest. “ Therefore, Kishore et al. teaches computing, for each of a plurality of pairs of locations in the genetic sequence, a linkage disequilibrium parameter; and selecting at least some of the target locations based on the linkage disequilibrium parameter.
Applying the KSR standard to Kishore et al., Kuznetsov et al. and Richards et al. the examiner concludes that the combination of the method of identifying a genetic marker associated with a trait of interest in a nested population of non-human organisms according to Kishore et al. with the method for designing genomes implemented by a computing platform as disclosed by Kuznetsov et al. and the a method for sequencing a plurality of different target polynucleotides in one or more samples from one or more subjects as taught by Richards et al. represents some teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to predictably lead to a method of identifying a genetic marker associated with a trait of interest and designing a genome using a linkage disequilibrium parameter, selecting at least some of the target locations based on the linkage disequilibrium parameter.
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have been motivated to combine the teachings of Kuznetsov et al. and Kishore et al. because contributing Kishore et al’s teaching to Kuznetsov et al.’s teaching would have made Kuznetsov et al.’s method stronger by providing more data via annotation of linked genomic loci. In support of this motivation, Kuznetsov et al. explicitly invites additional modifications to genome design in the future vis their disclosure in the specification: “Aspects described herein may also include providing information about designed genomes based on a set of constraints and/or rules and recommending modifications that may yield phenotypic improvements in future genome design.”
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because Kuznetsov et al. , Richards et al. and Kishore et al. are both computational methods of analyzing and quantitatively assessing genomes. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Claim(s) 13 are rejected under 35 U.S.C. 103 as being unpatentable over Kuznetsov et al. as evidenced by Barendt et al. as applied to claims 1-12, 14-16, and 18-23 in view of Deorowicz et al. (Bioinformatics, 31(10), 2015, 1569–1576).
Kuznetsov et al. as evidenced by Barendt et al. is applied to claims 1-12, 14-16, and 18-23 above.
Kuznetsov et al. teaches synonymous codons (which read on k-mers ) and frequency measurements as discussed in the above 35 U.S.C. 102(a)(2) rejection above, and explicitly in Fig. 5B, which “…illustrates codon frequencies…) and in the specification which states:
“…For each sub-experiment, the relative frequency of each codon was calculated…” (Spec; re: clm. 13, …probability score…weighted by the k-mer frequencies observed in the samples)
Kuznetsov et al. does not explicitly teach determining a sum of available k-mers in a segment (re: clm. 13).
Deorowicz et al. teaches k-mer counting, including summing bins of k-mers as disclosed on pg. 1570, sec. 2.2 (re: clm. 13, …determining a sum of available k-mers in the segment…).
Richards et al. does not teach determining location-specific probability scores (re: clm. 9 …. and the location-specific probability scores are determined based on…, re: clm. 10, …determining a global probability score for each of a plurality of synonymous codons…)
Applying the KSR standard to Deorowicz et al. and Kuznetsov et al. the examiner concludes that the combination of the method for sequencing a plurality of different target polynucleotides in one or more samples from one or more subjects according to Richards et al. with the method for designing genomes implemented by a computing platform as disclosed by Kuznetsov et al. represents some teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to predictably lead to a computational method of designing a genome with a synonymous segment including determining the sum of available k-mers in the segment and weighted by the k-mer frequencies within the samples.
One of ordinary skill in the art of bioinformatics would be motivated to modify the genome design method of Kuznetsov et al. with the addition of a summation of k-mers as disclosed by Deorowicz et al. as the combination would have made Kuznetsov et al.’s method stronger via the provision of more annotations (summation of k-mers).
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because, As previously stated, Kuznetsov et al. invites additional modifications to genome design in the future via their disclosure in the specification. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Claim(s) 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kuznetsov et al. as evidenced by Barendt et al. as applied to 1-16, and 18-23 in view of Coleman et al. (US12178869B2).
Kuznetsov et al. as evidenced by Barendt et al. is applied to 1-16, and 18-23 above.
Kuznetsov et al. does not teach k-mers corresponding to a dinucleotide, or k=2.
Coleman et al. teaches the use of designed recombinant viruses for the treatment of various forms of malignant tumors. The recombinant viruses of the invention are those in which one or more regions of the wild type virus was exchanged with a synthetic recoded sequence that reduces the codon pair score relative to human codon pair bias, or that increase the number for CpG di-nucleotides, or that increases the number of UpA di-nucleotides (abstract, re: clm. 17, … wherein k = 2 and each k-mer corresponds to a dinucleotide). Coleman et al. states in the specification:
“The present invention provides a modified virus that comprises a modified viral genome containing nucleotide substitutions engineered in one or more (e.g., 1, 2, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50, or more) locations in the genome, wherein the substitutions introduce a plurality of synonymous codons into the genome. This substitution of synonymous codons alters various parameters, including codon bias, codon pair bias, density of deoptimized codons and deoptimized codon pairs, RNA secondary structure, CpG dinucleotide content, C+G content”. A viral genome containing nucleotide substitutions engineered in 2 locations of the genome with CpG dinucleotide content reads on k=2 and dinucleotides (re: clm. 17, … wherein k = 2 and each k-mer corresponds to a dinucleotide.)
Applying the KSR standard to Coleman et al. and Kuznetsov et al. the examiner concludes that the combination of the method for administering a modified virus with a dinucleotide according to Coleman et al. with the method for designing genomes implemented by a computing platform as disclosed by Kuznetsov et al. represents some teaching, suggestion or motivation in the prior art that would have lead one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to predictably lead to a computational method of designing a genome with a dinucleotide.
One of ordinary skill in the art of bioinformatics would be motivated to modify the genome design method of Kuznetsov et al. with the addition of a method of increasing dinucleotides or CpG content at a specific region or regions of the genome disclosed by Coleman et al because contributing Coleman et al’s teaching to Kuznetsov et al.’s teaching would have made Kuznetsov et al.’s method stronger via the provision of more genomic editing considerations through the addition of dinucleotides (two base pairs) and codons (three base pairs).
One of ordinary skill in the art of sequence analysis before the effective filing date of the claimed invention would have had a reasonable expectation of success because Coleman et al. discloses codon pair scores in table 1 of the specification. Therefore, the invention would have been prima facie obvious to one of skill in the art at the time of filing of the application, absent evidence to the contrary.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN T STUBBS whose telephone number is (571)272-0340. The examiner can normally be reached M-F 8-5 EST.
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/J.T.S./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
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