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 .
Priority
Acknowledgment is made of applicant’s claim for priority through benefit of US Provisional Application 63/369,478, filed on 7/26/2022. As such the effective filing date of claims 1-36 is 7/26/2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 1/30/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Status
Claims 1-36 are pending.
Claims 1-36 are rejected.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “Figure 5, Item 328” has been used to designate both Other External Services and Tertiary Analysis Processing. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “Figure 5, Item 452” has been used to designate both ICA Services & Data Store and UPA. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: Figure 5, Item 336. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The use of the term Illumina, Inc., which is a trade name or a mark used in commerce, has been noted in this application. The term should be accompanied by the generic terminology; furthermore the term should be capitalized wherever it appears or, where appropriate, include a proper symbol indicating use in commerce such as ™, SM , or ® following the term.
Although the use of trade names and marks used in commerce (i.e., trademarks, service marks, certification marks, and collective marks) are permissible in patent applications, the proprietary nature of the marks should be respected and every effort made to prevent their use in any manner which might adversely affect their validity as commercial marks.
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 1-36 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claims recite computer readable medias for generating a customized report from the analysis of sequence data. The judicial exception is not integrated into a practical application because while claims 1-36 attempt to integrate the exception into a practical application, said application is either generically recited computer elements that do not add a meaningful limitation to the abstract idea, or it is insignificant extra solution activity and simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the computer elements only store and retrieve information in memory as well as perform basic calculations that are known to be well-understood, routine and conventional computer functions as recognized by the decisions listed in MPEP § 2106.05(d).
Framework with which to Analyze Subject Matter Eligibility:
Step 1: Are the claims directed to a category of statutory subject matter (a process, machine, manufacture, or composition of matter)? [see MPEP § 2106.03]
Claims are directed to statutory subject matter, specifically CRMs (claim 1-36).
Step 2A Prong One: Do the claims recite a judicially recognized exception, i.e., an abstract idea, a law of nature, or a natural phenomenon? [see MPEP § 2106.04(a)]
The claims herein recite abstract ideas, mental processes and mathematical concepts.
With respect to the Step 2A Prong One evaluation, the instant claims are found herein to recite abstract ideas that fall into the grouping of mental processes and mathematical concepts.
Claims 1, 25, 32, and 36: Accessing one or more data stores, creating an assertion for the variant of interest, and generating a customized report are processes selecting, identifying, and calculating information that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 2: The nucleic acid comprising a FASTA file or VCF is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claims 5, 27, and 34: The sequence analysis application comprising the specified methods is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claims 7 and 29: Selecting data stores based on a sequence analysis application is a process of identifying, comparing/contrasting, and selecting information that can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claims 8, 30, and 35: Creating additional assertions de novo based on user inputs is a process of comparing/contrasting and calculating information that can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 9: The data stores comprising external or third-party stores is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 10: The data stores comprising the specified data is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 11: The internal data store comprising a personalized knowledge base is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 12: Processing the populated template to generate or update the personalized knowledge base is a process of calculating, comparing/contrasting, and selecting information that can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 13: The nucleic acid sequence comprising data from humans is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 14: The nucleic acid sequence comprising data from non-humans is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claims 15 and 31: Displaying the data stores in a normalized layout is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 16: The dataset being uploaded from a location that is continuously or periodically monitored by a user input is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 17: Displaying each biomarker with an associated score that is selectable to create assertions is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 18: Generating a variant details summary is a process of calculating information that can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process. The genetic data comprising the specified information, and the variant details summary integrates external variant detail data and local variant detail data is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 19: The external and local variant detail data being displayed/printed with a shared field layout is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 20: Generating a customizable report is a process of calculating and selecting information that can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process. The report comprising the specified assertions is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 21: The assertions comprising those specified is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 22: The actionability criteria being customizable is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 23: The actionability criteria specifying a workflow is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Claim 24: The local variant data being accessed from a personalized knowledge base is merely further limiting the data itself which is an abstract idea, specifically a mental process.
Step 2A Prong Two: If the claims recite a judicial exception under prong one, then is the judicial exception integrated into a practical application? [see MPEP § 2106.04(d) and MPEP § 2106.05(a)-(c) & (e)-(h)]
Because the claims do recite judicial exceptions, direction under Step 2A Prong Two provides that the claims must be examined further to determine whether they integrate the abstract ideas into a practical application.
The following claims recite the following additional elements in the form of non-abstract elements:
Claims 1, 25, 32, and 36: Receiving a nucleic acid sequence dataset, displaying a selectable listing of more or more variants, receiving a selection of a variant of interest, displaying one or more variant findings, and receiving a selection of one or more of the variant findings are insignificant extra solution activities, specifically mere data gathering and necessary data outputting (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)]. Computer readable media, and machine-executable routines are all generic and nonspecific elements of a computer that do not improve the functioning of any computer or technology described herein [See MPEP § 2106.04(d)(1) and MPEP § 2106.05(d)].
Claim 3: Displaying a genomics viewer tool configured to display visual information associated with the selected variant of interest is an insignificant extra solution activity, specifically necessary data outputting (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claims 4 and 33: Receiving an indication of a sequence analysis application is an insignificant extra solution activity, specifically mere data gathering (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claims 6 and 28: Accessing data stores using a cloud platform or on premise is an insignificant extra solution activity, specifically mere data gathering (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 12: Providing a template for entry of past history case data, and receiving a populated template are insignificant extra solution activities, specifically mere data gathering and necessary data outputting (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 16: Automatically uploading the nucleic acid sequence dataset is an insignificant extra solution activity, specifically mere data gathering (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Claim 18: Accessing or receiving a data file comprising genetic data for a subject is an insignificant extra solution activity, specifically mere data gathering (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)]. Computer readable media, and machine-executable routines are all generic and nonspecific elements of a computer that do not improve the functioning of any computer or technology described herein [See MPEP § 2106.04(d)(1) and MPEP § 2106.05(d)].
Claim 22: Displaying an actionability criteria for one or more variant or disease characterizations is an insignificant extra solution activity, specifically necessary data outputting (See Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827- 28 (Fed. Cir. 1989) and Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis)) [See MPEP § 2106.05(g)].
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept? [see MPEP § 2106.05]
Because the additional claim elements do not integrate the abstract idea into a practical application, the claims are further examined under Step 2B, which evaluates whether the additional elements, individually and in combination, amount to significantly more than the judicial exception itself by providing an inventive concept.
The claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that are generic, conventional, nonspecific, or insignificant extra solution activity. These additional elements include:
The additional elements of computer readable media, and machine-executable routines are all generic and nonspecific elements of a computer that are well-understood, routine and conventional within the art and therefore do not improve the functioning of any computer or technology described therein (Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values), and Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)) [See MPEP § 2106.05(d)(II)]. Therefore, taken both individually and as a whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
The additional elements of receiving a nucleic acid sequence dataset, displaying a selectable listing of more or more variants, receiving a selection of a variant of interest, displaying one or more variant findings, receiving a selection of one or more of the variant findings, displaying a genomics viewer tool configured to display visual information associated with the selected variant of interest, receiving an indication of a sequence analysis application, accessing data stores using a cloud platform or on premise, providing a template for entry of past history case data, receiving a populated template, automatically uploading the nucleic acid sequence dataset, accessing or receiving a data file comprising genetic data for a subject, and displaying an actionability criteria for one or more variant or disease characterizations are all insignificant extra solution activities, specifically mere data gathering and necessary data outputting (See Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission), OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), and Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)) [See MPEP § 2106.05(g)]. Therefore, taken both individually and as a whole, the additional elements do not amount to significantly more than the judicial exception by providing an inventive concept.
Therefore, claims 1-36, when the limitations are considered individually and as a whole, are rejected
under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-13 and 15-36 are rejected under 35 U.S.C. 102(a)(I) as being anticipated by Miller et al. (Genome Medicine (2015) 1-16).
Claim 1 is directed to a CRM for generating a customized report of variant findings based upon assertions of the variants.
Claim 25 is directed to a CRM for generating a customized report of variant findings based upon assertions of the variants.
Claim 32 is directed to a CRM for generating a customized report of variant findings based upon assertions of the variants.
Miller et al. teaches on page 5, column 2, paragraph 1 “Causative variants were identified primarily with Variant Integration and Knowledge INterpretation in Genomes (VIKING) software (Additional file 2: Figure S2 and Additional file 3: Figure S3). Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26. Alternatively, a menu of pre-determined candidate gene lists can be utilized to filter variants in VIKING, such as genes with OMIM records, or genes previously associated with mitochondrial disorders. VIKING integrated the superset of relevant disease mappings and annotated variant genotypes. By allowing dynamic filtering of variants based on variables such as individual clinical features, diseases, genes, assigned ACMG-type pathogenicity category, allele frequency, genotype, and inheritance pattern, VIKING assists in identification of a differential diagnosis. VIKING settings can be saved, which allows configuration in a manner that can enable a provisional molecular diagnosis to be determined in as little as seconds. VIKING also allowed data mark-up, sessions to be saved, and export of fields in formats suitable for inclusion in diagnostic reports”, on page 3, column 1, paragraph 3 “Sequence data were generated with Illumina RTA 1.12.4.2 & CASAVA-1.8.2, aligned to the human reference GRCh37.p5 using GSNAP, and nucleotide (nt) variants were detected and genotyped with the Genome Analysis Tool Kit (GATK, versions 1.6. and 3.2). Sequence analysis used FASTQ, bam, and VCF files…Variants were annotated with the Rapid Understanding of Nucleotide variant Effect Software. RUNES incorporates data from ENSEMBL’s Variant Effect Predictor (VEP) software, produces comparisons to NCBI dbSNP, known disease variants from the Human Gene Mutation Database, and performs additional in silico prediction of variant consequences using RefSeq and ENSEMBL gene annotations…”, in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on one or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as a first input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; displaying a selectable listing of one or more variants identified in the nucleic acid sequence dataset; receiving a selection of a variant of interest from the selectable listing of the one or more variants; accessing one or more data stores comprising variant data associated with the selected variant of interest; displaying one or more variant findings accessed from the one or more data stores; receiving a selection of one or more of the variant findings; creating an assertion for the variant of interest for each selection of the one or more variant findings; and generating a customized report based on the assertions.
Claim 2 is directed to the CRM of claim 1 but further specifies that the dataset comprise a FASTA or VCF file.
Miller et al. teaches on page 3, column 1, paragraph 3 “Sequence data were generated with Illumina RTA 1.12.4.2 & CASAVA-1.8.2, aligned to the human reference GRCh37.p5 using GSNAP, and nucleotide (nt) variants were detected and genotyped with the Genome Analysis Tool Kit (GATK, versions 1.6. and 3.2). Sequence analysis used FASTQ, bam, and VCF files”, reading on wherein the nucleic acid sequence dataset comprises a FASTA file or a VCF.
Claim 3 is directed to the CRM of claim 1 but further specifies the displaying of a genomics viewer tool.
Miller et al. teaches on page 5, column 2, paragraph 2 “Where a single likely causative heterozygous variant for a recessive disorder was identified, the entire coding domain was manually inspected using the Integrated Genome Viewer (IGV) for coverage”, reading on wherein the one or more machine-executable routines, when executed, cause further acts to be performed comprising: displaying a genomics viewer tool configured to display visual information associated with the selected variant of interest.
Claim 4 is directed to the CRM of claim 1 but further specifies the receiving of an indication of a sequence analysis application.
Claim 26 is directed to the CRM of claim 25 but further specifies the receiving of an indication of a sequence analysis application.
Claim 33 is directed to the CRM of claim 32 but further specifies the receiving of an indication of a sequence analysis application.
Miller et al. teaches on page 5, column 2, paragraph 1 “Causative variants were identified primarily with Variant Integration and Knowledge INterpretation in Genomes (VIKING) software (Additional file 2: Figure S2 and Additional file 3: Figure S3) [6, 11]. Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1) [6, 11, 14, 15]. The SSAGA or Phenomizer record was created during the laboratory steps in WGS26. Alternatively, a menu of pre-determined candidate gene lists can be utilized to filter variants in VIKING, such as genes with OMIM records, or genes previously associated with mitochondrial disorders. VIKING integrated the superset of relevant disease mappings and annotated variant genotypes. By allowing dynamic filtering of variants based on variables such as individual clinical features, diseases, genes, assigned ACMG-type pathogenicity category, allele frequency, genotype, and inheritance pattern, VIKING assists in identification of a differential diagnosis”, reading on wherein the one or more machine-executable routines, when executed, cause further acts to be performed comprising: receiving an indication of a sequence analysis application based on which the nucleic acid sequence dataset will be analyzed.
Claim 5 is directed to the CRM of claim 4 and thus claim 1 but further specifies that the analysis application be one of those specified.
Claim 27 is directed to the CRM of claim 26 and thus claim 25 but further specifies that the analysis application be one of those specified.
Claim 34 is directed to the CRM of claim 33 and thus claim 32 but further specifies that the analysis application be one of those specified.
Miller et al. teaches on page 5, column 2, paragraph 1 “Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26. Alternatively, a menu of pre-determined candidate gene lists can be utilized to filter variants in VIKING, such as genes with OMIM records, or genes previously associated with mitochondrial disorders. VIKING integrated the superset of relevant disease mappings and annotated variant genotypes. By allowing dynamic filtering of variants based on variables such as individual clinical features, diseases, genes, assigned ACMG-type pathogenicity category, allele frequency, genotype, and inheritance pattern, VIKING assists in identification of a differential diagnosis”, reading on wherein the sequence analysis application comprises one of oncology testing, environmental surveillance, anti-microbial resistance (AMR) studies, infectious disease studies, public health and microbial surveillance, genetic disorder studies, or genetic disease testing.
Claim 6 is directed to the CRM of claim 1 but further specifies the data stores are accessed using a cloud platform of on the premises.
Claim 28 is directed to the CRM of claim 25 but further specifies the data stores are accessed using a cloud platform of on the premises.
Miller et al. teaches on page 3, column 1, paragraph 4 “RUNES incorporates data from ENSEMBL’s Variant Effect Predictor (VEP) software, produces comparisons to NCBI dbSNP, known disease variants from the Human Gene Mutation Database, and performs additional in silico prediction of variant consequences using RefSeq and ENSEMBL gene annotations. RUNES categorized each variant according to ACMG recommendations for reporting sequence variation [18–21] and with an allele frequency (MAF) derived from CPGM’s Variant Warehouse database of approximately 90 million variants and 3,900 individuals”, and on page 12, column 1, paragraph 2 “The DRAGEN alignment and variant calling hardware and software has specifications which are likely to make genome sequencing practicable in many hospital laboratories, such as reducing the need for cloud computing or a large local cluster. The VIKING software greatly alleviates the burden of genome analysis and interpretation and allows common inheritance modes to be rapidly examined”, reading on wherein the one or more data stores are accessed using a cloud platform or on premise.
Claim 7 is directed to the CRM of claim 1 but further specifies that the data stores be selected to be assessed based on a sequence analysis application.
Claim 29 is directed to the CRM of claim 25 but further specifies that the data stores be selected to be assessed based on a sequence analysis application.
Miller et al. teaches on page 3, column 1, paragraph 4 “Variants were annotated with the Rapid Understanding of Nucleotide variant Effect Software (RUNES, v3.3.5). RUNES incorporates data from ENSEMBL’s Variant Effect Predictor (VEP) software, produces comparisons to NCBI dbSNP, known disease variants from the Human Gene Mutation Database, and performs additional in silico prediction of variant consequences using RefSeq and ENSEMBL gene annotations”, reading on wherein the one or more data stores are selected to be accessed based on a sequence analysis application.
Claim 8 is directed to the CRM of claim 1 but further specifies the creation of additional assertions based on user inputs.
Claim 30 is directed to the CRM of claim 25 but further specifies the creation of additional assertions based on user inputs.
Claim 35 is directed to the CRM of claim 32 but further specifies the creation of additional assertions based on user inputs.
Miller et al. teaches on page 5, column 2, paragraph 1 “The SSAGA or Phenomizer record was created during the laboratory steps in WGS26. Alternatively, a menu of pre-determined candidate gene lists can be utilized to filter variants in VIKING, such as genes with OMIM records, or genes previously associated with mitochondrial disorders”, reading on wherein the machine-executable routines, when executed, cause further acts to be performed comprising: creating additional assertions based on user inputs, wherein the additional assertions are created de novo.
Claim 9 is directed to the CRM of claim 1 but further specifies that the data stores comprise those specified.
Miller et al. teaches on page 3, column 1, paragraph 4 “RUNES incorporates data from ENSEMBL’s Variant Effect Predictor (VEP) software, produces comparisons to NCBI dbSNP, known disease variants from the Human Gene Mutation Database, and performs additional in silico prediction of variant consequences using RefSeq and ENSEMBL gene annotations. RUNES categorized each variant according to ACMG recommendations for reporting sequence variation and with an allele frequency (MAF) derived from CPGM’s Variant Warehouse database of approximately 90 million variants and 3,900 individuals”, reading on wherein the one or more data stores comprise external or third-party data stores.
Claim 10 is directed to the CRM of claim 1 but further specifies that the data stores comprise internal data stores comprising the data specified.
Miller et al. teaches on page 5, column 2, paragraph 1 “Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26”, reading on wherein the one or more data stores comprise an internal data store comprising past history case data for a user or an organization with which the user is affiliated.
Claim 11 is directed to the CRM of claim 10 and thus claim 1, but further specifies that the internal data store comprises a personalized knowledge base.
Miller et al. teaches on page 5, column 2, paragraph 1 “Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26”, reading on wherein the internal data store comprises a personalized knowledge base.
Claim 12 is directed to the CRM of claim 11 and thus claim 1, but further specifies the creation of a report of past history data that is used to update the personalized knowledge base.
Miller et al. teaches on page 13, column 1, paragraph 2 “With further software development, it should be possible to generate an automatic report of the completeness of genotyping of all protein coding nucleotides and intron-exon boundaries of relevant disease genes with defined coverage and quality scores, and, thereby, in the future, to ‘rule out’ specific diagnoses”, reading on wherein the machine-executable routines, when executed, cause further acts to be performed comprising: providing a template for entry of past history case data for the user or the organization with which the user is affiliated; receiving as an input a populated template; and processing the populated template to generate or update the personalized knowledge base.
Claim 13 is directed to the CRM of claim 1 but further specifies that the sequencing data is of human origin.
Miller et al. teaches on page 3, column 1, paragraph 3 “Sequence data were generated with Illumina RTA 1.12.4.2 & CASAVA-1.8.2, aligned to the human reference GRCh37.p5 using GSNAP”, reading on wherein the nucleic acid sequence dataset comprises or is derived from sequence data of human origin.
Claim 15 is directed to the CRM of claim 1 but further specifies that the variant findings are displayed in a normalized layout.
Claim 31 is directed to the CRM of claim 25 but further specifies that the variant findings are displayed in a normalized layout.
Miller et al. teaches in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed”, reading on wherein the one or more variant findings accessed from the one or more data stores are displayed in a normalized layout.
Claim 16 is directed to the CRM of claim 1 but further specifies that the dataset is automatically uploaded from a location that is continuously or periodically monitored.
Miller et al. teaches on page 3, column 1, paragraph 4 “RUNES incorporates data from ENSEMBL’s Variant Effect Predictor (VEP) software, produces comparisons to NCBI dbSNP, known disease variants from the Human Gene Mutation Database”, reading on wherein the nucleic acid sequence dataset is automatically uploaded from a location that is continuously or periodically monitored and that is specified by a user input.
Claim 17 is directed to the CRM of claim 1 but further specifies displaying one or more biomarkers with an associated score that is selectable.
Miller et al. teaches in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on wherein the one or more machine-executable routines, when executed, cause further acts to be performed comprising: displaying one or more genome-wide biomarkers derived for the nucleic acid sequence dataset or variants present in the nucleic acid sequence dataset, wherein each genome-wide biomarker is displayed with an associated score and wherein one or more of the genome-wide biomarkers is selectable to create assertions used to generate the customized report.
Claim 18 is directed to a CRM which takes in genetic data of a subject and generates variant detail summaries based on external and local data.
Miller et al. teaches on page5, column 2, paragraph 1 “Causative variants were identified primarily with Variant Integration and Knowledge INterpretation in Genomes (VIKING) software” , and on page 3, column 1, paragraph 3 “Sequence data were generated with Illumina RTA 1.12.4.2 & CASAVA-1.8.2, aligned to the human reference GRCh37.p5 using GSNAP [22], and nucleotide (nt) variants were detected and genotyped with the Genome Analysis Tool Kit… Variants were annotated with the Rapid Understanding of Nucleotide variant Effect Software… RUNES incorporates data from ENSEMBL’s Variant Effect Predictor (VEP) software, produces comparisons to NCBI dbSNP, known disease variants from the Human Gene Mutation Database, and performs additional in silico prediction of variant consequences using RefSeq and ENSEMBL gene annotations”, reading on one or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: accessing or receiving a data file comprising genetic data for a subject, wherein the genetic data comprises one or both of a primary analysis or a secondary analysis of the subject’s genetic composition. Miller et al. teaches in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on generating a variant details summary for display or printout, wherein the variant details summary integrates and concurrently shows data comprising: external variant detail data acquired from one or more data stores external to a machine executing the machine-readable instructions; and local variant detail data comprising past case data of a user of the machine or an organization to which the user belongs.
Claim 19 is directed to the CRM of claim 18 but further specifies that the variant details are displayed having a shared field layout.
Miller et al. teaches in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on wherein the external variant detail data and the local variant detail data are displayed or printed having a shared field layout.
Claim 20 is directed to the CRM of claim 18 but further specifies the generation of a customizable report based on the genetic data comprising one or more assertions that relates observations to the data stores.
Miller et al. teaches on page 5, column 2, paragraph 1 “Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26. Alternatively, a menu of pre-determined candidate gene lists can be utilized to filter variants in VIKING, such as genes with OMIM records, or genes previously associated with mitochondrial disorders. VIKING integrated the superset of relevant disease mappings and annotated variant genotypes. By allowing dynamic filtering of variants based on variables such as individual clinical features, diseases, genes, assigned ACMG-type pathogenicity category, allele frequency, genotype, and inheritance pattern, VIKING assists in identification of a differential diagnosis”, in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on wherein the machine-executable routines, when executed, cause further acts to be performed comprising: generating a customizable report based on the genetic data, wherein the report comprises one or more assertions generated automatically or by the user, wherein each assertion relates one or more variant or disease observations derived from the genetic data to data derived from the one or more data stores external to the machine or from past case data.
Claim 21 is directed to the CRM of claim 20 and thus claim 18, but further specifies that the assertions comprise one or more of those specified.
Miller et al. teaches on page 5, column 2, paragraph 1 “Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26. Alternatively, a menu of pre-determined candidate gene lists can be utilized to filter variants in VIKING, such as genes with OMIM records, or genes previously associated with mitochondrial disorders. VIKING integrated the superset of relevant disease mappings and annotated variant genotypes. By allowing dynamic filtering of variants based on variables such as individual clinical features, diseases, genes, assigned ACMG-type pathogenicity category, allele frequency, genotype, and inheritance pattern, VIKING assists in identification of a differential diagnosis”, reading on wherein the one or more assertions comprise one or more of a therapeutic assertion, a prognostic assertion, or a diagnostic assertion.
Claim 22 is directed to the CRM of claim 18 but further specifies the displaying of actionability criteria that are customizable.
Miller et al. teaches in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on wherein the machine-executable routines, when executed, cause further acts to be performed comprising: displaying an actionability criteria for one or more variant or disease characterizations derived from the genetic data accessed, wherein the actionability criteria are customizable by the user or the organization to which the user belongs.
Claim 23 is directed to the CRM of claim 22 but further specifies that the actionability criteria specify a workflow for a given subject.
Miller et al. teaches in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on wherein the actionability criteria, when applied, specify a workflow for a given subject having a respective genetic variant or disease.
Claim 24 is directed to the CRM of claim 18 but further specifies that the local variant detail is accessed from a personalized knowledge base.
Miller et al. teaches on page 5, column 2, paragraph 1 “Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26”, reading on wherein the local variant detail data is accessed from a personalized knowledge base.
Claim 36 is directed to a CRM for generating a customized report of variant findings based upon assertions of the variants.
Miller et al. teaches on page 5, column 2, paragraph 1 “Causative variants were identified primarily with Variant Integration and Knowledge INterpretation in Genomes (VIKING) software (Additional file 2: Figure S2 and Additional file 3: Figure S3). Inputs for VIKING were the annotated genomic variant file produced by the RUNES pipeline and a SSAGA (Symptom and Sign Associated Genome Analysis) or Phenomizer record, comprising the clinical features of the affected patient, corresponding diseases in the differential diagnosis, and the respective disease genes (Additional file 1: Figure S1). The SSAGA or Phenomizer record was created during the laboratory steps in WGS26. Alternatively, a menu of pre-determined candidate gene lists can be utilized to filter variants in VIKING, such as genes with OMIM records, or genes previously associated with mitochondrial disorders. VIKING integrated the superset of relevant disease mappings and annotated variant genotypes. By allowing dynamic filtering of variants based on variables such as individual clinical features, diseases, genes, assigned ACMG-type pathogenicity category, allele frequency, genotype, and inheritance pattern, VIKING assists in identification of a differential diagnosis. VIKING settings can be saved, which allows configuration in a manner that can enable a provisional molecular diagnosis to be determined in as little as seconds. VIKING also allowed data mark-up, sessions to be saved, and export of fields in formats suitable for inclusion in diagnostic reports”, on page 3, column 1, paragraph 3 “Sequence data were generated with Illumina RTA 1.12.4.2 & CASAVA-1.8.2, aligned to the human reference GRCh37.p5 using GSNAP, and nucleotide (nt) variants were detected and genotyped with the Genome Analysis Tool Kit (GATK, versions 1.6. and 3.2). Sequence analysis used FASTQ, bam, and VCF files…Variants were annotated with the Rapid Understanding of Nucleotide variant Effect Software. RUNES incorporates data from ENSEMBL’s Variant Effect Predictor (VEP) software, produces comparisons to NCBI dbSNP, known disease variants from the Human Gene Mutation Database, and performs additional in silico prediction of variant consequences using RefSeq and ENSEMBL gene annotations…”, in Supplemental Figure S3 “A screen-shot of VIKING showing variants identified by DRAGEN in WGS26 of sample UDT_103, a patient with a molecular diagnosis of familial hemophagocytic lymphohistiocytosis type 3. Variants are displayed as rows in the right hand panel. The variant attributes are displayed by columns in the right hand panel. The bottom left panel permits selection of the variant attributes to be displayed” and in Supplemental Figure S2 “A screen-shot of the warehouse annotation and curation data for a genomic variant. Right clicking a variant row in VIKING opens a menu that includes a link-out to the CMH Variant Warehouse, which contains automated annotation data from RUNES (ACMG-type variant category, CM-KC allele frequency, homozygous and heterozygous status in other samples, BLOSUM score, SIFT score, and PolyPhen2 score), Entrez Gene, HGMD, ClinVar, COSMIC, and manual curation data for that variant (if available). Highlighted values represent hyperlinks to additional information”, reading on one or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: accessing or receiving a data file comprising genetic data for a subject, wherein the genetic data comprises one or both of a primary analysis or a secondary analysis of the subject’s genetic composition; and displaying a variant details summary interface, wherein the variant details summary interface integrates and concurrently shows data comprising: external variant detail data acquired from one or more data stores external to a machine executing the machine-readable instructions; and local variant detail data comprising past case data of a user of the machine or an organization to which the user belongs; and providing on or via the variant details summary interface selectable options for creating one or more assertions based on the external variant detail data, the local variant detail data, or a de novo assertion entry.
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.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Miller et al. (Genome Medicine (2015) 1-16) as applied to claims 1-13 and 15-36 above, and further in view of Sato et al. (BioRxiv (2020) 1-34).
Claim 14 is directed to the CRM of claim 1 but further specifies that the sequence is of non-human origin.
Miller et al. teaches the CRM of claim 1 as previously described.
Miller et al. does not teach the use of non-human sequences.
Sato et al. teaches in the abstract “we describe the generation of three mutant marmoset individuals in which exon 9 of PSEN1 gene product has been deleted (PSEN1-ΔE9). Such ΔE9 mutations have been reported to cause early on-set familial AD (references1-5). We used Transcription Activator-Like Effector Nuclease (TALEN) to destroy the 3’ splice site of exon 9 in the marmoset PSEN1 gene. To this end, TALEN exhibits high genome-editing efficacy, generates few off-target effects, and produces minimal mosaicism. Indeed, whole genome sequencing and other analyses illustrated an absence of off-target effects and an apparent absence of mosaicism. Fibroblasts obtained from newborn marmosets exhibited uncleaved full-length presenilin 1 protein (PS1) caused by the perturbation of PS1 endoproteolysis as well as an increased ratio of Aβ42/Aβ40 production, a signature of familial AD pathogenesis”, and on page 4, paragraph 2 “We used the Platinum TALENs designed to target the 3’ splice site of exon 9 of the marmoset PSEN1 gene (Figure 1a)42,43. After introduction of the TALEN mRNAs into the nuclei of marmoset pronuclear stage embryos, we performed surveyor assays and sequencing with genomic DNA extracted from developed embryos. We found that two out of three embryos exhibited deletions at the target sequences including the acceptor site as expected (Figure 1b). To confirm the exclusion of exon 9 in the PSEN1 mRNA, we performed RT-PCR and sequenced the corresponding cDNA sequencing using RNAs extracted from 4-cell-stage or single blastomeres of the TALEN-injected marmoset embryos”, reading on wherein the nucleic acid sequence dataset comprises or is derived from sequence data of non-human origin.
It would have been obvious at the time of first filing to have modified the teachings of Miller et al. for the CRMs of claims 1-13 and 15-36, with the teachings of Sato et al. for the diagnosis and characterization of alzheimers disease in primates as the first is building a platform for aggregating variant information and generating reports based on clinical associations of said variants and disease, and the latter is merely building the clinical associations of variants and disease but extending that to a primate model. Thus it would merely be a simple substitution of one known method, the use of human sequences and reference genomes, with another known method, the use of primate sequences and reference genomes, for an expected outcome, the association of variants with a disease/outcome and reporting/displaying it. Therefore it would have been obvious at the time of first filing to have modified the teachings of each and to be successful.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-2, 25, 32, and 36 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 7 of U.S. Patent No. US 2025011104 W. Although the claims at issue are not identical, they are not patentably distinct from each other because while there are minor differences between the independent claims, the limitations of claim 1 in the instant application are found within the limitations of claim 1 of U.S. Patent No. US 2025011104 W, and claims 25, 32, and 36 are mere obvious alternatives of claim 1, i.e. “accessing two or more external data stores” (Claim 25) or “past case data” (Claim 32), instead of “one or more data stores” (Claim 1).
Instant Application: 18/357,829
U.S. Patent No. US 2025011104 W
Claims 1: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as a first input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; displaying a selectable listing of one or more variants identified in the nucleic acid sequence dataset; receiving a selection of a variant of interest from the selectable listing of the one or more variants; accessing one or more data stores comprising variant data associated with the selected variant of interest; displaying one or more variant findings accessed from the one or more data stores; receiving a selection of one or more of the variant findings; creating an assertion for the variant of interest for each selection of the one or more variant findings; and generating a customized report based on the assertions.
Claim 1: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as an input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; causing the display of a selected case derived from the nucleic acid sequence data and a related case derived from a different set of nucleic acid sequence data; receiving an input corresponding to an instruction to merge the selected case and the related case; generating a merged case comprising data from both the selected case and the related case; performing one or more analysis operations using the merged case; and generating a customized report based on the merged case.
Claim 2: The one or more computer readable media of claim 1, wherein the nucleic acid sequence dataset comprises a FASTA file or a VCF.
Claim 7: The one or more computer readable media of claim 1, wherein the nucleic acid sequence dataset comprises a FASTA file or a VCF.
Claim 25: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as a first input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; displaying a selectable listing of one or more variants identified in the nucleic acid sequence dataset; receiving a selection of a variant of interest from the selectable listing of the one or more variants; accessing two or more external data stores comprising variant data associated with the selected variant of interest; displaying one or more variant findings accessed from the two or more external data stores; receiving a selection of one or more of the variant findings; creating an assertion for the variant of interest for each selection of the one or more variant findings; and generating a customized report based on the assertions.
Claim 1: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as an input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; causing the display of a selected case derived from the nucleic acid sequence data and a related case derived from a different set of nucleic acid sequence data; receiving an input corresponding to an instruction to merge the selected case and the related case; generating a merged case comprising data from both the selected case and the related case; performing one or more analysis operations using the merged case; and generating a customized report based on the merged case.
Claim 32: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as a first input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; displaying a selectable listing of one or more variants identified in the nucleic acid sequence dataset; receiving a selection of a variant of interest from the selectable listing of the one or more variants; accessing past case data comprising variant data associated with the selected variant of interest; displaying one or more variant findings accessed from the past case data; receiving a selection of one or more of the variant findings; creating an assertion for the variant of interest for each selection of the one or more variant findings; and generating a customized report based on the assertions.
Claim 1: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as an input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; causing the display of a selected case derived from the nucleic acid sequence data and a related case derived from a different set of nucleic acid sequence data; receiving an input corresponding to an instruction to merge the selected case and the related case; generating a merged case comprising data from both the selected case and the related case; performing one or more analysis operations using the merged case; and generating a customized report based on the merged case.
Claim 36: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: accessing or receiving a data file comprising genetic data for a subject, wherein the genetic data comprises one or both of a primary analysis or a secondary analysis of the subject’s genetic composition; and displaying a variant details summary interface, wherein the variant details summary interface integrates and concurrently shows data comprising: external variant detail data acquired from one or more data stores external to a machine executing the machine-readable instructions; and local variant detail data comprising past case data of a user of the machine or an organization to which the user belongs; and providing on or via the variant details summary interface selectable options for creating one or more assertions based on the external variant detail data, the local variant detail data, or a de novo assertion entry.
Claim 1: One or more computer readable media comprising machine-executable routines, wherein the machine-executable routines, when executed, cause acts to be performed comprising: receiving as an input a nucleic acid sequence dataset, wherein the nucleic acid sequence data set is an output of one or both of a primary analysis or a secondary analysis; causing the display of a selected case derived from the nucleic acid sequence data and a related case derived from a different set of nucleic acid sequence data; receiving an input corresponding to an instruction to merge the selected case and the related case; generating a merged case comprising data from both the selected case and the related case; performing one or more analysis operations using the merged case; and generating a customized report based on the merged case.
Conclusion
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Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/K.N.A./ Examiner, Art Unit 1687
/LARRY D RIGGS II/ Supervisory Patent Examiner, Art Unit 1686
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