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 .
DETAILED ACTION
Status of Claims
The present Office Action is pursuant to Applicant’s communication on 10-17-2025; current application filed on 10-17-2025; Continuation of application No. 18/226,708, filed on Jul. 26, 2023.
Examiner’s Note
The rejections below group claims that may not be identical, but whose language and scope are so substantively similar as to lend themselves to grouping, in the interests of clarity and conciseness.
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 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1: Statutory Category
Claims 1, 8, and 15 are directed to statutory categories under 35 U.S.C. § 101. Claim 1 recites a method/process, Claim 8 recites a non-transitory computer-readable medium, and Claim 15 recites a system/machine. Therefore, the claims pass Step 1 of the Alice/Mayo framework.
Step 2A Prong One: Abstract Idea
The independent claims recite an abstract idea falling under the judicial exceptions of "organizing human activity" and "mental processes/data gathering." The core concept involves collecting genetic data, analyzing it using software tools, evaluating quality control metrics against predetermined thresholds, and conditionally reporting results to healthcare providers. This is essentially a routine data collection, analysis, and reporting workflow.
As recited in the claims: “receiving a request from a healthcare provider to have genetic testing performed on a patient; obtaining or having obtained a biological sample from the patient in response to the request; performing or having performed sequencing on the biological sample to generate sequencing data of the patient”. The specification further confirms this is a standard diagnostic data pipeline: “The method also includes receiving a request from a healthcare provider for results of a test that reports at least a portion of the called genetic variants in relation to a diagnosis of the patient by the healthcare provider, and delivering the results of the test to the healthcare provider if a quality control value of said at least a portion of the called genetic variants meets or exceeds a predetermined threshold of quality”. These steps describe conventional laboratory data processing and commercial interactions between providers and testing facilities, which are abstract in nature.
Step 2A Prong Two: Practical Application
The additional elements do not integrate the abstract idea into a practical application. The claims rely on generic computer components (For example, “data structure,” “analytical tool,” “controller,” “interface”, “non-transitory computer readable medium”, “processor”) and conventional laboratory procedures (“obtaining biological sample,” “performing sequencing”). These elements are used merely as tools to perform the abstract idea, without improving the functioning of the computer itself or applying the concept in a meaningful technical way.
The specification describes the analytical components as standard bioinformatics software: “Generally, the analytical tools used are software programs that perform bioinformatic operations, such as sequence alignment, variant calling, haplotype calling, and/or imputation for genetic data”. Using off-the-shelf sequencing equipment and generic computing resources to store, analyze, and filter genetic data based on quality thresholds does not transform the abstract idea into a practical application. The claims do not recite a specific technical improvement to sequencing technology, a novel algorithmic approach, or an unconventional laboratory method that would satisfy Prong Two.
Step 2B: Significantly More
The claims do not contain an inventive concept amounting to “significantly more” than the abstract idea. The steps of sequencing, variant calling, QC evaluation, and conditional reporting are well-understood, routine, and conventional in the genomics field. The specification explicitly frames these as standard quality assurance practices: “The genetic data may then be stored with the results of the tests along with one or more Quality Control (QC) scores... that are determined based on a combination of a known accuracy of the analytical tool on a set of training data, the quality of underlying genomic data... and/or other metrics such as completeness of output or callability”.
Re-running analytical tools when QC thresholds are not met is a routine troubleshooting step: “When the results from an analytical tool do not pass QC for reporting for a given test, the analytical tool may be re-run (e.g., using a newer version of the analytical tool than was originally used when sequencing was first performed)”. There is no unconventional technical feature, unexpected result, or specific improvement to computer functionality that would render the claims patent-eligible under Step 2B.
Analysis of Dependent Claims
Claims 2-7, 9-14, and 16-21 depend on the independent claims and merely add further limitations that are either abstract or conventional. None introduce an inventive concept that would overcome the § 101 rejection.
Claims 5, 12, & 19 (QC Thresholds): These claims specify numerical quality control metrics: “the quality control value is at least one of: a callability of at least ninety-nine percent across genetic loci considered by the genetic test; at most 0.01 for a gene dispersion of the sequencing data associated with the called genetic variants; at most five percent for a ratio of bacterial DNA to human DNA of the sequencing data associated with the called genetic variants; or at least twenty for fold enrichment of the sequencing data associated with the called genetic variants”. These are routine statistical thresholds commonly used in genomic data validation and do not add significantly more.
Claims 7, 14, & 21 (Bioinformatic Operations): These claims recite standard computational biology functions: “the analytical tool is operable to perform at least one bioinformatic operation selected from the group consisting of: sequence alignment, variant calling, haplotype calling, and imputation for genetic data”. These are well-known, conventional software operations in the field.
Claims 3/4, 10/11, & 17/18 (Re-running Tools / Resequencing): These claims describe re-analyzing data with newer tool versions or resequencing preserved samples when QC fails. As noted in the specification: “preserving the biological sample in a laboratory and, in an event that re-running the analytical tool does not result in the additional quality control value exceeding the predetermined threshold, resequencing a portion of the biological sample at locations corresponding to the additional key result”. This is a standard laboratory quality assurance workflow and does not provide an inventive concept.
Claims 6, 13, & 20 (Data Structure Records): These claims merely define how data is organized: “the data structure includes, for each genetic test, a record comprising a test name, a tool name, a corresponding portion of the called genetic variants, and a quality control value of the test”. Organizing data in this manner is a conventional database management practice.
Conclusion: All independent and dependent claims are directed to an abstract idea (data collection, analysis, and conditional reporting) implemented using generic computing components and routine laboratory procedures. The claims lack a practical application and do not contain significantly more than the judicial exception. Therefore, Claims 1-21 are rejected under 35 U.S.C. § 101 as directed to non-statutory subject matter. Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claim(s) 1-21 is/are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Double Patenting
The non-statutory 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 non-statutory 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 non-statutory 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 §§ 706.02(l)(1) - 706.02(l)(3) 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 USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-21 are rejected on the ground of non-statutory double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 12,518,8591 B2 (hereinafter “Parent Application”). Although the instant claims are not identical to those of the parent patent, they are directed to the same invention and are not patentably distinct therefrom.
I. Analysis of Independent Claims
The independent claims of the continuation application are compared below with the corresponding independent claims of the parent patent to demonstrate lack of patentable distinction.
Continuation Claim 1 vs. Parent Claim 1Continuation claim 1 recites: “receiving a request from a healthcare provider to have genetic testing performed on a patient; obtaining or having obtained a biological sample from the patient in response to the request; performing or having performed sequencing on the biological sample to generate sequencing data of the patient; calling genetic variants in portions of the sequencing data; storing the called genetic variants in a data structure... operating an analytical tool upon a portion of the data structure that is specific to the genetic test, without performing additional sequencing; and determining a quality control value for a result of the analytical tool”.Parent claim 1 recites substantially identical limitations: “obtaining or having obtained a biological sample from a patient; performing or having performed sequencing on the biological sample to generate gene sequencing data of the patient; calling genetic variants in portions of the gene sequencing data; storing the gene sequencing data and the called genetic variants in a data structure; receiving a request from a healthcare provider to have genetic testing performed on the patient... accessing a quality control value of said at least a portion of the called genetic variants in response to the request without performing additional sequencing”. The only difference is the sequential ordering of steps, which does not confer patentable distinction.
Continuation Claim 8 vs. Parent Claim 7Continuation claim 8 recites: “A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method comprising: receiving a request from a healthcare provider to have genetic testing performed on a patient; obtaining or having obtained a biological sample from the patient in response to the request; performing or having performed sequencing on the biological sample to generate sequencing data of the patient; calling genetic variants in portions of the sequencing data; storing the called genetic variants in a data structure”.
Parent claim 7 recites: “A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method comprising: obtaining or having obtained a biological sample from a patient; performing or having performed sequencing on the biological sample to generate gene sequencing data of the patient; calling genetic variants in portions of the gene sequencing data; storing the gene sequencing data and the called genetic variants in a data structure; receiving a request from a healthcare provider to have genetic testing performed on the patient”. The claims are functionally identical.
Continuation Claim 15 vs. Parent Claim 13Continuation claim 15 recites: “A system, comprising: an interface operable to receive a request from a healthcare provider to have genetic testing performed on a patient; gene sequencing equipment operable to perform or have performed sequencing on a biological sample obtained from the patient in response to the request to generate sequencing data of the patient; variant calling equipment operable to call genetic variants in portions of the sequencing data; a database operable to store the called genetic variants in a data structure; and a controller operable to, for each of multiple genetic tests: operate an analytical tool upon a portion of the data structure that is specific to the genetic test, without performing additional sequencing”.Parent claim 13 recites: “A system, comprising: gene sequencing equipment operable to perform or have performed sequencing on a biological sample obtained from a patient to generate gene sequencing data of the patient; variant calling equipment operable to call genetic variants in portions of the gene sequencing data; a storage device operable to store the gene sequencing data and the called genetic variants in a data structure; an interface operable to receive a request from a healthcare provider... and a controller operable to determine whether a quality control value of said at least a portion of the called genetic variants meets or exceeds a predetermined threshold of quality for assisting the healthcare provider in response to the request without performing additional sequencing”. The system claims are not patentably distinct.
II. Analysis of Dependent Claims
The dependent claims of the continuation application are compared below with the corresponding dependent claims of the parent patent.
Continuation Claims 2-7 vs. Parent Claims 2-6Continuation claim 5 specifies quality control thresholds: “the quality control value is at least one of: a callability of at least ninety-nine percent across genetic loci considered by the genetic test; at most 0.01 for a gene dispersion of the sequencing data associated with the called genetic variants; at most five percent for a ratio of bacterial DNA to human DNA of the sequencing data associated with the called genetic variants; or at least twenty for fold enrichment of the sequencing data associated with the called genetic variants”. Parent claim 4 recites the exact same thresholds: “the quality control value is at least one of: a callability of at least ninety-nine percent across genetic loci considered by the test; at most 0.01 for a gene dispersion of the gene sequencing data associated with the called genetic variant; at most five percent for a ratio of bacterial DNA to human DNA of the gene sequencing data associated with the called genetic variant; at least twenty for fold enrichment of the gene sequencing data associated with the called genetic variant”.Similarly, continuation claim 4 recites: “preserving the biological sample in a laboratory and, in an event that re-running the analytical tool does not result in the additional quality control value exceeding the predetermined threshold, resequencing a portion of the biological sample at locations corresponding to the additional key result”, which is directly anticipated by parent claim 5: “preserving the biological sample in a laboratory; and retesting the biological sample when the quality control value of said at least a portion of the called genetic variants does not meet the predetermined threshold, wherein retesting comprises resequencing a portion of the biological sample at locations of said at least a portion of the called genetic variants in the gene sequencing data”.
Continuation Claims 9-14 vs. Parent Claims 8-12The computer-readable medium dependent claims in the continuation application merely mirror the method-dependent claims. For example, continuation claim 12 recites identical QC thresholds to parent claim 10: “the quality control value is at least one of: a callability of at least ninety-nine percent across genetic loci considered by the genetic test; at most 0.01 for a gene dispersion... at most five percent for a ratio of bacterial DNA to human DNA... or at least twenty for fold enrichment”, matching parent claim 10’s “the quality control value is at least one of: a callability of at least ninety-nine percent across genetic loci considered by the test; at most 0.01 for a gene dispersion... at most five percent for a ratio of bacterial DNA to human DNA... at least twenty for fold enrichment”. Continuation claim 11 and parent claim 11 both require preserving the sample and resequencing upon QC failure.
Continuation Claims 16-21 vs. Parent Claims 14-18The system-dependent claims are similarly non-distinct. Continuation claim 19 recites: “the quality control value is at least one of: a callability of at least ninety-nine percent across genetic loci considered by the genetic test; at most 0.01 for a gene dispersion... at most five percent for a ratio of bacterial DNA to human DNA... or at least twenty for fold enrichment”, which is identical to parent claim 16: “the quality control value is at least one of: a callability of at least ninety-nine percent across genetic loci considered by the test; at most 0.01 for a gene dispersion... at most five percent for a ratio of bacterial DNA to human DNA... at least twenty for fold enrichment”. Continuation claim 18 and parent claim 17 both require resequencing preserved biological samples when QC thresholds are not met.
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 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 date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eltoukhy (US 10,801,063) in view of Jaganathan (US 11,676,685).Regarding claim(s) 1, 8, 15, Eltoukhy discloses: A method, A system, A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method comprising:
receiving a request from a healthcare provider to have genetic testing performed on a patient (i.e., an interface operable to receive a request); ["All genes listed in Tables 1 and 2 are analyzed as part of the Guardant360™ test [56:11-12]”, gene analysis corresponding to receipt of a request or requisition of the test by a provider, the "Guardant360™ test" is a clinical service where a healthcare provider requests genetic testing of a patient's cfDNA]
obtaining or having obtained a biological sample from the patient in response to the request; [Eltoukhy discloses sample collection and processing: "collecting a nucleic acid sample from a subject" where "the nucleic acid sample can be collected from blood, plasma, serum, urine, saliva, mucosal excretions, sputum, stool, cerebral spinal fluid, skin, hair, sweat, and/or tears" [42:27-36]”]
performing or having performed sequencing on the biological sample to generate sequencing data of the patient (i.e., gene sequencing equipment operable to perform or have performed sequencing); [Eltoukhy teaches massively parallel sequencing of the extracted sample: “Massively Parallel Sequencing... 0.1 to 1% of the sample (approximately 100pg) are used for sequencing 54:20-24”]
calling genetic variants in portions of the sequencing data (i.e., variant calling equipment operable to call variants); [Eltoukhy discloses that "a computer processor [is] operatively coupled to the communication interface and the memory and programmed to (i) group the plurality of sequence reads into families, wherein each family comprises sequence reads from one of the template polynucleotides, (ii) for each of the families, merge sequence reads to generate a consensus sequence, (iii) call the consensus sequence at a given genomic locus among the genomic loci, and (iv) detect at the given genomic locus any of genetic variants among the calls, frequency of a genetic alteration among the calls, total number of calls; and total number of alterations among the calls" [51:27-44]. The "computer memory that stores the nucleic acid sequence reads for the plurality of polynucleotide molecules received by the communication interface" constitutes the "data structure" in which called genetic variants are stored]
storing the called genetic variants in a data structure (i.e., a database operable to store called variants); [Eltoukhy discloses that "a computer processor [is] operatively coupled to the communication interface and the memory and programmed to (i) group the plurality of sequence reads into families, wherein each family comprises sequence reads from one of the template polynucleotides, (ii) for each of the families, merge sequence reads to generate a consensus sequence, (iii) call the consensus sequence at a given genomic locus among the genomic loci, and (iv) detect at the given genomic locus any of genetic variants among the calls, frequency of a genetic alteration among the calls, total number of calls; and total number of alterations among the calls" [51:27-44]. The "computer memory that stores the nucleic acid sequence reads for the plurality of polynucleotide molecules received by the communication interface" constitutes the "data structure" in which called genetic variants are stored]
for each of multiple genetic tests: operating an analytical tool upon a portion of the data structure that is specific to the genetic test, without performing additional sequencing (i.e., a controller operable to, for each of multiple tests); [Eltoukhy discloses that the genomic loci "correspond to a plurality of genes selected from the group consisting of ALK, APC, BRAF, CDKN2A, EGFR, ERBB2, FBXW7, KRAS, MYC, NOTCH1, NRAS, PIK3CA, PTEN, RB1, TP53, MET, AR, ABL1, AKT1, ATM, CDH1, CSF1R, CTNNB1, ERBB4, EZH2, FGFR1, FGFR2, FGFR3, FLT3, GNA11, GNAQ, GNAS, HNF1A, HRAS, IDH1, IDH2, JAK2, JAK3, KDR, KIT, MLH1, MPL, NPM1, PDGFRA, PROC, PTPN11, RET, SMAD4, SMARCB1, SMO, SRC, STK11, VHL, TERT, CCND1, CDK4, CDKN2B, RAF1, BRCA1, CCND2, CDK6, NF1, TP53, ARID1A, BRCA2, CCNE1, ESR1, RIT1, GATA3, MAP2K1, RHEB, ROS1, ARAF, MAP2K2, NFE2L2, RHOA, and NTRK1 [5:45-58]"
Eltoukhy further discloses at least two distinct analytical operations performed on the same sequencing data without re-sequencing:
"Sequence variation [associated with SNV] is detected by counting distribution of bases at each locus. If 98% of the reads have the same base (homozygous) and 2% have a different base, the locus is likely to have a sequence variant, presumably from cancer DNA " (first analytical tool - variant calling); and
"CNV is detected by counting the total number of sequences (bases) mapping to a locus and comparing with a control locus [54:36-43]" (second analytical tool - copy number analysis).
These are distinct "genetic tests" (SNV detection and CNV detection) each operating on a "portion of the data structure that is specific to the genetic test" (i.e., the loci/genes relevant to each test), and both are performed on the same sequencing data "without performing additional sequencing"]
Regarding [g], Eltoukhy discloses that "A quality score for each sequence is calculated and sequences are filtered based on the their quality scores [54:31-35]”. This constitutes determining a quality control value associated with a result of the analytical tool]
Eltoukhy does not explicitly disclose as disclosed by Jaganathan:
determining a quality control value for a result of the analytical tool; [This is the core teaching of Jaganathan. The patent is titled "ARTIFICIAL INTELLIGENCE-BASED QUALITY SCORING" and teaches: "Quality scoring refers to the process of assigning a quality score to each base call. Quality scores are defined according to the Phred framework, which transforms the values of predictive features of sequencing traces to a probability based on a quality table [53:1-54:67]"
Jaganathan further teaches: "For each of the four base call classes (A, C, T, and G), large numbers of sequencing images are used as training examples… [54:66-55:2] We observe that the base call was correctly predicted in ninety percent of the numerous instances… This means that for the 0.90 softmax score, the base calling error rate is 10% and the base calling accuracy rate is 90%, which in turn corresponds to quality score Q10”]
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Regarding [h], Eltoukhy discloses delivering a report; ["Patient test results comprising the genetic variants are listed in Table 4 " and that the assay is designed to "identify genetic variants in cancer-associated somatic variants with high sensitivity [55:33-56:55]" for clinical decision-making. The results are delivered to the ordering healthcare provider.]
Eltoukhy does not explicitly disclose as disclosed by Jaganathan:
in an event that a quality control value for a key result that is responsive to the request exceeds a predetermined threshold of quality for assisting the healthcare provider: delivering a report based upon the key result to the healthcare provider to complete the genetic testing (i.e., the interface being further operable to…); [This is the core teaching of Jaganathan. The patent is titled "ARTIFICIAL INTELLIGENCE-BASED QUALITY SCORING" and teaches: "Quality scoring refers to the process of assigning a quality score to each base call. Quality scores are defined according to the Phred framework, which transforms the values of predictive features of sequencing traces to a probability based on a quality table."
Jaganathan further teaches: "For each of the four base call classes (A, C, T, and G), large numbers of sequencing images are used as training examples… We observe that the base call was correctly predicted in ninety percent of the numerous instances… This means that for the 0.90 softmax score, the base calling error rate is 10% and the base calling accuracy rate is 90%, which in turn corresponds to quality score Q10." [Page 18]"]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Eltoukhy, including mechanism(s) [g]-[h] as taught by Jaganathan. One of ordinary skill would have been so motivated to employ said mechanism(s), combining Jaganathan’s quality scoring system with Eltoukhy multi-measure analytical framework, both references operating in the field of genetic testing and sequencing data analysis, Eltoukhy providing a specific framework of computing multiple quantitative measures from the same mapped read data and Jaganathan teaching multiple analytical tasks (quality scoring, variant classification) on stored data. Combining these would yield a system that operates multiple genetic test analytical tools on a stored data structure without additional sequencing.
Note: The "receiving a request from a healthcare provider" [a] and "delivering a report" [h] limitations are well-understood routine steps in clinical genetic testing workflows and do not add patentable significance when combined with the technical limitations above.
Regarding claim(s) 2, 9, 16, Eltoukhy-Jaganathan as a combination discloses: The method of claim 1, Jaganathan disclosing: further comprising:
receiving an additional request to have additional genetic testing performed on the patient; [Jaganathan teaches: "FIG. 55 shows various sequencing tasks that can be performed using the neural network-based base caller 218. Some examples include quality scoring (QScoring) and variant classification [53:1-58]"
Jaganathan teaches that the same stored sequencing data can support multiple analytical tasks, which is equivalent to receiving "an additional request" and "consulting the data structure."]
consulting the data structure without performing additional sequencing for the patient; [Jaganathan teaches reusing stored intermediate data: "The data flow logic 6397 can write intermediate data to the memory 6348A in place of the sensor data for a given patch of an array of tile data [73:26-39]" Jaganathan further teaches: "The processed and transformed images can be stored on the data cache 6404 for sensing cycles that were previously used [74:1-31]"
This teaches consulting a stored data structure (memory 6348A / data cache 6404) without performing additional sequencing.]
in an event that an additional quality control value for an additional key result that is responsive to the additional request exceeds a predetermined threshold of quality: delivering a report based upon the additional key result to complete the additional genetic testing; [Jaganathan discloses threshold-based quality determination: "Any base call with Q<20 should be considered low quality, and any variant identified where a substantial proportion of sequenced reads supporting the variant are of low quality should be considered potentially false positive [94:30-38]" . When the QC value exceeds the threshold, the result is reliable and a report can be delivered] and
in an event that the additional quality control value for the additional key result does not exceed the predetermined threshold of quality: attempting to re-run a corresponding analytical tool upon the data structure; [Jaganathan teaches: "In some implementations, a chastity filter 6010 terminates the base calling of a given cluster when the quality score 6008 assigned to its called base, or an average quality score over successive base calling cycles, falls below a preset threshold [58:1-33]"
The patent also teaches model updates: "model data, including kernel data like filter weights and biases can be sent from the host CPU to the configurable processor, so that the model can be updated as a function of cycle number… the trained parameters may be updated once every 20 cycles [75:1-36]"
This teaches re-running an analytical tool (updating model parameters) when quality thresholds are not met.]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Eltoukhy, including mechanism(s) [a]-[d] as taught by Jaganathan. One of ordinary skill would have been so motivated to employ said mechanism(s), as Jaganathan's quality-gated analysis system with Eltoukhy's multi-measure framework handle additional testing requests by consulting the same stored data structure, since both references operate in the same field of genetic data analysis.
Regarding claim(s) 3, 10, 17, Eltoukhy-Jaganathan as a combination discloses: The method of claim 2, wherein: attempting to re-run the corresponding analytical tool comprises attempting to run a version of the corresponding analytical tool which is newer than a version of the corresponding analytical tool that was originally operated upon the data structure. [Jaganathan explicitly teaches updating analytical tool versions: "model data, including kernel data like filter weights and biases can be sent from the host CPU to the configurable processor, so that the model can be updated as a function of cycle number. A base calling operation can comprise, for a representative example, on the order of hundreds of sensing cycles. Base calling operation can include paired end reads in some embodiments. For example, the model trained parameters may be updated once every 20 cycles (or other number of cycles), or according to update patterns implemented for particular systems and neural network models [75:21-21]". Jaganathan further teaches: "the trained parameters can be updated on the transition from the first part to the second part [75:35-37]"
This teaches re-running an analytical tool with an updated (newer) version of the model/parameters upon the same stored data structure]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Eltoukhy, including mechanism(s) [a] as taught by Jaganathan. One of ordinary skill would have been so motivated to employ said mechanism(s) to use a newer version of an analytical tool (updated model parameters) when quality thresholds are not met, as Jaganathan already teaches model updates as a function of cycle number and system configuration.
Regarding claim(s) 4, 11, 18, Eltoukhy-Jaganathan as a combination discloses: The method of claim 2, Jaganathan disclosing [a]: further comprising: preserving the biological sample in a laboratory and, in an event that re-running the analytical tool does not result in the additional quality control value exceeding the predetermined threshold, resequencing a portion of the biological sample at locations corresponding to the additional key result. [Jaganathan discloses target-specific sequencing: "the method includes obtaining input data that includes a sequence of per-cycle image patch sets generated for a series of sequencing cycles of a sequencing run”, and the system is configured to perform "resequencing of whole genomes or target genomic regions [62:38-50]”. Jaganathan further states: "high-throughput nucleic acid analyses include without limitation de nova sequencing, re-sequencing, whole genome sequencing”. The concept of re-sequencing specific loci (targeted re-sequencing) when quality is insufficient is well-established.]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Eltoukhy, including mechanism(s) [a] as taught by Jaganathan. One of ordinary skill would have been so motivated to employ said mechanism(s), combining Jaganathan’s quality scoring system with Eltoukhy multi-measure analytical framework, both references operating in the field of genetic testing and sequencing data analysis, Eltoukhy providing a specific framework of computing multiple quantitative measures from the same mapped read data and Jaganathan teaching multiple analytical tasks (quality scoring, variant classification) on stored data. Combining these would yield a system that operates multiple genetic test analytical tools on a stored data structure without additional sequencing, and re-sequence a portion of a preserved sample at specific locations when quality control thresholds are not met, as this is a standard quality assurance protocol in clinical genetics laboratories, Jaganathan explicitly contemplates re-sequencing of target regions.
Regarding claim(s) 5, 12, 19, Eltoukhy-Jaganathan as a combination discloses: The method of claim 1, Jaganathan disclosing: wherein: the quality control value is at least one of:
a callability of at least ninety-nine percent across genetic loci considered by the genetic test; [Jaganathan discloses quality metrics based on base calling accuracy: "if the quality score of a base is Q30, the probability that this base is called incorrectly is 0.001. This also indicates that the base call accuracy is 99.9% [53:39-58]”. A callability of 99% corresponds to a Q20 threshold, which Jaganathan explicitly discusses: "Any base call with Q<20 should be considered low quality [94:30-38]”. Jaganathan's quality scoring framework provides the mechanism for determining callability across genetic loci.
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Table above: 53:49-58]
at most 0,01 for a gene dispersion of the sequencing data associated with the called genetic variants;
at most five percent for a ratio of bacterial DNA to human DNA of the sequencing data associated with the called genetic variants; ["at most 0.01 for a gene dispersion of the sequencing data associated with the called genetic variants"
Jaganathan discloses error rate thresholds: "the base calling error rate is 10% and the base calling accuracy rate is 90%" for Q10, and for Q20…, "Error Probability: 0.01 (1 in 100) [See Table above]”. A gene dispersion of at most 0.01 corresponds to a Q20-level error probability threshold. Jaganathan's quality table explicitly maps quality scores to error probabilities]
or at least twenty for fold enrichment of the sequencing data associated with the called genetic variants;
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Eltoukhy, including mechanism(s) [a] as taught by Jaganathan. One of ordinary skill would have been so motivated to employ said mechanism(s), given that specific QC value thresholds (99% callability, 0.01 dispersion, 5% bacterial contamination, 20-fold enrichment) are well-known quality control metrics in clinical genomics. Jaganathan explicitly discloses quality thresholds based on error probabilities (Q20 = 0.01 error rate, Q30 = 0.001), and Eltoukhy's clinical system requires such QC metrics for regulatory compliance. Selecting specific numerical thresholds is a matter of routine optimization.
Regarding claim(s) 6, 13, 20, Eltoukhy-Jaganathan as a combination discloses: The method of claim 1, Jaganathan disclosing [a]: wherein: the data structure includes, for each genetic test, a record comprising a test name, a tool name, a corresponding portion of the called genetic variants, and a quality control value of the test. [Eltoukhy's system for "DETECTING GENETIC VARIANTS" in a clinical setting requires a data structure that associates tests with their results and quality metrics.
Jaganathan discloses a quality scoring framework where quality scores are correlated with classification scores: "correlating the quality scores to the quantized classification scores based on the fit [131:55-64]”, and a "quality score correspondence scheme [132:37-44]" that maps results to quality metrics. Jaganathan further discloses: "the data structure includes, for each genetic test, a record comprising a test name, a tool name, a corresponding portion of the called genetic variants, and a quality control value of the test" is structurally analogous to Jaganathan's quality scoring system where "for each of the four base call classes (A, C, T, and G), large numbers of sequencing images are used as training examples [54:66-55:1]" and quality scores are associated with specific results]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Eltoukhy, including mechanism(s) [a] as taught by Jaganathan. One of ordinary skill would have been so motivated to employ said mechanism(s) storing test metadata (name, tool, data portion, QC value) in a data structure is a well-known database design practice in bioinformatics and clinical laboratory information management systems (LIMS). Eltoukhy's clinical system inherently requires such metadata for regulatory traceability.
Regarding claim(s) 7, 14, 21, Eltoukhy-Jaganathan as a combination discloses: The method of claim 1, Jaganathan disclosing [a]: wherein: the analytical tool is operable to perform at least one bioinformatic operation selected from the group consisting of: sequence alignment, variant calling, haplotype calling, and imputation for genetic data. [Eltoukhy's patent title "METHODS AND SYSTEMS FOR DETECTING GENETIC VARIANTS" and its classification under C12Q 1/6869 directly correspond to variant calling. Jaganathan discloses: "The technology disclosed provides neural network based methods and systems that address these and similar needs" including "increasing the level of throughput in high-throughput nucleic acid sequencing technologies [7:3-19]”. Jaganathan further discloses: "sequence alignment" is referenced in the context of "aligning reads to the appropriate references”. Jaganathan's quality scoring framework operates on variant calls: "A quality score is a measure of the probability of a sequencing error in a base call" , and the system supports "variant classification" as one of the "sequencing tasks that can be performed using the neural network-based base caller 218”.
Regarding haplotype calling, Jaganathan discloses: "The term “haplotype” refers to a combination of alleles at adjacent sites on a chromosome that are inherited together [93:17-22]”. Regarding imputation, Jaganathan's framework for quality scoring and base calling supports imputation as a downstream analytical operation.]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Eltoukhy, including mechanism(s) [a] as taught by Jaganathan. One of ordinary skill would have been so motivated to employ said mechanism(s) as analytical tools (sequence alignment, variant calling, haplotype calling, imputation) are well-established bioinformatic operations. Eltoukhy's system for detecting genetic variants inherently employs variant calling, and Jaganathan's quality scoring system operates on the output of such tools. Combining these standard operations with the quality scoring framework is obvious.
Conclusion
The prior art made of record2 and NOT relied upon is considered pertinent to applicant's disclosure:
Babiarz (US 11,486,008):
The invention provides methods, systems, and computer readable medium for detecting ploidy of chromosome segments or entire chromosomes, for detecting single nucleotide variants and for detecting both ploidy of chromosome segments and single nucleotide variants. In some aspects, the invention provides methods, systems, and computer readable medium for detecting cancer or a chromosomal abnormality in a gestating fetus..
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL EZEWOKO whose telephone number is 571 272 7850. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached on 571 270 5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-7850.
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/MICHAEL I EZEWOKO/Primary Examiner, Art Unit 3682
1 Application 18/226,708
2Please see Form 892 for complete listing
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