DETAILED ACTION
Applicant's response, filed 6/17/2025, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 .
Claims Status
Claims 1-18 and 46 are pending.
Claims 1-18 and 46 are rejected.
Specification
Response to Amendment
In view of applicant’s amendments to the specification, the prior objection to the specification is withdrawn.
Drawings
Response to Amendment
In view of applicant’s amendments to the specification, the prior objection to the drawings is withdrawn.
Claim Objections
Claim 14 objected to because of the following informalities: insert a “wherein” between “claim 12” and “one or more target genes”. Appropriate correction is required.
Claim Rejections - 35 USC § 101
Response to Amendment
In view of applicant’s amendments to the claims, the prior analysis of the claims under 35 U.S.C. 101 has been updated and is provided below.
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1-18 and 46 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claims recite a method of. This judicial exception is not integrated into a practical application because while claim 1 attempt to integrate the exception into a practical application, said practical application is a generically recited computer element that does not add a meaningful limitation to the abstract idea as it is 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 computer systems (claims 1-18, and 46).
Step 2A Prong One: Do the claims recite a judicially recognized exception, i.e., an abstract idea, law of nature, or natural phenomenon? [see MPEP § 2106.04(a)]
The claims herein recite abstract ideas.
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 mathematical concepts.
The following claims recite abstract ideas (mathematical concepts):
Claim 1: Mapping the sequence reads to the reference sample, generating a copy number score, filtering regions, partitioning the sequence into a plurality of segments, extracting a copy number segment score, generating a segment weight, generating a weighted score, aggregating the weighted scores, and generating a diagnostic and therapeutic report based on the CNV prediction, are all processes of collecting, comparing/contrasting, calculating, and summarizing data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 2: Training the machine learning classifier via maximum likelihood, is a verbal articulation of a mathematical process, specifically a mathematical concept.
Claim 3: Training the machine learning classifier via a Hidden Markov Model, is a verbal articulation of a mathematical process, specifically a mathematical concept.
Claim 4: Training the machine learning classifier via Bayesian inference, is a verbal articulation of a mathematical process, specifically a mathematical concept.
Claim 5: Retrieving correlation parameters, applying a machine learning classifier, generating a prediction of the locus, and predicting a disease condition are processes of collecting, comparing/contrasting, calculating, and summarizing data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 6: The genetic material comprising cell free DNA is directed to the data itself, which is an abstract idea, rendering this an abstract idea, specifically a mental process.
Claim 7: Determining a level of deletion of the chromosome is a process of assessing and comparing information which can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 8: Determining the physical distance between the segment and locus of interest is a process of assessing and comparing information which can be done via pen and paper or within the human mind and is therefore an abstract idea, specifically a mental process.
Claim 9: Analyzing sequence coverage information are processes of collecting, comparing/contrasting, and calculating data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 10: Generating a prediction that the locus of interest is in the second genetic state is a process of comparing/contrasting, and calculating data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 11: Generating a prediction that the locus of interest is in the second genetic state is a process of comparing/contrasting, and calculating data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 12: The locus of interest being associated with the disease condition is directed to the data itself, which is an abstract idea, rendering this an abstract idea, specifically a mental process.
Claim 13: The locus of interest comprising an HLA locus is directed to the data itself, which is an abstract idea, rendering this an abstract idea, specifically a mental process.
Claim 14: One or more target genes and one or more reference genes not being in the same regulation pathway is directed to the data itself, which is an abstract idea, rendering this an abstract idea, specifically a mental process.
Claim 15: The target genes being in genetic linkage with referene genes is directed to the data itself, which is an abstract idea, rendering this an abstract idea, specifically a mental process. Identifying one or more segments to analyze is a process of comparing/contrasting and picking data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 16: The first genetic state comprising at least of the specified states listed in the group provided is directed to the data itself, which is an abstract idea, rendering this an abstract idea, specifically a mental process.
Claim 17: Determining a treatment based on the predicted disease condition is a process of comparing/contrasting, and calculating data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 18: Determining a segment includes a copy number loss, and determining that the locus of interest also includes a copy number loss are processes of comparing/contrasting, calculating, and summarizing data that can be done via pen and paper or within the human mind and are therefore abstract ideas, specifically mental processes.
Claim 46: Partitioning the sequence into a plurality of segments is a process of selecting and dividing information that can be done via pen and paper or within the human mind and is therefore 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)]
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:
Claim 1: A computer system, memory, and a processor are 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)]. Accessing a plurality of sequence reads is an insignificant extra solution activity, specifically mere data gathering [See MPEP § 2106.04(g)]. A reference sequence comprising a sequence of interest and locus of interest, and a segment-performance data comprising data associated with historical performance of a given segment are further limiting the data stored on the memory but there is no indication that the data type is changing it from a generic computer data storage (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 § 2106.04(d)(II)].
Claim 5: A computer system, non-transitory memory, and a processor are 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)]. Accessing a plurality of sequence reads is an insignificant extra solution activity, specifically mere data gathering [See MPEP § 2106.04(g)]. A reference sequence comprising a sequence of interest and locus of interest, and a segment-performance data comprising data associated with historical performance of a given segment are further limiting the data stored on the memory but there is no indication that the data type is changing it from a generic computer data storage (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 § 2106.04(d)(II)].
Claim 9: Accessing a plurality of sequence reads is an insignificant extra solution activity, specifically mere data gathering [See MPEP § 2106.04(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 or law of nature 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 exceptions because the claims recite additional elements that are generic, conventional, or nonspecific. These additional elements include:
The additional elements of a computer system, memory, non-transitory memory, and a processor are 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 (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), 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 a reference sequence comprising a sequence of interest and locus of interest, and a segment-performance data comprising data associated with historical performance of a given segment are further limiting the data stored on the memory but there is no indication that the data type is changing it from a generic computer data storage which is just conventional data storage (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 § 2106.04(d)(II)].
The additional element of accessing a plurality of sequence reads (Conventional: Specification Paragraph [0081]) is an insignificant extra solution activity, specifically mere data gathering (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 § 2106.04(g)].
Therefore, claims 1-18, and 46, when the limitations are considered individually and as a whole, are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's arguments filed 6/17/2025 have been fully considered but they are not persuasive. Applicant argues that the use of mental process and mathematical concepts to define the content of claims 1-5 is improper as the claims recite process that cannot be performed practically within the human mind, specifically citing that “the human mind cannot physically form a "segment-performance data store", "aggregate the weighted scores into machine learning (ML) input data and input the ML input data to a trained ML copy-number classifier whose parameters were iteratively trained, using the segment- performance data store, to generate a CNV prediction at the locus of interest", and "apply a trained machine-learning (ML) classifier, the trained ML classifier having parameters that were iteratively trained using the segment-performance datastore, to the one or more correlation parameters and the detected first genetic state to generate a prediction that the locus of interest is in the second genetic state, wherein the second genetic state is either identical to or different from the first genetic state". However, a segment performance data store is merely an additional output but the mere presence of additional elements does not negate the fact that the claims also recite judicial exceptions, while aggregating weighted scores and iteratively training a machine learning classifier using particular data are merely collecting information and performing repetitive calculation, and applying a trained machine-learning (ML) classifier to generate a prediction is merely performing calculations within a mathematical model to generate a particular outcome. The mere use of machine learning or computer memory does not preclude human capability, rather examiner directs applicant’s attention to MPEP 2106.04(a)(2)(III).B “The use of a physical aid (e.g., pencil and paper or a slide rule) to help perform a mental step (e.g., a mathematical calculation) does not negate the mental nature of the limitation, but simply accounts for variations in memory capacity from one person to another”. A segment of DNA is interpretable by a human, and alignments, segmentation and use of scoring functions, weighted or not, are also interpretable and executable by the human mind.
Additionally, applicant asserts that no mathematical relationships or formulas are recited in any limitations. Examiner directs applicant to claims 2-4, which claim maximum likelihood estimation, Hidden Markov Models, and Bayesian inference, all of which are mathematical formulas/models for training machine learning.
Furthermore, applicant asserts that the claims “recite a combination of additional elements beyond the alleged judicial exception”, specifically “additional elements, including but not limited to, "a reference sequence", "a segment-performance data store", "a copy number score", an "ML copy-number classifier" or "ML classifier"”. However, examiner directs applicant to the updated analysis above, but in summary, "a reference sequence", and "a copy number score" are directed to the data itself which is not patent eligible as it is directed to data itself, which is an abstract idea; a "ML copy-number classifier" or "ML classifier" can be considered an additional element but only if said machine learning tool is specific and not generic; and "a segment-performance data store" is merely memory within a computer which is generic.
Applicant further asserts an improvement to technology citing both McRO, CardioNet, as well as Uniloc, which are directed to cases in which the invention improves upon the functioning of the computer itself, now being able to perform a task which it was previously incapable of performing. However, examiner directs applicant to MPEP 2106.05(a) - “It is important to note, the judicial exception alone cannot provide the improvement”, the “ability to resolve the genetic state of a locus”, “the HLA locus”, “quantitative prediction of copy-number loss, gain, or other variant”, "copy-number score", and the "unknown" field, are all abstract ideas or judicial exceptions. Applicant has not provided any indication of the additional elements recited in the claim that either individually or in combination with the judicial exception provide the asserted improvement to technology.
Claim Rejections - 35 USC § 103
Response to Amendment
In view of applicant’s amendments to the claims, an updated prior art search was performed.
Response to Arguments
Applicant’s arguments filed on 6/17/2025, with respect to 35 U.S.C. 103 have been fully considered and are persuasive. The rejections under 35 U.S.C. 103 of claims 1 and 5 have been withdrawn. As such so too are rejections under 35 U.S.C. 103 of all dependent claims.
Subject Matter Potentially Free Over Prior Art
In view of the current amendments specifically for claims 1 and 5 “a segment-performance data store comprising data associated with historical performance of a given segment at predicting a CNV at the locus of interest across a plurality of samples of different subjects”, in addition to “partition, based on the segment-performance data store, the sequence of interest into a plurality of segments” and “aggregate the weighted scores into machine learning (ML) input data and input the ML input data to a trained ML copy-number classifier whose parameters were iteratively trained, using the segment-performance data store”, are not found within a search of the prior art. Specifically while databases exist for the express purpose of developing and benchmarking CNV prediction models such as DGV, dbVAR, ClineGen, TCGA, GDC, etc., there is no collection of CNV segment level performance data. The cited such as ClinGen provide a region name, the location on the chromosome of the region, whether they believe there is sufficient evidence to link to a clinical outcome, and a list of appearances in previous research. Comparatively however, the claimed invention uses segments of regions and stores historical performance to predict a CNV at a locus of interest specifically storing multiple tests across multiple samples across multiple individuals, which are then used to generate predictions. The most similar prior art found was a paper by Zhang et al. (PLoS computational biology (2015) 1-27), which uses segmentation but also read depth to classify CNV regions as SCNAs or not. While this method is similar in use of its segmentation and classification of CNV regions it does not use historical performance of the region segmentations nor does it solely do so, but rather relies on read depth. As such no adequate teachings were found to read fully on claims 1 and 5 of the current application and as such, all dependent claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEENAN NEIL ANDERSON-FEARS whose telephone number is (571)272-0108. The examiner can normally be reached M-Th, alternate F, 8-5.
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/K.N.A./ Examiner, Art Unit 1687
/OLIVIA M. WISE/ Supervisory Patent Examiner, Art Unit 1685