DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Applicant's response, filed on 11/26/2025, is 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.
Status of claims
Canceled:
2-3, 5-6, 10, 13, 18-21, 24
Pending:
1, 4, 7-9, 11-12, 14-17, 22-23
Amended:
1, 11, 14-15
Withdrawn:
none
Examined:
1, 4, 7-9, 11-12, 14-17, 22-23
Independent:
1
Allowable:
none
Priority
As detailed on the 10/14/2021 filing receipt, this application claims priority to as early as 07/27/2020.
Information Disclosure Statement
The Information Disclosure Statements filed on 11/28/2025 and on 02/13/2026 are compliance with the provisions of 37 CFR 1.97 and have been considered in full. A signed copy of the list of references cited from each IDS is included with this Office Action.
Withdrawn Rejections/Objections
The rejection of claims 1, 4, 7-17 and 22-23 under 35 U.S.C. §112(a), in the Office action mailed 06/30/2025 is withdrawn in view of the amendments filed 11/26/2025.
The rejection of claims 1, 4, 7, 10-17 and 22-23 under 35 U.S.C. §103 over Bell in view of Nicula and Chereji, in the Office action mailed 06/30/2025 is withdrawn in view of the amendments and remarks filed 11/26/2025.
The rejection of claims 8-9 under 35 U.S.C. §103 over Bell in view of Nicula and Chereji and further in view of Luo and Yi, in the Office action mailed 06/30/2025 is withdrawn in view of the amendments and remarks filed 11/26/2025.
The rejection of claims 1, 7, 12 and 13 on the ground of nonstatutory double patenting as being unpatentable over claims 1, 3-5 and 17 of copending Application No. 17/534,368 (reference application) is withdrawn in view of the amendments filed 11/26/2025.
Regarding 35 USC 103 -- no prior art applied
No prior art is applied to claims 1, 4, 7-9, 11-12, 14-17 and 22-23. The claims overcome the closest prior art to Bell (as cited on the 07/21/2022 Office Action and 02/14/2025 "Notice of References Cited" form 892) and Nicula (as cited on the 07/21/2022 "Notice of References Cited" form 89). Bell teaches determining a homologous recombination deficiency (HRD) status of a DNA sample using machine learning models. Nicula teaches binning of the reference genome and arranging coverage signals into one- and two-dimensional vectors. However, Bell and Nicula do not teach "wherein the reference genome is divided into a first set of at most 100kbp bins and further comprising a step of collapsing the 100kbp bins into a second set of bins of at least 500kbp prior to arranging the coverage signals of the chromosome arm into the coverage signal array" in claim 1. It is not clear that any combinable art of record would have rendered the claims obvious.
Response to 35 USC § 103 Remarks received 11/26/2025
Applicant’s remarks, see pages 6-12, filed 11/26/2025, with respect to the rejection(s) of claim(s) 1, 4, 7-17 and 22-23 under 35 USC § 103 have been fully considered and are persuasive. Therefore, the rejections have been withdrawn.
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, 4, 7-9, 11-12, 14-17 and 22-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claim 1 recites determining the HRD status of the patient DNA sample… aligning the sequencing reads of the subject DNA sample to a reference genome, wherein the reference genome is divided into a plurality of bins, each bin belonging to a same genomic region of a chromosome arm in the reference genome to be analyzed; counting and normalizing the number of aligned reads in each bin along each chromosome arm, to obtaining a coverage signal on each chromosome arm based on the step of counting and normalizing the number of aligned reads in each bin along each chromosome arm; arranging the coverage signals of the chromosome arms into a coverage data signal array for the subject DNA sample, comprising: arranging the coverage signals of the chromosome arms into a 1D coverage data signal vector or a 2D coverage data signal array, arranging the coverage signals of the chromosome arms into a the 2D coverage data signal array comprising aligning in rows the coverage data signal for each chromosome with respect to a centromeric bin of each chromosome arm, that is the bin adjacent to the centromere region of the chromosome arm; determining and outputting, via the trained machine learning model, a homologous recombination deficiency score (HRD score) of the subject DNA sample, and determining a negative, a positive or an uncertain homologous recombination deficiency (HRD) status of the subject DNA sample according to the HRD score out of the trained machine learning model.
Claim 4 recites wherein counting and normalizing the number of aligned reads in each bin along each chromosome arm to obtain a coverage signal on the chromosome arm comprises normalizing the coverage signal per sample, and/or normalizing by GC content to apply a GC-bias correction.
Claim 7 recites wherein the plurality of samples of known homologous recombination deficiency status are tumor data samples with a known homologous recombination deficiency status.
Claim 8 recites tumor data samples with a known homologous recombination deficiency status are augmented with artificial sample data generated by combining data from chromosomes of the tumor data samples with a known homologous recombination deficiency status label, forming data augmented samples.
Claim 9 recites wherein the data augmented samples are generated in order to represent a purity-ploidy ratio distribution as observed in the tumor data samples.
Claim 12 recites a method for selecting a cancer patient for treatment with a platinum-based chemotherapeutic agent, a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor, the method comprising the step of detecting that a tumor patient sample is HRD positive using the method of claim 1.
Claim 14 recites wherein the patient DNA sample is a tumor cell-free DNA (cfDNA), a fresh-frozen tissue (FFT) or a formalin-fixed paraffin-embedded (FFPE) sample.
Claim 15 recites wherein an HRD score or the HRD status of the patient DNA sample is a predictor of a tumor response to a cancer treatment regimen, wherein the patient DNA sample is of a cancer patient.
Claim 17 recites wherein the patient has a cancer, and wherein the cancer is a high grade serous ovarian cancer.
Claim 23 recites converting the coverage data signal array into a coverage data signal image; and inputting the coverage data signal image to the trained machine learning model, wherein the model has been further trained using coverage signal images for a plurality of samples of known homologous recombination deficiency status to distinguish between the coverage data signal image from samples with a positive homologous recombination deficiency status and the coverage data signal image from samples with a negative homologous recombination deficiency status.
The processes of claim 1 includes aligning reads, determining HRD status and score, arranging data into an array, which could be practically performed in the human mind with pen and paper. Claim 12 includes the process of selecting a cancer patient and claim 12 include determining a HRD status. Selecting could be accomplished by choosing from a list. Therefore, under the broadest reasonable interpretation, the claims can be practically carried out in the human mind or with pen and paper as claimed, which falls under the "Mental processes" grouping of abstract ideas. Although, claims 1 and 12 recites performing the method as part of a method executed on a computer, there are no additional imitations to indicate that anything other than a generic computer is required. However, merely requiring that the steps are carried out with a generic computer does not negate the mental nature of these steps and equates rather to merely using a computer as a tool to perform the mental process. The processes of claim 1 include generating a data array and trained machine learning model; claim 4 include the counting and normalizing and claim 9 includes determining a purity-ploidy ratio distribution that are mathematical concepts and/or formulas and requires carrying out a series of mathematical calculations, which falls under the “mathematical concepts” grouping of abstract ideas. Claims 14 and 15 recites the patient DNA sample and claim 12 and 17 recites the cancer patient, which are laws of nature. Claims 1, 8, 9, 12, 15, and 23 recite a correlation between the subject DNA sample and HRD status. This is similar to the concept of a correlation between a patient’s genotype and risk of QTc prolongation in Vanda Pharmaceuticals Inc. v. West-Ward Pharmaceuticals, 887 F.3d 1117, 1135-36, 126 USPQ2d 1266, 1281 (Fed. Cir. 2018) that the courts identified as a natural phenomenon. As such, claims 1, 4, 7-9, 11-12, 14-17 and 22-23 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception in some other meaningful way.
Claim 1 recites A computer-based method of determining a homologous recombination deficiency (HRD) status of a subject DNA sample, the method comprising the steps of:(a) extracting and isolating fragments of DNA from a patient DNA sample:(b) constructing a sequencing library comprising the fragments of DNA from the patient DNA sample overlapping a set of chromosomes (c) sequencing, via whole genome sequencing, the sequencing library to a read depth is of at least 0.1X and at most 5X; obtaining sequencing reads of the subject DNA sample to be analyzed; wherein the sequencing reads are obtained via low pass whole genome sequencing of the subject DNA sample; wherein the reference genome is divided into a first set of at most 100kbp bins and further comprising a step of collapsing the 100kbp bins into a second set of bins of at least 500kbp prior to arranging the coverage signals of the chromosome arm into the coverage signal array; inputting the coverage data signal array to a trained machine learning model, wherein the model has been trained using coverage signal arrays for a plurality of samples of known homologous recombination deficiency status to distinguish between the coverage data signal array from samples with a positive homologous recombination deficiency status and the coverage data signal array from samples with a negative homologous recombination deficiency status
Claim 11 recites wherein the bins of the first set of bins have a uniform size of at most 100kbp and the bins of the second set of bins have a size of between 2.5 to 3.5 Mbp and are obtained by pooling between 25 to 35 100kbp bins from the first set of bins.
Claim 16 recites wherein the cancer treatment regimen is-a radiation therapy.
Claim 22 recites wherein the trained machine learning model is a Convolutional Neural Network (CNN) model.
The processes of claim 1 include extracting and isolating fragments of DNA, constructing a sequencing library, sequencing, obtaining sequencing reads, obtaining a coverage signal and inputting the coverage data signal array to a trained machine learning model, which equate to mere data gathering and outputting activities. Claim 1 also recites a generic computer environment and methods of obtaining data that serves as input to the recited judicial exception in the claims. The limitations of claim 11 is providing information on the size and depth of the data and do not require that the particular data generating processes be performed. Claim 16 is providing information of the cancer treatment regimen and claim 22 is providing information on the type of machine learning model. Therefore, these limitations do not change the character of the obtaining data step beyond mere data gathering activity. Claims 4, 7-9, 12, 14-15, 17, and 23 do not recite any elements in addition to the judicial exception. As such, as currently recited, the claims do not appear to recite an improvement to technology or apply or use the recited judicial exception in some other meaningful way. Therefore, claims 1, 4, 7-9, 11-12, 14-17 and 22-23 are directed to an abstract idea (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to well-understood, routine and conventional activities, insignificant extra-solution activity or mere instructions to implement the abstract idea on a generic computer. The instant claims recite the following additional elements:
Claim 1 recites A computer-based method of determining a homologous recombination deficiency (HRD) status of a subject DNA sample, the method comprising the steps of:(a) extracting and isolating fragments of DNA from a patient DNA sample:(b) constructing a sequencing library comprising the fragments of DNA from the patient DNA sample overlapping a set of chromosomes (c) sequencing, via whole genome sequencing, the sequencing library to a read depth is of at least 0.1X and at most 5X; obtaining sequencing reads of the subject DNA sample to be analyzed; wherein the sequencing reads are obtained via low pass whole genome sequencing of the subject DNA sample; wherein the reference genome is divided into a first set of at most 100kbp bins and further comprising a step of collapsing the 100kbp bins into a second set of bins of at least 500kbp prior to arranging the coverage signals of the chromosome arm into the coverage signal array; inputting the coverage data signal array to a trained machine learning model, wherein the model has been trained using coverage signal arrays for a plurality of samples of known homologous recombination deficiency status to distinguish between the coverage data signal array from samples with a positive homologous recombination deficiency status and the coverage data signal array from samples with a negative homologous recombination deficiency status
Claim 11 recites wherein the bins of the first set of bins have a uniform size of at most 100kbp and the bins of the second set of bins have a size of between 2.5 to 3.5 Mbp and are obtained by pooling between 25 to 35 100kbp bins from the first set of bins.
Claim 16 recites wherein the cancer treatment regimen is-a radiation therapy.
Claim 22 recites wherein the trained machine learning model is a Convolutional Neural Network (CNN) model.
Limitations that equate to mere data gathering and outputting via generic computer components, such as receiving data at a computer or outputting data, amount to insignificant extra-solution activity as set forth by the courts in Mayo, 566 U.S. at 79, 101 USPQ2d at 1968 and OIP Techs., Inc, v, Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Also, the courts have recognized that detecting DNA or enzymes in a sample, analyzing DNA to provide sequence information or detecting allelic variants and amplifying and sequencing nucleic acid sequences as well-understood, routine, conventional activity in the life science arts when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05(d)). Additionally, methods for extracting and isolating fragments of DNA, constructing a sequencing library and sequencing are well-known conventional methods as disclosed by Anson ("DNA extraction from primary liquid blood cultures for bloodstream infection diagnosis using whole genome sequencing." Journal of Medical Microbiology 67.3 (2018): 347-357.; as cited on the attached “Noticed of References cited” 892 form). Also, low-pass whole genome sequencing is commercially available as disclosed by BGI (Low-Pass Whole Genome Sequencing. BGI Americas. 2018; as cited on the 06/30/2025 “Noticed of References cited” 892 form). Therefore, methods for extracting and isolating fragments of DNA, constructing a sequencing library, sequencing and lp-WGS are well-understood, routine and conventional methods. The use of machine learning models to analyze genomic data is also a known method. Evidence that these steps, in combination, are well-understood, routine and conventional in the field can be found in Leung, Michael KK, et al. "Machine learning in genomic medicine: a review of computational problems and data sets." Proceedings of the IEEE 104.1 (2015): 176-197; as cited on the 07/21/2022 “Noticed of References cited” 892 form. In particular, see Leung pg 179-180 under Section III; pg. 183-184 Figure 6 and 1) Sequencing, 2) Microarrays and 3) Basic computational models and, pg. 185 Section IV. Overall, the additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Claims 4, 7-9, 12, 14-15, 17, and 23 do not recite additional limitations. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1, 4, 7-9, 11-12, 14-17 and 22-23 are not patent eligible.
Response to 35 USC § 101 Remarks received 11/26/2025
Applicant amended claims 1, 11 and 14-15.
It is noted that Applicant’s remarks are based on amended claims.
In Applicant's remarks for Claim Rejections under 35 U.S.C. §101, see pages 12-14, Applicant states that amended claim 1 recites the limitation "extracting and isolating fragments of DNA from a patient DNA sample." Applicant states that the limitation is a step that must be performed physically and cannot practically be performed in the human mind, nor with any kind of computer, generic or otherwise. Therefore, Applicant asserts that the instantly amended claim 1 is not directed to an abstract idea without significantly more.
In response, Applicants' remarks have been fully considered and are not persuasive. The process of extracting and isolating fragments of DNA from a patient DNA sample amounts are additional elements that amount to mere data gathering and is a field of use or insignificant extra solution activity. As indicated in MPEP 2106.05(g), data gathering is insignificant extra solution activity and a data gathering step that is limited to a particular data source or a particular type of data could be considered to be both insignificant extra-solution activity and a field of use limitation. Also, the courts have also recognized that techniques for detecting DNA or enzymes in a sample, analyzing DNA to provide sequence information or detecting allelic variants and amplifying and sequencing nucleic acid sequences as well-understood, routine, conventional activity in the life science arts when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. (See MPEP 2106.05(d)). Therefore, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to well-understood, routine and conventional activities, insignificant extra-solution activity or mere instructions to implement the abstract idea on a generic computer. As discussed in the 101 rejection section above, the additional elements equate to mere data gathering and outputting via generic computer components, such as receiving data at a computer or outputting data, amount to insignificant extra-solution activity as set forth by the courts in Mayo, 566 U.S. at 79, 101 USPQ2d at 1968 and OIP Techs., Inc, v, Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Also, the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more as identified by the courts in Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Overall, the additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception.
Conclusion
No claims are allowed.
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.
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/K.K./Examiner, Art Unit 1686
/LARRY D RIGGS II/ Supervisory Patent Examiner, Art Unit 1686