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 .
Claim Status
Claims 1-20 are currently pending and under examination herein.
Claim(s) 1-20 are rejected.
Priority
The instant application also claims benefit to U.S. provisional application No. 63413539 filed on 10/05/2022. Domestic benefit is acknowledged. As such, the effective filing date of claims 1-20 is 10/05/2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/26/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. A signed copy of a list of references cited from each IDS is included in this Office Action.
Drawings
The drawings filed on 10/05/2023 are accepted.
Specification
The specification filed on 10/05/2023 is accepted.
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 1-20 are rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea and/or a natural phenomenon 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).
Claims 1, 11, and 20 recite computing, using a processor associated with the computing device, methylation beta values for one or more CpG-sites identified in the sequencing data, identifying, using the processor, one or more differentially methylated regions (DMRs) based on statistical analysis of the methylation beta-values for the one or more CpG-sites; selecting, using the processor and via a feature selection process, a subset of the one or more DMRs to utilize as training data; and training, using the processor and the training data, the classifier to predict the survival outcome of the at least one patient.
Claim 4 and 14 recites wherein the feature selection process corresponds to a principal component analysis technique.
Claim 5 and 15 recites wherein the classifier is a principal component random forest classifier.
Claim 6 and 16 recites assessing a performance of the classifier utilizing nested cross-validation.
Claim 7 and 17 recites wherein the nested cross-validation is further utilized to optimize hyperparameters in the training data.
Claim 8 and 18 recites wherein the training the classifier comprises configuring the classifier to generate a score that is associated with the survival outcome.
Claim 9 and 19 recites wherein the survival outcome is a binarized survival outcome designation.
Claim 10 recites wherein the training data further includes one or more clinical variables associated with the at least one patient.
The limitations reciting computing, using a processor associated with the computing device, methylation beta values for one or more CpG-sites identified in the sequencing data and training, using the processor and the training data, the classifier to predict the survival outcome of the at least one patient is a mathematical computation which falls under the “mathematical concept” grouping of ideas.
The limitations reciting identifying, using the processor, one or more differentially methylated regions (DMRs) based on statistical analysis of the methylation beta-values for the one or more CpG-sites; selecting, using the processor and via a feature selection process, a subset of the one or more DMRs to utilize as training data fall under the “mental process” grouping of ideas. Evaluation and selection based on presented data can be performed practically in the human mind or with a pen and paper and are therefore abstract ideas.
The limitations reciting wherein the feature selection process corresponds to a principal component analysis technique; wherein the classifier is a principal component random forest classifier; assessing a performance of the classifier utilizing nested cross-validation; wherein the nested cross-validation is further utilized to optimize hyperparameters in the training data; wherein the training the classifier comprises configuring the classifier to generate a score that is associated with the survival outcome; wherein the survival outcome is a binarized survival outcome designation; wherein the training data further includes one or more clinical variables associated with the at least one patient merely serve to further limit the abstract ideas recited above. As such, claims 1-20 recite abstract ideas.
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 additional elements that reflects an improvement to technology or applies or uses the recited judicial exception in some other meaningful way. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment. Specifically, the claims recite the following additional elements:
Claims 1, 11, and 20 recite receiving, at a computing device, DNA sequencing data derived from a methylation assay performed on a biological sample associated with the at least one patient.
Claim 2 and 12 recites wherein the methylation assay is a cell-free DNA targeted methylation assay and the biological sample is one of: a blood plasma sample or a blood serum sample.
Claim 3 and 13 recites wherein the methylation assay is a whole-genome bisulfite sequencing (WGBS) assay and wherein the biological sample is bone marrow tissue.
Claim 11 recites a system.
Claim 20 recites a non-transitory computer-readable medium.
The limitations reciting receiving, at a computing device, DNA sequencing data derived from a methylation assay performed on a biological sample associated with the at least one patient amount to insignificant data gathering.
The limitations reciting wherein the methylation assay is a cell-free DNA targeted methylation assay and the biological sample is one of: a blood plasma sample or a blood serum sample and wherein the methylation assay is a whole-genome bisulfite sequencing (WGBS) assay and wherein the biological sample is bone marrow tissue merely serve to further limit the data gathering step.
Furthermore, there are no limitations that indicate that the claimed computer, processor, input device or computer-readable medium require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. As such, claims 1-20 do not integrate the abstract idea into a practical application.
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 amount to mere instructions to implement the abstract idea in a generic field-of-use and/or technological environment. The instant claims recite the following additional elements:
Claims 1, 11, and 20 recite receiving, at a computing device, DNA sequencing data derived from a methylation assay performed on a biological sample associated with the at least one patient.
Claim 2 and 12 recites wherein the methylation assay is a cell-free DNA targeted methylation assay and the biological sample is one of: a blood plasma sample or a blood serum sample.
Claim 3 and 13 recites wherein the methylation assay is a whole-genome bisulfite sequencing (WGBS) assay and wherein the biological sample is bone marrow tissue.
Claim 11 recites a system.
Claim 20 recites a non-transitory computer-readable medium.
The limitations reciting receiving, at a computing device, DNA sequencing data derived from a methylation assay performed on a biological sample associated with the at least one patient; wherein the methylation assay is a cell-free DNA targeted methylation assay and the biological sample is one of: a blood plasma sample or a blood serum sample; and wherein the methylation assay is a whole-genome bisulfite sequencing (WGBS) assay and wherein the biological sample is bone marrow tissue are well-understood, routine, and conventional activities within the art. The courts have identified a variety of laboratory techniques as well-understood, routine, conventional activities within the life science arts. Namely, the laboratory activities of determining the level of a biomarker in blood by any means, *Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352, 1362, 123 USPQ2d 1081, 1088 (Fed. Cir. 2017)); detecting DNA or enzymes in a sample (Sequenom, 788 F.3d at 1377-78, 115 USPQ2d at 1157); Cleveland Clinic Foundation 859 F.3d at 1362, 123 USPQ2d at 1088 (Fed. Cir. 2017)); and analyzing DNA to provide sequence information or detect allelic variants (Genetic Techs. Ltd., 818 F.3d at 1377; 118 USPQ2d at 1546) are conventional activities. Furthermore, the courts have identified steps of receiving data over a network or storing and retrieving information in memory as conventional computer functions in 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 Versata Dev. Group, Inc. V. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
As aforementioned, there are no limitations that indicate that the claimed computer, processor, input device or computer-readable medium require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. Of note, the court considered the additional elements individually, noting that all the computer functions were “‘well-understood, routine, conventional activit[ies]’ previously known to the industry," each step “does no more than require a generic computer to perform generic computer functions”, and the recited hardware was “purely functional and generic” (573 U.S. at 225-26, 110 USPQ2d at 1984-85).
There are no additional elements that comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Drake et al. (US20210174958A1) as filed in the IDS on 2/23/2024.
Regarding claims 1, 11, and 20, Drake teaches:
A computer-implemented method (computing disclosed throughout in the pipeline; see [0024] for computer system, [0046]-[0050] for further explicit disclosure) for building a classifier to predict a survival outcome in at least one patient diagnosed with Myelodysplastic Syndrome (MDS), (explicitly describes methods of analyzing biological analytes that are readily obtained to stratify individuals at risk of or who have cancer and to provide effective characterization of early stage cancer to guide treatment decisions in [0016]; see [0397] for explicit disclosure of myelodysplastic syndromes; see also [0129] which explicitly discloses that the prognosis is a representation of the likelihood that the subject will survive) comprising:
receiving, at a computing device, DNA sequencing data derived from a methylation assay performed on a biological sample associated with the at least one patient (see step 210 in Fig. 2 for the pipeline; see also paragraph [0225] where details of the obtaining sequencing information is explained and [0230] where cfDNA Assays of Methylation is disclosed)
computing, using a processor associated with the computing device, methylation beta values for one or more CpG-sites identified in the sequencing data (as per [0065] of the Applicant’s specification, methylation beta values represent the degree of DNA methylation at a specific CpG site or region and are calculated as the ratio of the methylated signal intensity to the sum of the methylated and umethylated signal intensities at each CpG site; see [0236]-[0237] where base-wise methylation percentages are one of many metrics in methylation analysis; see also [0495]-[0497] for explicit recitation of a ratio between methylated and unmethylated CpG sites);
identifying, using the processor, one or more differentially methylated regions (DMRs) based on statistical analysis of the methylation beta-values for the one or more CpG-sites (see [0245] for explicit recitation that the methylation analysis is Differentially Methylated Region (DMR) analysis which are used to quantitate CpG methylation over regions of the genome and further describes the steps of DMR analysis);
selecting, using the processor and via a feature selection process, a subset of the one or more DMRs to utilize as training data (see [0493] where DMRs are used for CpG sites and is explicitly stated that it is possible to take a number of samples from different classes and discover which regions are the most differentially methylated between the different classifications. One then selects a subset to be differentially methylated and uses these for classification)
and training, using the processor and the training data, the classifier to predict the survival outcome of the at least one patient (see [0320] where training samples are used for training various for different purposes such as the aforementioned classification of a condition, of a treatment, of a prognosis, and more. A good cancer prognosis can correspond to when the individual is has the potential for symptom resolution or improvement or is expected to recover after treatment (e.g., a tumor is shrinking, or cancer is not expected. to return) as used herein refers to prognosis associated with disease. forms that are less aggressive and/or more treatable. For example, less aggressive more treatable forms of cancer have higher expected survival than more aggressive and/or less treatable forms. In various examples, a good prognosis refers to a tumor staying the same size or decreasing in response to treatment, remission or improved overall survival).
The Examiner notes that Drake discloses a computer-implemented method, system, and non-transitory computer readable medium throughout the disclosure (see [0024] for computer system, [0046]-[0050] for further explicit disclosure). The claim features are grouped together for compact prosecution because these features are shared between the claims with the only difference being whether the claim is directed to a computer-implemented method, system, or non-transitory computer readable medium.
Regarding claims 2 and 12,
The method of claim 1, wherein the methylation assay is a cell-free DNA targeted methylation assay (see [0230] where cfDNA Assays of Methylation is disclosed) and the biological sample is one of: a blood plasma sample or a blood serum sample (see [0117] and [0302] where plasma is collected to be used for the analytic pipeline; also disclosed throughout).
Regarding claims 3 and 13,
The method of claim 1, wherein the methylation assay is a whole-genome bisulfite sequencing (WGBS) assay (see [0033] and [0174] explicitly recited as whole-genome bisulfite sequencing) and wherein the biological sample is bone marrow tissue (see [0117] where biological sample is a solid tissue and the solid tissue includes a primary tumor, metastatic tumor, a polyp, or an adenoma; see also [0397] where bone cancer is inferred by the method). Accordingly, bone cancer analysis necessarily requires bone marrow samples. It is elementary that the mere recitation of a newly discovered function or property, inherently possessed by things in the prior art, does not cause a claim drawn to distinguish of the prior art. Under the principles of inherency, if a prior art device, in its normal and usual operation, would necessarily perform the method claimed, then the method claimed will be considered to be anticipated by the prior art device. Additionally, where the Patent Office has
reason to believe that a functional limitation asserted to be critical for establishing novelty in the
claimed subject matter may, in fact, be an inherent characteristic of the prior art, it possesses
the authority to require the applicant to prove that the subject matter shown to be in the prior art
does not possess the characteristic relied on (see MPEP § 2112).
Regarding claims 4 and 14,
The method of claim 1, wherein the feature selection process corresponds to a principal component analysis technique (see [0328]; features for a given analyte may be determined using PCA).
Regarding claims 5 and 15,
The method of claim 1, wherein the classifier is a principal component random forest classifier (see [0035] where it is explicitly recited that the classifying of the biological sample is performed by a classifier trained and constructed according to random forest classifiers).
Regarding claims 6 and 16,
The method of claim 1, further comprising assessing a performance of the classifier utilizing nested cross-validation (see [0563] where a cross-validation procedure is explicitly recited along with accompanying details).
Regarding claims 7 and 17,
The method of claim 6, wherein the nested cross-validation is further utilized to optimize hyperparameters in the training data (see [0563]-[0564] where the cross-validation procedure is described and minimizing generalization which is optimization).
Regarding claims 8 and 18,
The method of claim 1, wherein the training the classifier comprises configuring the classifier to generate a score that is associated with the survival outcome (see [0320] where the selection of features and creation of a feature vector for training the model can repeat until one or more desired criteria are satisfied such as a numerical value; additionally, a set of training samples is used for training various models for different purposes such as a classification of a prognosis which refers to a degree of improved overall survival).
Regarding claims 9 and 19,
The method of claim 1, wherein the survival outcome is a binarized survival outcome designation (see [0129] where the prognosis step as previously described having a threshold of whether the subject will survive such as one, two, three, four, or five years; according to the Applicant’s specification on [0082], the binarized output is a three year threshold).
Regarding claim 10,
The method of claim 1, wherein the training data further includes one or more clinical variables associated with the at least one patient (see Fig. 4 depicting an overview of a multi-analyte approach where the clinical variables are associated with the patient at the beginning of the pipeline).
Conclusion
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/P.N./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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