DETAILED ACTION
Applicant’s response, filed 07/17/2025, has been fully considered. Rejections and/or objections not reiterated from previous Office Actions are hereby withdrawn. 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 .
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.
Restriction Election
When an application includes a claim to a single subcombination, and that subcombination is required by plural claimed combinations that are properly restrictable, the subcombination claim is a linking claim and will be examined with the elected combination MPEP 806.05(c) III. The three inventions are directed to distinct combinations that require a common subcombination (claim 1), where newly submitted claims 151 and 156 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons: where claim 151 is for determining that a subject has a cancer condition based on the output of the ensemble model and claim 156 is another distinct step further comprising that the subject has a cancer condition and performing whole genome sequencing. Because claim 150 was previously presented, applicant has constructively elected that combination.
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits. Accordingly, claims 151-158 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
To preserve a right to petition, the reply to this action must distinctly and specifically point out supposed errors in the restriction requirement. Otherwise, the election shall be treated as a final election without traverse. Traversal must be timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are subsequently added, applicant must indicate which of the subsequently added claims are readable upon the elected invention.
Should applicant traverse on the ground that the inventions are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other invention.
Claim Status
Claims 1, 130-131, 133-138, 140-142, 147, and 149-158 are pending.
Claims 151-158 are withdrawn due to being not elected by previous presentation.
Claims 130-131, 133-138, 140-142, and 147 are withdrawn.
Claims 2-129, 132, 139, 143-146, and 148 are canceled.
Claims 151-158 are newly added.
Claims 1, 149, and 150 are under examination.
Claims 1, 149, and 150 are rejected.
Priority
Applicant’s claim under 35 USC § 120 for the benefit of prior-filed Application No. 17/352231 is acknowledged.
Applicant’s claim under 35 USC § 119(e) for the benefit of prior-filed Provisional Application No. 63/041692 is acknowledged.
The '692 provisional application does not provide adequate support for the claim element "a model trained to estimate circulating tumor fraction [based on] the at least two sets of nucleic acid sequence metrics", wherein the "two sets of nucleic acid sequence metrics" are two of "(i) a plurality of copy number metrics … (ii) a plurality of fragment length metrics … and (iii) a plurality of methylation metrics". The '692 application discloses a model that uses only one type of metric, not a combination of two or more types of metrics. Consequently, all claims are examined as though they had an effective filing date of 18 Jun 2021.
The '692 provisional application also does not provide adequate support for the claimed elements of a model that "deconvolves the proportion of non-cancerous and cancerous tissues …" as recited in claim 18.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 01/18/2023 is in compliance with the provisions of 37 CFR 1.97 and has therefore been considered. A signed copy of the IDS document is included with this Office Action.
Drawings
The Drawings submitted 07/07/2022 are accepted.
Claim Rejections - 35 USC § 101
The previous 101 rejection has been maintained.
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, 130-131, 133-138, 140-142, and 147 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more.
MPEP 2106 organizes judicial exception analysis into Steps 1, 2A (Prongs One and Two) and 2B as follows below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework Analysis as Pertains to the Instant Claims:
Step 1
With respect to Step 1: yes, the claims are directed to method, system, and a non-transitory computer-readable medium i.e., a process, machine, or manufacture within the above 101 categories [Step 1: YES; See MPEP § 2106.03].
Step 2A, Prong One
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations);
certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information) and mathematical concepts (in particular mathematical relationships and formulas) are as follows:
Independent claims 1, 130, and 131:
mapping each respective nucleic acid sequence, in the set of nucleic acid sequences, to a location in a reference construct for the genome of the species of the
determining, from the set of mapped nucleic acid sequences, a plurality of methylation metrics, a plurality of copy number metrics, and a plurality of fragment length metrics for the liquid biopsy sample, wherein (1) the plurality of methylation metrics comprises a plurality of bin-level methylation metrics, a plurality of fragment-level methylation metrics, and a plurality of CpG-level methylation metrics, wherein the plurality of methylation metrics are corrected for DNA methylation degradation prior to the whole genome methylation sequencing or incomplete identification of methylated residues during the whole genome methylation sequencing of the plurality of cell-free DNA fragments by a procedure comprising
determining, for each respective genomic region in a second plurality of genomic regions, wherein the methylation patterns of each respective genomic region in the second plurality of genomic regions is invariant in cancerous and non-cancerous tissues, a quantity of putative methylation sites, in the respective nucleic acid sequences that map to the corresponding genomic region in the second plurality of genomic regions, that are methylated
determining a divergence between (i) an expected quantity of putative methylation sites, in the respective nucleic acid sequences that map to the corresponding genomic region in the second plurality of genomic regions, that are methylated, and (ii) the determined quantity of putative methylation sites that are methylated, and correcting the plurality of methylation metrics based on the determined divergence and (2) the plurality of fragment length metrics comprises a plurality of bin-level fragment size metrics and a plurality of fragment-level fragment size metrics; and
applying an ensemble model to the plurality of methylation metrics, the plurality of copy number metrics, and the plurality of fragment length metrics, thereby estimating the circulating tumor fraction of the subject as output from the ensemble wherein the ensemble model consists of:
a first component model that generates a first circulating tumor fraction estimate based on the plurality of bin-level methylation metrics, wherein each respective bin-level methylation metric in the plurality of bin-level methylation metrics represents a corresponding genomic region comprising a corresponding plurality of putative methylation sites in a first plurality of genomic regions that are differentially methylated in a cancerous tissue relative to a non- cancerous tissue, and the respective bin-level methylation metric represents a comparison of at least: (a) the quantity of the corresponding putative methylation sites in the respective nucleic acid sequences in the set of nucleic acid sequences that map to the respective genomic region that are methylated and (b) the quantity of the corresponding putative methylation sites in the respective nucleic acid sequences in the set of nucleic acid sequences that map to the respective genomic region that are unmethylated.
a second component model that generates a second circulating tumor fraction estimate based on the plurality of fragment-level methylation metrics, wherein each respective fragment-level methylation metric in the plurality of fragment-level methylation metrics represents a respective nucleic acid sequence, in at least a subset of the set of mapped nucleic acid sequences, that map to a respective genomic region in a third plurality of genomic regions that is differentially methylated in a cancerous tissue relative to anon-cancerous tissue, and each respective fragment-level methylation metric in the plurality of fragment-level methylation metrics comprises a respective probability value that the DNA fragment corresponding to the respective nucleic acid sequence was from a cancerous cell based on fitting (a) the methylation pattern of the respective nucleic acid sequence and (b) the length of the DNA fragment corresponding to the nucleic acid sequence to one of a first DNA fragment distribution for DNA fragments originating from cancerous cells and a second DNA fragment distribution for DNA fragments originating from non-cancerous cells using a probabilistic model or an admixture model
a third component model that generates a third circulating tumor fraction estimate based on the plurality of CpG-level methylation metrics, wherein each respective CpG-level methylation metric in the plurality of CpG-level methylation metrics represents a corresponding CpG dinucleotide in a set of CpG dinucleotides in the genome of the species of the subject, and the respective CpG-level methylation metric is determined based on a corresponding fraction of the occurrences of the respective CpG dinucleotide, in the set of mapped nucleic acid sequences, that are methylated
a fourth component model that generates a fourth circulating tumor fraction estimate based on the plurality of bin-level fragment size metrics, wherein, each respective bin-level fragment size metric in the plurality of bin-level fragment size metrics represents a corresponding genomic region in a fourth plurality of genomic regions, and each respective bin- level fragment size metric in the plurality of bin-level fragment size metrics is determined based on a comparison of (a) the abundance of nucleic acid sequences, in the set of mapped nucleic acid sequences that map to the corresponding genomic region, having a length that satisfies a minimal length threshold, to (b) the abundance of nucleic acid sequences, in the set of mapped nucleic acid sequences that map to the corresponding genomic region, having a length that does not satisfy the minimal length threshold
a fifth component model generates a fifth circulating tumor fraction estimate based on the plurality of fragment-level fragment size metrics, wherein each respective fragment-level fragment size metric in the plurality of fragment-level fragment size metrics represents a respective nucleic acid sequence, in at least a subset of the set of mapped nucleic acid sequences, each respective fragment-level fragment size metric in the plurality of fragment-level fragment
a sixth component model that generates a sixth circulating tumor fraction estimate based on the plurality of copy number metrics size metrics is based on the length of the DNA fragment corresponding to the respective nucleic acid sequence
the ensemble model combines the first circulating tumor fraction estimate, the second circulating tumor fraction estimate, the third circulating tumor fraction estimate, the fourth circulating tumor fraction estimate, the fifth circulating tumor fraction estimate, and the sixth circulating tumor fraction estimate
Independent claim 149:
mapping each respective nucleic acid sequence, in the set of nucleic acid sequences, to a location in a reference construct for the genome of the species of the
determining, from the set of mapped nucleic acid sequences, a plurality of methylation metrics, a plurality of copy number metrics, and a plurality of fragment length metrics for the liquid biopsy sample, wherein (1) the plurality of methylation metrics comprises a plurality of bin-level methylation metrics, a plurality of fragment-level methylation metrics, and a plurality of CpG-level methylation metrics (2) the plurality of fragment length metrics comprises a plurality of bin-level fragment size metrics and a plurality of fragment-level fragment size metrics; and
applying an ensemble model to the plurality of methylation metrics, the plurality of copy number metrics, and the plurality of fragment length metrics, thereby estimating the circulating tumor fraction of the subject as output from the ensemble wherein the ensemble model consists of:
a first component model that generates a first circulating tumor fraction estimate based on the plurality of bin-level methylation metrics, wherein each respective bin-level methylation metric in the plurality of bin-level methylation metrics represents a corresponding genomic region comprising a corresponding plurality of putative methylation sites in a first plurality of genomic regions that are differentially methylated in a cancerous tissue relative to a non- cancerous tissue, and the respective bin-level methylation metric represents a comparison of at least: (a) the quantity of the corresponding putative methylation sites in the respective nucleic acid sequences in the set of nucleic acid sequences that map to the respective genomic region that are methylated and (b) the quantity of the corresponding putative methylation sites in the respective nucleic acid sequences in the set of nucleic acid sequences that map to the respective genomic region that are unmethylated.
a second component model that generates a second circulating tumor fraction estimate based on the plurality of fragment-level methylation metrics, wherein each respective fragment-level methylation metric in the plurality of fragment-level methylation metrics represents a respective nucleic acid sequence, in at least a subset of the set of mapped nucleic acid sequences, that map to a respective genomic region in a third plurality of genomic regions that is differentially methylated in a cancerous tissue relative to anon-cancerous tissue, and each respective fragment-level methylation metric in the plurality of fragment-level methylation metrics comprises a respective probability value that the DNA fragment corresponding to the respective nucleic acid sequence was from a cancerous cell based on fitting (a) the methylation pattern of the respective nucleic acid sequence and (b) the length of the DNA fragment corresponding to the nucleic acid sequence to one of a first DNA fragment distribution for DNA fragments originating from cancerous cells and a second DNA fragment distribution for DNA fragments originating from non-cancerous cells using a probabilistic model or an admixture model
a third component model that generates a third circulating tumor fraction estimate based on the plurality of CpG-level methylation metrics, wherein each respective CpG-level methylation metric in the plurality of CpG-level methylation metrics represents a corresponding CpG dinucleotide in a set of CpG dinucleotides in the genome of the species of the subject, and the respective CpG-level methylation metric is determined based on a corresponding fraction of the occurrences of the respective CpG dinucleotide, in the set of mapped nucleic acid sequences, that are methylated
a fourth component model that generates a fourth circulating tumor fraction estimate based on the plurality of bin-level fragment size metrics, wherein, each respective bin-level fragment size metric in the plurality of bin-level fragment size metrics represents a corresponding genomic region in a fourth plurality of genomic regions, and each respective bin- level fragment size metric in the plurality of bin-level fragment size metrics is determined based on a comparison of (a) the abundance of nucleic acid sequences, in the set of mapped nucleic acid sequences that map to the corresponding genomic region, having a length that satisfies a minimal length threshold, to (b) the abundance of nucleic acid sequences, in the set of mapped nucleic acid sequences that map to the corresponding genomic region, having a length that does not satisfy the minimal length threshold
a fifth component model generates a fifth circulating tumor fraction estimate based on the plurality of fragment-level fragment size metrics, wherein each respective fragment-level fragment size metric in the plurality of fragment-level fragment size metrics represents a respective nucleic acid sequence, in at least a subset of the set of mapped nucleic acid sequences, each respective fragment-level fragment size metric in the plurality of fragment-level fragment
a sixth component model that generates a sixth circulating tumor fraction estimate based on the plurality of copy number metrics size metrics is based on the length of the DNA fragment corresponding to the respective nucleic acid sequence
the ensemble model combines the first circulating tumor fraction estimate, the second circulating tumor fraction estimate, the third circulating tumor fraction estimate, the fourth circulating tumor fraction estimate, the fifth circulating tumor fraction estimate, and the sixth circulating tumor fraction estimate
Dependent claims 133-138, 140-141, and 147 recite further steps that limit the judicial exceptions in independent claims 1 and 137 and, as such, also are directed to those abstract ideas. For example, claims 133-134 further limits the nucleic acid of claim 1, claims 135-138 further limits the whole genome sequencing of claim 1, claims 140-142 further limit the set of nucleic acid sequences of claim 137, and claim 147 further limits the sample of claim 1;
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined to each cover performance either in the mind and/or by mathematical operation because the method only requires a user to manually map and determine. Without further detail as to the methodology involved in “mapping each respective nucleic acid sequence”, “determining, from the set of mapped nucleic acid sequences”, “determining, for each respective genomic region”, “determining a divergence”, under the BRI, one may simply, for example, use pen and paper to estimate a circulating tumor fraction. Some of these steps and those recited in the dependent claims require mathematical techniques, such as: “applying an ensemble model”, “generates a first circulating tumor fraction estimate”, “generates a second circulating tumor fraction estimate”, “generates a third circulating tumor fraction estimate”, “generates a fifth circulating tumor fraction estimate”, “generates a first circulating tumor fraction estimate”, “generates a sixth circulating tumor fraction estimate”, “combines the first circulating tumor fraction estimate, the second circulating tumor fraction estimate, the third circulating tumor fraction estimate, the fourth circulating tumor fraction estimate, the fifth circulating tumor fraction estimate, and the sixth circulating tumor fraction estimate” as described in the published specification [0151].
Therefore, claims 1, 130, and 131 and those claims dependent therefrom recite an abstract idea [Step 2A, Prong 1: YES; See MPEP § 2106.04].
Step 2A, Prong Two
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 judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d).III).
Additional elements, Step 2A, Prong Two
With respect to the instant recitations, the claims recite the following additional elements:
Independent claims 1, 130, 131, and 149:
A liquid biopsy
obtaining, in electronic form, a set of nucleic acid sequences from a whole genome methylation sequencing of a plurality of cell-free DNA fragments from a liquid biopsy sample obtained from the test subject, wherein each respective nucleic acid sequence in the set of nucleic acid sequences comprises a methylation pattern for a corresponding cell-free DNA fragment in the plurality of cell-free DNA fragments, and wherein the set of nucleic acid sequences represents at least 100 MB of the genome of the test subject
Dependent claim 150:
providing to the test subject a personalized cancer treatment based on the circulating tumor fraction estimated by the ensemble model.
The claims also include non-abstract computing elements. For example, independent claim 130 includes a computing system and claim 131 includes a non-transitory computer-readable medium.
Considerations under Step 2A, Prong Two
With respect to Step 2A, Prong Two, the additional elements of the claims do not integrate the judicial exceptions into a practical application for the following reasons. Those steps directed to data gathering, such as “obtaining”, and to data outputting, such as “providing”, perform functions of collecting the data needed to carry out the judicial exceptions. Data gathering and outputting do not impose any meaningful limitation on the judicial exceptions, or on how the judicial exceptions are performed. Data gathering and outputting steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)).
Further steps directed to additional non-abstract elements of “a computing system and a non-transitory computer-readable medium” do not describe any specific computational steps by which the “computer parts” perform or carry out the judicial exceptions, nor do they provide any details of how specific structures of the computer, such as the computer-readable recording media, are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, and therefore the claim does not integrate that judicial exceptions into a practical application. The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc.… are recited so generically (i.e., no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer, and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer (MPEP 2106.05(f)).
In regards to the limitations reciting a liquid biopsy, it is found to be insignificant extra-solution activity as performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989).
Thus, none of the claims recite additional elements which would integrate a judicial exception into a practical application, and the claims are directed to one or more judicial exceptions [Step 2A, Prong 2: NO; See MPEP § 2106.04(d)].
Step 2B (MPEP 2106.05.A i-vi)
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the instant claims, the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), 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), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(II)(i)).
As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
With respect to claims 130 and 131 and those claims dependent therefrom, the computer-related elements or the general purpose computer do not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (see MPEP 2106.06(A)). The specification also notes that computer processors and systems, as example, are commercially available or widely used at [0117 and 0121-0123]. The additional elements are set forth at such a high level of generality that they can be met by a general purpose computer. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than the judicial exceptions (see MPEP 2106.05(b)I-III).
With respect to claims 1, 130, 131, and 149, the limitations of a liquid biopsy sample is well-understood, routine, and conventional in the art. The specification discloses methods for calculating tumor mutation burden in liquid biopsy samples and/or solid tissue samples are known in the art [0354].
Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself [Step 2B: NO; See MPEP § 2106.05].
Therefore, the instant claims are not drawn to eligible subject matter as they are directed to one or more judicial exceptions without significantly more. For additional guidance, applicant is directed generally to the MPEP § 2106.
Response to Applicant Arguments
Applicant submits that Claim 1 recites novel data structures that are used in making the circulating tumor fraction such as the fragment-level methylation metrics used in the second component model [p. 18, par. 3] and is an improvement in the functioning of a computer [p. 19, par. 2].
It is respectively found not persuasive. The claims are not analogous to the data structure of the Enfish as one is a type of data that is provided to the computer and one is a structure to put that data into, therefore it can not be considered improvement in the functioning of a computer.
Applicant submits claim 1 is distinguishable over the holding in re Board of Trustees of the Leland Stanford Junior Univ., No. 2020-1288 (Fed. Cir. Mar. 25, 2021), which affirmed the Patent Trial and Appeal Board's rejection of the patentability of claims directed to computerized methods to generate genetic data [p. 20, par. 3].
It is respectively found not persuasive. The claims are not analogous to the data structure of the Enfish as one is a type of data that is provided to the computer and one is a structure to put that data into, therefore it cannot be considered improvement in the functioning of a computer.
Claim Rejections - 35 USC § 103
The previous 103 rejection is maintained.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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.
A. Claim(s) 1, 130-131, 135-138, 140-142, 147, and 149-150 is/are rejected under 35 U.S.C. 103 as being unpatentable over Guo et al (Identification of Methylation Haplotype Blocks Aids in Deconvolution of Heterogeneous Tissue Samples and Tumor Tissue-of-Origin Mapping from Plasma DNA," Nature Genetics 2017, cited on IDS dated 07/07/2022) in view of Adalsteinsson et al (Adalsteinsson, Viktor A et al. “Scalable Whole-Exome Sequencing of Cell-Free DNA Reveals High Concordance with Metastatic Tumors.” Nature communications 8.1 (2017), cited on IDS dated 07/07/2022), in further view of Yang et al. (Yang, P. et al., "A Review of Ensemble Methods in Bioinformatics," Current Bioinformatics 2010, cited on IDS dated 07/07/2022), further in view of Krueger et al. (Bioinformatics 2011), further in view of Li et al. (Nucleic Acids Research 2018; ref. A254 on IDS of 7 Jul 2022), and further in view of Lo et al. (US 2013/0237431; ref. A3 on IDS of 7 Jul 2022).
Guo discloses obtaining whole-genome bisulfite sequencing data and reduced-representation bisulfite sequencing data [p. 643, col. 1, par. 2]. Guo further discloses identified a total of 771 million methylation haplotype informative reads [p. 636, col. 1, par. 1]. Guo also discloses reads were mapped to the reference human genome, which comprises more than 1 Mb [p. 643, col. 1, par. 3]. Guo further discloses a minimum 10× depth of coverage in our WGBS data set) and repeated 1,000,000 times [p. 643, col. 2, par. 1].
Guo discloses the human genome was split into non-overlapping 'sequence able and mappable' segments …then partitioning each segment into methylation haplotype blocks (MHBs)” [p. 643, col. 1, par. 4]. Guo further discloses defining a methylated haplotype load (MHL) for each candidate region [p. 643, col. 1, par. 4]. Guo also discloses by focusing on the MHBs with a low MHL in the blood, they identified cancer-associated highly methylated haplotypes (caHMHs) and such haplotypes were present in only the tumor tissues and the matched plasma from the same patient, but not in whole blood or any other non-cancer samples [p. 638, col. 1, par. 3]. Guo discloses deconvoluting the reads into cancer/normal classes to estimate the tumor fraction in the sample [p. 644, col. 1, par. 2].
Guo is silent on "a plurality of copy number metrics". Consequently, the model of Guo uses only bin-level methylation metrics, not a combination of methylation and copy number metrics.
However, Adalsteinsson discloses
A) obtaining a cfDNA sample from a patient [p. 7, col. 2, par. 3], then obtaining whole-genome sequencing data from the sample [p. 7, col. 2, par. 3]
B) reads are aligned to the genome [p. 7, col. 2, par. 5]
C) predicting a copy number for a specific genome bin [p. 8, col. 1, par. 5]
D) using a probabilistic model to estimate the tumor fraction using the copy number predictions [p. 8, col. 1, par. 5].
Adalsteinsson also discloses merged ×0.1 mixtures for 44 breast/prostate cfDNA (CT) ULP-WGS samples with ≥0.05× coverage (1.5 million reads) [p. 9, col. 1, par. 5]. Adalsteinsson further discloses that cfDNA can be used for immunotherapy including influencing treatment strategies [p. 6, col. 1, par. 3].
Adalsteinsson is silent on "a plurality of methylation metrics". Consequently, the model of Adalsteinsson uses only copy number metrics, not a combination of methylation and copy number metrics.
However, Yang discloses that "ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuracy" [p.1, par. 2]. Yang further discloses that one way of combining classifiers is Bayesian combination [p. 3, par. 5-6]. Yang concludes that "a carefully engineered ensemble algorithm generally offer higher accuracy and stability than a single algorithm can achieve" [p. 12, par. 9]. Yang discloses that each classifier within the ensemble operates in a different hypothesis space [p. 2, par. 3] in Guo and Adalsteinsson, the hypothesis space is a range of tumor fractions within the cfDNA sample
Combining the classifiers of Guo and Adalsteinsson into an ensemble, as taught by Yang, results in a model (the ensemble classifier) that uses both bin-level methylation metrics and copy number metrics, to estimate the tumor fraction in a cfDNA sample.
An invention would have been obvious to one of ordinary skill in the art if some motivation in the prior art would have led that person to combine prior art reference discloseings to arrive at the claimed invention. Prior to the time of invention, said practitioner would have been motivated to combine the model of Guo and the model of Adalsteinsson into an ensemble model, because Yang discloses that ensemble models typically perform much better than single models. Given that both models use cfDNA data and a probabilistic model to estimate tumor fractions, and given that Yang discloses that ensembles can be created from any kind of classifier, said practitioner would have readily predicted that the combination would successfully result in a method of estimating tumor fraction in a cfDNA sample based on both methylation and copy number metrics. The invention is therefore prima facie obvious.
The combination of Guo, Adalsteinsson and Yang discloses a method of estimating tumor fraction in a cfDNA sample using bin-level methylation data, copy number data, and an ensemble model. But none of these disclose using segment-level methylation data in the model.
However, Li discloses
A) obtaining a cfDNA sample from a subject, and then obtaining whole-genome methylation sequencing data from the sample [p. 2, col. 2, par. 2].
B) identifying reads "that fall into the genomic regions of selected markers" [p. 2, col. 2, par. 2] , which necessitates that the reads be mapped to genomic regions
C) characterizing methylation patterns for each read [p. 4, col. 1, par.1].
D) "we develop a probabilistic framework to infer the tumor-derived cfDNA fraction" based on the methylation patterns of each read [p. 4, col. 2, par. 1].
Li discloses that the class-membership probability of the read is a function of the methylation state of each methylation site in the read, and the number of methylation sites in the read, which constitutes "the length of the DNA fragment" [p. 4, col. 1, par. 2]. Li discloses that the class-membership probability of the read is calculated using a probabilistic model and methylation patterns for normal and tumor tissue [p. 4, col. 1, par. 2].
Yang provides a motivation to combine the tumor fraction calculation model of Li with the models of Guo and Adalsteinsson into an ensemble model that estimates tumor fraction from a combination of bin-level methylation metrics, segment-level methylation metrics, and copy number metrics.
An invention would have been obvious to one of ordinary skill in the art if some motivation in the prior art would have led that person to combine prior art reference discloseings to arrive at the claimed invention. Prior to the time of invention, said practitioner would have been motivated to add a tumor fraction prediction based on fragment-level methylation metrics, as taught by Li, to the ensemble model of Guo, Adalsteinsson and Yang, because Li discloses that fragment-level methylation analysis is useful for predicting tumor fraction, and Yang discloses those additional heterogeneous predictors increase the accuracy of an ensemble predictor. Given that Guo, Adalsteinsson and Li all disclose predicting tumor fraction from characteristics of cfDNA samples, and that Yang discloses that ensembles can be created from any kind of classifier, said practitioner would have readily predicted that the combination would successfully result in a method of estimating tumor fraction in a cfDNA sample based on bin-level methylation, copy number, and fragment-level methylation metrics. The invention is therefore prima facie obvious.
The combination of Guo, Adalsteinsson and Yang discloses an ensemble model for estimating tumor fraction from bin-level methylation data, fragment-level methylation data, and copy-number data, but does not disclose estimating tumor fraction from "fragment-level fragment size metrics".
Lo discloses estimating tumor fraction from fragment size metrics, including a distribution of lengths of fragments from normal tissue, and a separate distribution of lengths of fragments from tumor tissue (e.g. Fig. 15A). As explained above, Yang provides a motivation to combine the tumor fraction estimation model of Lo with the models of Guo, Adalsteinsson and Li into an ensemble model that estimates tumor fraction from a combination of methylation metrics, copy number metrics and fragment size metrics.
An invention would have been obvious to one of ordinary skill in the art if some motivation in the prior art would have led that person to combine prior art reference discloseings to arrive at the claimed invention. Prior to the time of invention, said practitioner would have been motivated to add a tumor fraction prediction based on fragment length to the ensemble model of Guo, Adalsteinsson and Yang, because Lo discloses that the distributions of fragment lengths vary between normal and tumor tissues, and Yang discloses those additional heterogeneous predictors increase the accuracy of an ensemble predictor. Given that Guo, Adalsteinsson and Lo all disclose predicting tumor fraction from characteristics of cfDNA samples, and that Yang discloses that ensembles can be created from any kind of classifier, said practitioner would have readily predicted that the combination would successfully result in a method of estimating tumor fraction in a cfDNA sample based on methylation, copy number, and fragment size metrics. The invention is therefore prima facie obvious.
Response to Applicant Arguments
Applicant submits the cited references, either individually or in combination, fail to disclose or suggest several limitations of the claimed method [p. 22, par. 2].
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Applicant submits examiner's rationale relies on impermissible hindsight reconstruction [p. 28, par. 6].
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
Conclusion
No claims are allowed.
THIS ACTION IS MADE FINAL. 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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/D.M.B./Examiner, Art Unit 1685 /Soren Harward/Primary Examiner, TC 1600