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 .
Status of Claims
Applicant’s amendment filed 8/15/2025 is acknowledged. Claims 1, 5-14, 21, 32, and 38 have been amended. Claims 36 and 37 have been cancelled. Claims 1-14, 20-27, 31-35, and 38 are pending in the instant application and the subject of this non-final office action.
All of the amendments and arguments have been reviewed and considered. Any rejections or objections not reiterated herein have been withdrawn in light of amendments to the claims or as discussed in this office action.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Previous Rejection
Status of Prior Rejections/Objections:
The duplicate advisory and rejections of claims 36 and 37 are withdrawn in view of the cancellation of the claims.
The 101 rejection of claims 1-14, 20-27, 31-35, and 38 has been modified for clarity.
The 112(b) rejections of claims 1 and 38 and dependents thereof are withdrawn in view of the amendments to the claims.
The prior art rejection(s) under 35 USC 102 directed to claim(s) 1, 2, 4-11, 22, 24-27, and 31-35 as being anticipated by Olsen is/are maintained and modified as necessitated by claim amendments.
The prior art rejection(s) under 35 USC 103 directed to the following claims as being unpatentable over the following are maintained and modified:
Claim 3 under Olsen in view of Bibikova
Claim 12 under Olsen in view of Loomba
Claim 13 under Olsen in view of Ma
Claim 23 under Olsen in view of Hernandez
New Ground(s) of Rejections
Claim Interpretation
In evaluating the patentability of the claims presented in this application, claim terms have been given their broadest reasonable interpretation (BRI) consistent with the specification, as understood by one of ordinary skill in the art, as outlined in MPEP 2111.
Regarding claims 1, 5, 7, 14 and 32-35, 38, the specification recites the following limits for NAFLD, NASH and cirrhosis in para [0003]: “NAFLD often progresses to nonalcoholic steatohepatitis (NASH), which can progress to cirrhosis, and eventually progress to liver cancer”. However, in the art, NAFLD is most commonly used as an umbrella term: “The broader term of nonalcoholic fatty liver disease (NAFLD) started to be used in 2002, and encompassed the full spectrum of fatty liver disease from isolated hepatic steatosis or NAFL to NASH and NASH cirrhosis” (Cotter TG, Rinella M. Nonalcoholic Fatty Liver Disease 2020: The State of the Disease. Gastroenterology. 2020 May;158(7):1851-1864: pg. 1851, para 2). It is therefore interpreted that NALFD, as used in the instant application, encompasses “NAFL” and any other NAFLD-spectrum condition(s) with lower severity than NASH and cirrhosis, but excludes NASH and cirrhosis. Likewise, as these conditions/diseases exist on a spectrum, it is likewise interpreted that by determining a particular “severity”, a model would inherently be placing a patient/sample into a given “bin” or “class” for a particular disease state (e.g., NAFL or NASH).
Claim Rejections - 35 USC § 112(a)
Claims 1-14, 20-27, 31-35, and 38 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claims 1-14, 20-27, 31-35, and 38, claim 1 recites “(c) identifying a methylation pattern … based on the set of CpG … statuses, wherein the methylation pattern distinguishes between … states compris[ing] a … NAFLD … positive state, a … NASH … positive state, and a cirrhosis positive state; (d) assigning to the DNA sample the NAFLD positive state, the NASH positive state, or the cirrhosis positive state based on the methylation pattern identified in (c)”.
The instant disclosure teaches pairwise methylation patterns for distinguishing between (i) instant “NALFD” and cirrhosis (Fig. 6); (ii) NASH and cirrhosis (Fig. 7); and (iii) instant “NAFLD” and NASH (Fig. 8). See also pg. 14, 7.2 Pairwise discrimination between disease state in primary liver tissues and pg. 19, 7.3 Pairwise discrimination between liver disease states in cfDNA samples (emphasis added).
No species in the genus of a classifier is capable of distinguishing three or more states using a methylation pattern.
For this reason, the described species of pairwise classifiers are not sufficient to represent the claimed species of the identification of a particular methylation pattern and assignment of a liver disease state based on the methylation pattern capable of distinguishing between three or more states.
Further, claims 8 and 9 recite classifying a stage of fibrosis; claim 10 recites classifying types of hepatitis; and claim 11 recites classifying levels of inflammation in the DNA sample. The disclosure fails to provide evidence of any representative species of models/classifiers capable of classifying the DNA sample of having a probability of each or any of these states.
For these reasons, the described species of pairwise classifiers for NAFLD, NASH, and cirrhosis are not sufficient to represent the claimed species of the identification of a particular methylation pattern and assignment of a non-cancer liver disease state, comprising at least the three claimed diseases states. The described species of pairwise classification are further not sufficient describe further classifying the DNA sample as having a probability of the various fibrosis, hepatitis, or inflammation states. Thus, claims 1-14, 20-27, 31-35, and 38 lack written description support sufficient to convey to a skilled artisan that the Applicant had possession of the full breadth of the claimed invention at the time of filing.
Claim Rejections - 35 USC § 101
Claims 1-14, 20-27, 31-35, and 38 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exceptions without significantly more. The claim(s) recite(s) abstract ideas. This judicial exception is not integrated into a practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The following three inquiries are used to determine whether a claim is drawn to patent-eligible subject matter:
Step 1. Is the claim directed to a process, machine, manufacture, or composition of matter?
Yes, the claims are directed to a process/method.
Step 2A, prong 1. Does the claim recite a law of nature, a natural phenomenon, or an abstract idea (recognized judicial exceptions)?
The claims are directed to classifying a liver disease of a subject based on a methylation pattern comprising assigning a liver disease state to the subject based on the methylation pattern, as recited in claim 1. Assigning encompassed the abstract idea of a mental process (i.e., evaluation of data or information to reach a conclusion or make a judgement). Identifying further encompasses the abstract idea of a mathematical calculation, which may encompass a mental process. Determining a plurality of CpG methylation statuses may further encompass mental processes (i.e., looking up the statuses in a table).
Additionally, the assertion of assigning a liver disease state classification based on a methylation pattern also recites a natural phenomenon of the correlation between a liver disease and methylation statuses of a set of CpG sites of target sequence.
Step 2A, prong 2. Is the judicial exception(s) integrated into a practical application?
Regarding claim 1, the claim recites in (a) and (c)(i) “obtaining … DNA sample(s)”. Such represents necessary data gathering and selecting a particular data source to be manipulated in the judicial exceptions and thus does not amount to a practical application. See MPEP 2106.04(d) and 2106.05(g).
Further, step (e) recites administering … a therapy selected to treat the NAFLD positive state, the NASH positive state, or the cirrhosis positive state. Although this limitation indicates that a treatment is to be administered, it does not provide any information as to how the patient is to be treated or what the treatment is, but instead covers any possible treatment that a medical professional decides to administer to the patient. As such, there are no meaningful constraints on the administering step such that the particular treatment or prophylaxis consideration would apply because it is not limited to any particular manner or type of treatment. See MPEP 2106.04(d)(2).
Moreover, the claim merely provides the identification made in limitations above to the relevant audience (such as a physician or another medical professional) and at most adds a suggestion to take that identification into account when treating patients. See Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 78 (2012). The treatment limitation may thus be understood as no more than an attempt to generally link the judicial exception to a field of use. See MPEP 2106.05(h). Therefore, the treatment limitation fails to require a particular application of the abstract idea and therefore amounts only to a generic instruction to “apply” the exception or to a mere indication of the field of use or technological environment in which the abstract idea is performed. See also Example 49 of the July 2024 Subject Matter Eligibility Examples (https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf). Thus, it does not amount to a practical application.
It is further noted that, broadly interpreted, step (e) does not specifically tie the therapy to the positive state assigned in step (d), though this alone would not rectify the genericness of the “selected” treatment.
Regarding claims 2-4, the claims recite that the DNA sample comprises fragments of a particular origin (claim 2), that the method comprises shearing/digestion to obtain smaller fragments (claim 3), and enriching fragments via probes or with a panel of PCR primers (claim 4). Such amounts to a selection of particular data source and/or mere data gathering. See MPEP 2106.04(d) and 2106.05(g).
Shearing/digestion and enrichment via probes/amplification are routine within the art: Krygier (Krygier M, et al. A simple modification to improve the accuracy of methylation-sensitive restriction enzyme quantitative polymerase chain reaction. Anal Biochem. 2016 May 1;500:88-90) teaches the popularity of digestion-based MSRE-qPCR (pg. 99, col 2, para 1) and Heiss (Heiss JA, et al. Battle of epigenetic proportions: comparing Illumina's EPIC methylation microarrays and TruSeq targeted bisulfite sequencing. Epigenetics. 2020 Jan-Feb;15(1-2):174-182) teaches targeted enrichment using baits in TruSeq Mehtyl Capture (pg. 175, col 2, para 1; see also pt. 174, col 1, para 1, spanning col 2). Thus, the claims are not integrated into a practical application.
Regarding claims 5-14, 31-35, 38, the claims recite calculations/classifications or qualities thereof and thus encompasses further abstract ideas. Thus, the claims do not amount to a practical application.
Regarding claims 20-21, the claims recite that the CpG sites of the DNA sample are enriched and a particular origin of DNA sample(s)—amounting to a selection of a particular data source to be manipulated—and selecting a set of CpG sites based on particular calculations, which encompasses further abstract ideas. Thus, the claims do not amount to a practical application.
Regarding claims 22-27, the claims recite well known methods for determining CpG sites: methylation-aware sequencing (claims 22 and 26); methylation-aware arrays and PCR (claims 23 and 27); bisulfite treatment or enzyme-based deamination (claim 24) and a DNA array with enrichment (claim 25). Such amounts to a selection of particular data source and/or mere data gathering. See MPEP 2106.04(d) and 2106.05(g).
See Heiss, which teaches methylation-aware bisulfite sequencing (pg. 175, Bisulfite Sequencing, spanning pg. 176; see also pg. 174, para 1) and methylation-aware arrays using amplification enrichment (pg. 176, Microarray data; see also pg. 174, para 1). Thus, the claims are not integrated into a practical application.
Step 2B. Does the claim amount to significantly more?
No, the data collecting/sample selection and generic treatment limitations of the claims are broadly recited and well known within the art. Step (c) of claim 1 amounts to merely training a model based on data comprising feature selection. See, e.g., Olsen (WO 2020/150258: para [0129]-[0151], especially [0129] and [0151]). Even if the classes (states) and data were found to be novel, selecting novel data (i.e., mere data gathering) and applying an abstract method is not sufficient to amount to significantly more under 101 and novelty is not the standard for determining subject matter eligibility. See Ariosa Diagnostics, Inc. v. Sequenom, 788 F.3d 1371, 1373, 115 USPQ2d 1152, 1153 (Fed. Cir. 2015).
MPEP 2106.05(I) discusses the search for the inventive concept, which must be furnished beyond the judicial exceptions(s). In the instant case, the claims encompass abstract ideas, mere data gathering, and a treatment step that amounts to mere instruction to “apply” the judicial exception give its breadth. See MPEP 2106.04(d)(2)(a). The Courts have found that such limitations directed to data gathering and generic treatments have not been enough to qualify as “significantly more” than the judicial exception. See MPEP 2106.05(I)(A).
Further, such disease classes are well known within the art (see Cotter, cited in Interpretation) and, thus, this also does not amount to significantly more.
No additional claim recites limitations sufficient to be “significantly more”.
Claim Rejections - 35 USC § 102
Claim(s) 1-2, 4-11, 14, 20, 22, 24-27, 31-32, and 38 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Olsen (WO 2020 150258 A1; cited on the IDS dated 03/13/2024, published 07/23/2020).
Olsen teaches a method of classifying a liver disease of a subject (entire document, e.g., Fig. 1) comprising:
(a)-(b) obtaining a set of CpG methylation status at a set of CpG sites of target sequences from a cfDNA sample (para [0017-18]; [0099]; [0194]; [0204]: “A cell-free biological sample is obtained…from a subject…processed and assayed for nucleic acid molecules (e.g., nucleic acid molecules derived from the cell-free biological sample)”; [0201]: “Methylation values are calculated for 10,508 analyzed CpGs”; Fig. 1)
identifying a methylation pattern based on the set of CpG methylation statuses, wherein the methylation pattern distinguishes between NAFL [instant “NALFD”], NASH, and cirrhosis (para [0194]: “Group A (…NAFL/Fibrosis F0-1), Group B (NASH/F0-1), and Group C (NASH/F3-4)”; [0193]: “a panel of cfDNA methylation markers that predict the presence of…NASH is identified”; para [0178]: “based at least in part on a data set obtained using the methods…identifying the presence or absence of cirrhosis”; [0093]: “identifying liver disease by processing biological samples…subjects may include patients with NAFLD who are at increased risk of having SH and/or fibrosis” [i.e., those with NAFL]; [0202]; Table 3; [0154])
assigning a liver disease state to the subject based on the methylation pattern, wherein the liver disease state comprises one of: NAFL [instant “NALFD”], NASH, and cirrhosis (Fig. 1; para [0040]; “the presence or the severity of the liver disease is identified according to a Non-Alcoholic Fatty Liver Disease Activity Score [NAS] composite comprising steatosis, lobular inflammation, and hepatocellular ballooning”; [0154]: “an NAS value of >5 including both steatosis and hepatocyte ballooning is considered indicative of NASH”; [0178]: “identifying the presence or absence of cirrhosis”; [0072]; [0197]; claim 10)
administering a therapeutic intervention to treat the severity of the disease of the subject upon identifying the subject as having the disease/a given severity thereof (para [0164])
In the identifying a severity of a disease, Olsen teaches that the methods comprise a machine learning algorithm trained on one or more features (para [0118]), wherein markers and genomic regions are identified from subjects having a liver disease and/or a particular severity compared to subjects not having a liver disease and/or having a different severity (para [0120]). Olsen teaches that values associated with said nucleic acids are analyzed using feature selection using filter techniques to assess the relevance of features and search for an optimal set (para [0122]), wherein selected features are classified using a classifier algorithm (para [0123]). Olsen teaches classifiers capable of outputting more than two values in the classification, wherein such may be the clinical identification of the liver disease of the subject (para [0125]).
Regarding claim 2, Olsen teaches that a sample may include cfDNA fragments (e.g.: para 0079).
Regarding claim 4, Olsen teaches enrichment of target regions using hybridization to capture probes (e.g.: para 0201).
Regarding claims 5-7, Olsen teaches analyzing methylation levels and patterns (e.g.: para [0153]; para [0204]) and providing a value of the probability of having a liver disease of a particular severity (e.g.: para [0128]), and teaches the use of cutoff values in classifying a sample (e.g.: para [0127]).
As above, Olsen teaches that the subject may be at risk of [i.e., not have] NASH but have NALFD, i.e., have NAFL [instant “NAFLD”], thus teaching that methylation pattern distinguishes between instant “NALFD” and NASH in a training subset of data. It is likewise noted that Olsen provides a NAS score threshold for distinguishing NASH and lower severity NAFLD, i.e., NALF. Therefore, it follows that the severity of liver disease probability and cut-offs would be provided for each of said liver disease severity states.
Regarding claims 8 and 9, Olsen teaches that subject classification can include a measure of the level or stage of fibrosis including no fibrosis (e.g.: para [0154]; Table 2; para [0194]). As in the rejection of claim 5 above, Olsen teaches assigning a probability to a severity of a liver disease, wherein Olsen also teaches cirrhosis.
Regarding claims 10 and 11, Olsen includes aspects of determining the absence of liver inflammation (e.g.: para [0009] and [0155]), where absence of inflammation of the liver is no hepatitis (instant claim 10) and no inflammation (instant claim 11). As in the rejection of claim 5 above, Olsen teaches assigning a probability to a severity of a liver disease, wherein Olsen also teaches NASH (instant claim 10).
Regarding claim 14, Olsen teaches providing a value of the probability of having a liver disease of a particular severity (e.g.: para [0128]), and teaches providing a report of results (e.g.: para [0094]).
As discussed above in claim 5, the severities correspond to NAFLD, NASH, and cirrhosis positive states.
Regarding claim 20, in the method of Olsen, Olsen teaches enrichment of target regions using hybridization to capture probes (e.g.: para [0201]) on training samples including plasma samples (para [0200]), wherein the cfDNA was analyzed (para [0197]). Olsen teaches feature selection using weights of logistic regression and ANOVA [i.e., analysis of variance, which utilizes a “cut-off requirement” determined by a significance and degrees of freedom].
Regarding claims 22, 24 and 26, Olsen teaches bisulfite sequencing which provides a detection of 5mC or 5hmC (e.g.: para [0101]; [0098]).
Regarding claim 25, Olsen teaches using arrays of probes from a targeted panel to enrich particular sequences (e.g.: para [0107]).
Regarding claim 27, Olsen teaches quantitative PCR and digital PCR (e.g.: para [0108]).
Regarding claims 31, Olsen teaches that a machine learning algorithm can be used to analyze methylation profiles and select particular CpG sites that are indicative of liver disease stage or severity (e.g.: para [0118]-[0125]).
Regarding claims 32, Olsen teaches the analysis of liver disease is based on methylation detected in a cell-free sample from the subject such as a plasma sample, which does not require any liver biopsy (e.g.: para [0205] and [0018]).
Regarding claim 38, in the method of Olsen, Olsen teaches filtering values associated with differentially methylated regions (para [0121]) using feature selection to select a subset of features by assessing the relevance and/or optimizing a set of features [i.e., reducing the number of informative and/or predictive CpGs for identifying the states] (para [0122-0123]).
Claim Rejections - 35 USC § 103
Claim(s) 1-2, 4-11, 14, 20, 22, 24-27, 31-35, and 38 is/are rejected under 35 U.S.C. 103 as being unpatentable over Olsen (WO 2020 150258 A1; cited on the IDS dated 03/13/2024, published 07/23/2020).
Olsen teaches a method of classifying a liver disease of a subject (entire document, e.g., Fig. 1) comprising:
(a)-(b) obtaining a set of CpG methylation status at a set of CpG sites of target sequences from a cfDNA sample (para [0017-18]; [0099]; [0194]; [0204]: “A cell-free biological sample is obtained…from a subject…processed and assayed for nucleic acid molecules (e.g., nucleic acid molecules derived from the cell-free biological sample)”; [0201]: “Methylation values are calculated for 10,508 analyzed CpGs”; Fig. 1)
identifying a methylation pattern based on the set of CpG methylation statuses, wherein the methylation pattern distinguishes between NAFL [instant “NALFD”], NASH, and cirrhosis (para [0194]: “Group A (…NAFL/Fibrosis F0-1), Group B (NASH/F0-1), and Group C (NASH/F3-4)”; [0193]: “a panel of cfDNA methylation markers that predict the presence of…NASH is identified”; para [0178]: “based at least in part on a data set obtained using the methods…identifying the presence or absence of cirrhosis”; [0093]: “identifying liver disease by processing biological samples…subjects may include patients with NAFLD who are at increased risk of having SH and/or fibrosis” [i.e., those with NAFL]; [0202]; Table 3; [0154])
assigning a liver disease state to the subject based on the methylation pattern, wherein the liver disease state comprises one of: NAFL [instant “NALFD”], NASH, and cirrhosis (Fig. 1; para [0040]; “the presence or the severity of the liver disease is identified according to a Non-Alcoholic Fatty Liver Disease Activity Score [NAS] composite comprising steatosis, lobular inflammation, and hepatocellular ballooning”; [0154]: “an NAS value of >5 including both steatosis and hepatocyte ballooning is considered indicative of NASH”; [0178]: “identifying the presence or absence of cirrhosis”; [0072]; [0197]; claim 10)
administering a therapeutic intervention to treat the severity of the disease of the subject upon identifying the subject as having the disease/a given severity thereof (para [0164])
In the identifying a severity of a disease, Olsen teaches that the methods comprise a machine learning algorithm trained on one or more features (para [0118]), wherein markers and genomic regions are identified from subjects having a liver disease and/or a particular severity compared to subjects not having a liver disease and/or having a different severity (para [0120]). Olsen teaches that values associated with said nucleic acids are analyzed using feature selection using filter techniques to assess the relevance of features and search for an optimal set (para [0122]), wherein selected features are classified using a classifier algorithm (para [0123]). Olsen teaches classifiers capable of outputting more than two values in the classification, wherein such may be the clinical identification of the liver disease of the subject (para [0125]).
Regarding claim 2, in the method of Olsen, Olsen teaches that a sample may include cfDNA fragments (e.g.: para [0079]).
Regarding claim 4, in the method of Olsen, Olsen teaches enrichment of target regions using hybridization to capture probes (e.g.: para [0201]).
Regarding claims 5-7, in the method of Olsen, Olsen teaches analyzing methylation levels and patterns (e.g.: para [0153]; para [0204]) and providing a value of the probability of having a liver disease of a particular severity (e.g.: para [0128]), and teaches the use of cutoff values in classifying a sample (e.g.: para [0127]).
As above, Olsen teaches that the subject may be at risk of [i.e., not have] NASH but have NALFD, i.e., have NAFL [instant “NAFLD”], thus teaching that methylation pattern distinguishes between instant “NALFD” and NASH in a training subset of data. It is likewise noted that Olsen provides a NAS score threshold for distinguishing NASH and lower severity NAFLD, i.e., NALF. Therefore, it follows that the severity of liver disease probability and cut-offs would be provided for each of said liver disease severity states.
Regarding claims 8 and 9, in the method of Olsen, Olsen teaches that subject classification can include a measure of the level or stage of fibrosis including no fibrosis (e.g.: para [0154]; Table 2; para [0194]). As in the rejection of claim 5 above, Olsen teaches assigning a probability to a severity of a liver disease, wherein Olsen also teaches cirrhosis.
Regarding claims 10 and 11, in the method of Olsen, Olsen includes aspects of determining the absence of liver inflammation (e.g.: para [0009] and [0155]), where absence of inflammation of the liver is no hepatitis (instant claim 10) and no inflammation (instant claim 11). As in the rejection of claim 5 above, Olsen teaches assigning a probability to a severity of a liver disease, wherein Olsen also teaches NASH (instant claim 10).
Regarding claim 14, in the method of Olsen, Olsen teaches providing a value of the probability of having a liver disease of a particular severity (e.g.: para [0128]), and teaches providing a report of results (e.g.: para [0094]).
As discussed above in claim 5, the severities correspond to NAFLD, NASH, and cirrhosis positive states.
Regarding claim 20, in the method of Olsen, Olsen teaches enrichment of target regions using hybridization to capture probes (e.g.: para [0201]) on training samples including plasma samples (para [0200]), wherein the cfDNA was analyzed (para [0197]; see also para [0077]). Olsen teaches feature selection using weights of logistic regression and ANOVA [i.e., analysis of variance, which utilizes a “cut-off requirement” determined by a significance and degrees of freedom] (para [0122]).
Regarding claims 22, 24 and 26, in the method of Olsen, Olsen teaches bisulfite sequencing which provides a detection of 5mC or 5hmC (e.g.: para [0101]; [0098]).
Regarding claim 25, in the method of Olsen, Olsen teaches using arrays of probes from a targeted panel to enrich particular sequences (e.g.: para [0107]).
Regarding claim 27, in the method of Olsen, Olsen teaches quantitative PCR and digital PCR (e.g.: para [0108]).
Regarding claims 31, in the method of Olsen, Olsen teaches that a machine learning algorithm can be used to analyze methylation profiles and select particular CpG sites that are indicative of liver disease stage or severity (e.g.: para [0118]-[0125]).
Regarding claims 32, in the method of Olsen, Olsen teaches the analysis of liver disease is based on methylation detected in a cell-free sample from the subject such as a plasma sample, which does not require any liver biopsy (e.g.: para [0205] and [0018]).
Regarding claims 33-35, as discussed in the rejection of claim 5 above, Olsen teaches providing a probability of each of the severities of the liver disease and further teaches probabilities of classifications including at least about 60% and at least about 80% (para [0128]). Olsen teaches configuring the ML algorithm at various accuracies, sensitivities, specificities, PPV, NPV, and statistical confidence (para [0141-146]; [0149]), wherein Olsen teaches that the trained ML algorithm may be adjusted or tune to improve performance including said factors for identifying a severity of the disease by adjusting or tuning parameters of the ML algorithm (para [0150]).
Thus, while Olsen fails to teach specific probabilities corresponding to specific severities [i.e., the disease states], such would be obvious under MPEP 2144.05 routine optimization, not least because Olsen specifically teaches tuning the algorithm to optimize for specific classification abilities.
Regarding claim 38, in the method of Olsen, Olsen teaches filtering values associated with differentially methylated regions (para [0121]) using feature selection to select a subset of features by assessing the relevance and/or optimizing a set of features [i.e., reducing the number of informative and/or predictive CpGs for identifying the states] (para [0122-0123]).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Olsen (WO 2020 150258 A1; cited on the IDS of 03/13/2024, published 07/23/2020), in view of Bibikova (Bibikova M, et al. High density DNA methylation array with single CpG site resolution. Genomics. 2011 Oct;98(4):288-95. Epub 2011 Aug 2).
Regarding claim 3, in the method of Olsen, Olsen teaches the identification of sets of CpG sites with methylation statuses that are associated liver disease severity, and the detection of methylation profiles in DNA fragments in a sample from a subject to identify a liver disease severity.
Olsen et al does not provide for the further shearing of fragments in a sample.
Bibikova rectifies this by teaching shearing of DNA as part of a methylation analysis (e.g.: pg. 293, 4.6 Whole-genome bisulfite sequencing), wherein the technique allows for high throughput profiling using a BeadChip (Abstract).
Therefore, it would have obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the DNA shearing of Bibikova in the DNA methylation detection of Olsen. The artisan would have been so motivated in order to allow for high throughput analysis, as taught by Bibikova. Such would have a high expectation of success as both are directed at methylation analysis and represent the application of a known technique to a known method.
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Olsen (WO 2020 150258 A1; cited on the IDS dated 03/13/2024, published 07/23/2020), in view of Loomba (Loomba R, et al. DNA methylation signatures reflect aging in patients with nonalcoholic steatohepatitis. JCI Insight. 2018 Jan 25;3(2):e96685).
Regarding claim 12, in the method of Olsen, Olsen teaches the identification of sets of CpG sites with methylation statuses that are associated liver disease severity, and the detection of methylation profiles in DNA fragments in a sample from a subject to identify a liver disease severity.
However, Olsen fails to teach a level of classification based on necrosis.
Loomba rectifies this by teaching an association between DNA methylation and necrosis in NASH pg. 2-3 and Figure 3C and 3D).
Loomba further teaches that their results identify a peripheral blood methylation signature that links enhanced age acceleration of NASH patients with tissue injury based on functional differences in cellular apoptosis and necrosis (pg. 2, para 3), wherein such identify a subset of NASH patients (pg. 3, para 1).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included probability of necrosis related to detected CpG methylation, as taught by Loomba, in the DNA methylation-based classification of Olsen, motivated by the desire to meaningfully further subset NASH patients, as taught by Loomba. There would have been a strong expectation of success as both are directed to methylation pattern analysis in non-alcoholic liver diseases and such represents the application of a known technique to a known method.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable Olsen (WO 2020 150258 A1; cited on the IDS dated 03/13/2024, published 07/23/2020), in view of Ma (Ma J, et al. A Peripheral Blood DNA Methylation Signature of Hepatic Fat Reveals a Potential Causal Pathway for Nonalcoholic Fatty Liver Disease. Diabetes. 2019 May;68(5):1073-1083. Epub 2019 Apr 1.).
Regarding claim 13, in the method of Olsen, Olsen teaches the identification of sets of CpG sites with methylation statuses that are associated liver disease severity, and the detection of methylation profiles in DNA fragments in a sample from a subject to identify a liver disease severity, but fails to teach classifying a level of fat.
Ma rectifies this by teaching an association between DNA methylation and variation in hepatic fat (e.g.: p. 1077 - Variation in Hepatic Fat Explained by Differentially Methylated CpGs; Table 1), wherein the methylation sites were also associated with risk for new-onset type 2 diabetes (T2D) (abstract). Ma teaches that NAFLD is a risk factor for T2D (Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included a level of haptic fat related to detected CpG methylation, as taught by Ma, in the DNA methylation-based classification of Olsen, motivated by the desire to further predict a comorbid condition of NALFD [i.e., T2D], as taught by Ma. There would have been a strong expectation of success as both are directed to methylation pattern analysis in non-alcoholic liver diseases and such represents the application of a known technique to a known method.
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable Olsen (WO 2020 150258 A1; cited on the IDS dated 03/13/2024, published 07/23/2020), in view of Zhou (WO 2017/212428; published 12/14/2017).
Regarding claim 21, in the method of Olsen, Olsen teaches enrichment of target regions using hybridization to capture probes (e.g.: para [0201]) on training samples (para [0200]). Olsen teaches feature selection using weights of logistic regression and ANOVA [i.e., analysis of variance, which utilizes a “cut-off requirement” determined by a significance and degrees of freedom] (para [0122]).
Olsen teaches that the sample may comprise blood, including leukocytes or white blood cells, wherein a sample may comprise both cells and cell-free nucleic acid material, and wherein nucleic acid molecules may be included within cells (para [0077]).
However, Olsen fails to explicitly teach training the model based on samples from purified white blood cell types.
Zhou rectifies this by teaching a method of characterizing a cfDNA sample by calculating a methylation pattern of a cfDNA read and characterizing the read as containing a biological composition [tissue origin] (e.g., claim 1), wherein the biological composition may be diseased tissue, liver tissue, neutrophils, T-cell, B-cells, and combinations thereof (claim 7). Zhou teaches diagnosing a disease utilizing the method (e.g., pg. 27, cfDNA Composition and Disease Diagnosis).
Zhou further teaches that cfDNA fragments harboring aberrant methylation in “outlier” markers often come from white blood cells in due to inter-individual variance, wherein such will impair the accuracy of methylation analysis (para [00242]). Zhou teaches removing markers corresponding to these normal cells, such as white blood cells (para [00242]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have selected the set of CpG sites, taught by Olsen, based on a classifier(s) of Olsen using a sample comprising white blood cells, in view of Zhou, in the DNA methylation-based classification of Olsen, motivated by the desire to remove “outlier” markers, as taught by Zhou. There would have been a strong expectation of success as both are directed to methylation pattern analysis in disease diagnosis and such represents the application of a known technique to a known method.
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable Olsen (WO 2020 150258 A1; cited on the IDS dated 03/13/2024, published 07/23/2020), in view of Hernández (Hernández HG, et al. Optimizing methodologies for PCR-based DNA methylation analysis. Biotechniques. 2013 Oct;55(4):181-97).
Regarding claim 23, in the method of Olsen, Olsen teaches the identification of sets of CpG sites with methylation statuses that are associated liver disease severity, and the detection of methylation profiles in DNA fragments in a sample from a subject to identify a liver disease severity. Olsen further teaches sequence identification with array methods and PCR (para [0103]). Olsen taches that methylated/hydroxymethylated cytosines are 5mC or 5hmC (para [0101]).
Olsen fails to explicitly teach the determination of average level of 5mC or 5hmC across individual sites.
Hernandez rectifies this by teaching quantifying methylation at CpG sites using averages and including PCR (e.g.: p. 184 - Direct-BSP; Cloning-based BSP; Figure 2; pg. 185, col 3, para 2: “sequencing results…should be averaged”). Hernandez teaches that direct-BSP provides more accurate detection of differences as low as 20% in methylation status in a single CpG (pg. 185, col 2, para 1).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to used known prior art method for the detection and quantifying of CpG methylation, including direct-BSP as taught by Hernandez, in the DNA methylation-based classification of Olsen. The artisan would have been so motivated in order to utilize the accurate detection of low level of methylation status in a single CpG provided by the method, as taught by Hernandez. There would have been a strong expectation of success as both are directed to methylation pattern analysis in nucleic acids and such represents the application of a known technique to a known method.
Response to Arguments
Applicant's arguments filed 8/15/2025 have been fully considered but they are not persuasive.
In response to the applicant’s argument regarding the 101 rejection, contrary to the applicant’s argument that the claim now ties the judicial exception to a practical application, a “therapy selected to treat” one of the states is not sufficient to tie the judicial exceptions to a practical application. The therapy is generically recited and thus amounts to no more than instructions to “apply” the judicial exception to a relevant party (e.g., a clinician). See the 101 rejection above for additional discussion, in particular the cited example from the Subject Matter Eligibility Examples. It is also noted that, broadly interpreted, the therapy administration is not specifically tied to the assigned state.
Further, as discussed in the 101 rejection, contrary to applicant’s assertion that the identifying the methylation pattern based on CpG statuses and predicting three states is neither routine nor conventional, the standard for subject matter eligibility under Step 2B is not novelty or obviousness, but rather an “inventive concept”. See MPEP 2106.05(I). In the instant case, the claims encompass abstract ideas, mere data gathering, and a treatment step that amounts to mere instruction to “apply” the judicial exception give its breadth. The Courts have found that such limitations directed to data gathering and generic treatments have not been enough to qualify as “significantly more” than the judicial exception. See MPEP 2106.05(I)(A). Thus, the claimed elements, on the whole, are not sufficient to amount to significantly more.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., absence of histological confirmation or differentiation from a healthy individual) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Indeed, it common in machine learning methods to utilize a data where the class of the sample is identified through traditional/gold-standard means, such as histological identification. Additionally, the claims merely require that the methylation pattern is predictive of the NAFLD, NASH, or cirrhosis positive states and distinguishes between the NAFLD, NASH, and cirrhosis positive states, wherein the sample is assigned a state based on the methylation pattern. The claims permit—aside from claim 32—the artisan to utilize a biopsy to select subjects to perform this method on or to utilize a biopsy to confirm the method before treat, for example, given the open ended “comprising”. Likewise, while it is noted that there are embodiments that comprise non-methylation factors in Olsen, Olsen teaches many embodiments.
Further, while applicant argues that Olsen would be unable to distinguish NAFL and NASH because of NAFL’s “little or no inflammation or liver damage” whereas NASH is defined by “inflammation of the liver and liver damage” necessitating “methylation markers that are associated with more than inflammation and fibrosis” (Remarks, pg. 11, para 3), Olsen teaches determining the severity of fibrosis, severity of inflammation, and presence of steatohepatitis, as noted in the Remarks at the top of pg. 12. Therefore, Olsen does sufficiently teach distinguishing between NAFL (i.e., little inflammation and little liver damage) and NASH (i.e., inflammation, liver damage, and steatohepatitis [Non-Alcoholic SteatoHepatitis]). Further supporting this, Zeybel (2015, as cited in the IDS dated 10/15/2025) distinguishes between mild and severe NALFD [i.e., NALF and NASH] based on progression of fibrosis using methylation (entire document, e.g., Abstract).
Regarding the arguments of Bibikova, Loomba, Ma, Hernandez, and Peng each individually not meeting all of the elements of the amended claims to which they were applied, 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).
For the above reasons, arguments are not considered persuasive.
Conclusion
No claims are allowed.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Qi (WO 2019/209884 A1; published 10/31/2019) teaches a method of screening for a condition of a subject comprising obtaining a first plurality of sequencing reads from a first sample comprising cell-free nucleic acids from the subject (claim 1), wherein said sequencing reads comprise reads informative of a methylation profile of the cf-nucleic acids (claim 3), wherein the condition is a liver condition selected from the group consisting of liver cirrhosis, hepatocellular carcinoma, NAFLD, NASH, and a combination thereof (claim 31).
It is noted that a combination thereof may be cirrhosis, NAFLD, and NASH. Qi does not explicitly teach feature selection.
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/EMMA R HOPPE/ Examiner, Art Unit 1683
/ANNE M. GUSSOW/ Supervisory Patent Examiner, Art Unit 1683