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 1-10, 13-19, and 24-29 are pending and under examination.
Claims 1-10, 13-19, and 24-29 are rejected.
Claims 11-12, 20-23, and 30 are canceled.
Claims 1 and 24 are amended and independent.
No claims are new, withdrawn, or allowed.
Office Action Outline
Rejections applied
Abbreviations
112/b Indefiniteness
PHOSITA
"a Person Having Ordinary Skill In The Art before the effective filing date of the claimed invention"
112/b "Means for"
BRI
Broadest Reasonable Interpretation
112/a Enablement,
Written description
CRM
"Computer-Readable Media" and equivalent language
112 Other
IDS
Information Disclosure Statement
102, 103
JE
Judicial Exception
101 JE(s)
112/a
35 USC 112(a) and similarly for 112/b, etc.
x
101 Other
N:N
page:line
Double Patenting
MM/DD/YYYY
date format
Priority
As detailed in the 10/09/2019 filing receipt, this application claims benefit of priority to U.S Provisional Application 62/738,965, filed 09/28/2018.
Overview of Withdrawal/Revision of Objections/Rejections
In view of the amendment and remarks received 01/23/2026:
• The Specification objection is withdrawn.
• The product by process interpretations are no longer asserted.
• The 112(b) rejection is withdrawn. Claims 1 and 24 have been amended to recite "...the classification indicating whether the candidate variant is a somatic mutation that is predicted to be unmatched in genomic nucleic acid or a somatic variant that is predicted to be matched in genomic nucleic acid" (amended in portions underlined) which is considered to clarify the scope of "somatic mutation" and "somatic variant" in the claim.
• The 101 rejection is maintained with revision.
• The 103 rejection is withdrawn for the following reasons: Applicant's 01/23/2026 arguments regarding the 103 rejection (p.15-19) are overall persuasive. Specifically, Applicant's assertion is persuasive that the Saunders reference "...is different from multiplying likelihoods output from two distinct learned distributions in a mixture model - one variant-level and one gene-level-as required by claim 1" (p.17, paragraph 4). Although the claims read on a Bayesian statistical method for modeling joint posterior with a prior (as used in Saunders), see Specification [0141-0143], the difference lies in the distributions used (as asserted by Applicant, p.17, para.4), in that the claimed invention uses a variant-level and a gene-level distribution (the first and second distributions in claims 1 and 24, from which the first and second likelihoods are determined from, which are ultimately used in determining the numerical score used for classification of the candidate variant in claims 1 and 24) of a single cell free nucleic acid sample, while Saunders determines distributions from matched tumor and normal samples (emphasis added). The prior art, including the cited references, does not teach at least: "determining, by the machine-learning mixture model, a numerical score describing an overall likelihood that the candidate variant is a somatic mutation unmatched in the genomic nucleic acid sample using 1) a comparison of a measure of first properties of a distribution of somatic mutations unmatched in genomic nucleic acid to a measure of second properties of a distribution of somatic variants matched in genomic nucleic acid and 2) a product of the first likelihood that the candidate variant is a somatic mutation and the second likelihood that the certain gene on which the candidate variant is located will have at least one mutation" of claims 1 and 24.
Rejections and/or objections not maintained from previous office actions are withdrawn. The following rejections and/or objections are either maintained or newly applied. They constitute the complete set applied to the instant application.
Claim Interpretation
Claims 1, 5, 8, 15, 24, and 26 recite the term “alternate frequency," which is interpreted from Specification [0079] and [0083] as the frequency of a given alternate allele (the alternative allele also known as ALT, mutation, or variant).
Claims 1, 2, 5, 6, 9, 10, 13, 15-19, and 24-29 recite the term “variant(s)," and claims 1, 2, 9, 16, 17, 19, 24, and 27 recite the term “mutation(s).” The specification at para. [0073] discloses “the term ‘mutation’ refers to one or more SNVs (single nucleotide variants) or indels,” while [0084] discloses “the term ‘variant’ or ’true variant’ refers to a mutated nucleotide base at a position in the genome.” Therefore the single terms “variant” and “mutation” are being interpreted as being interchangeable.
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 1-10, 13-19, and 24-29 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 details the following framework to analyze Subject Matter Eligibility:
• Step 1: Are the claims directed to a category of statutory subject matter (a process, machine, manufacture, or composition of matter)? (see MPEP § 2106.03)
• Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. an abstract idea, a law of nature, or a natural phenomenon? (see MPEP § 2106.04(a)). Note, the MPEP at 2106.04(a)(2) & 2106.04(b) further explains that abstract ideas and laws of nature 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);
• mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information);
• laws of nature and natural phenomena are naturally occurring principles and/or relations that are naturally occurring or that do not have markedly different characteristics compared to what occurs in nature.
• Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application? (see MPEP § 2106.04(d))
• Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept? (see MPEP § 2106.05)
Step 1:
Claims 1-10, 13-19, and 28-29 are directed to a 101 process, here a method. Claims 24-27 are directed to a 101 machine or manufacture, here a system. As such, claims 1-10, 13-19, and 24-29 are directed to a related method and system, which fall under categories of statutory subject matter. (See MPEP § 2106.03). (Step 1: Yes.)
Step 2A, Prong One:
The claims are found to recite abstract ideas in the form of mental processes and mathematical concepts, as well as a law of nature, as follows:
Independent claim 1 recites mental processes of: identifying a candidate variant; determining by applying a first distribution of a machine-learning mixture model, a first likelihood that the candidate variant is a somatic mutation based on an observed frequency of the somatic mutation against the first distribution, (also considered a mathematical concept), wherein the first distribution of the machine learning mixture model is generated to determine a candidate variant source using a training data set of known somatic variants identified in cell-free nucleic acid samples and in matched genomic nucleic acid samples from a population of training subjects; determining that the candidate variant is located on a certain gene (also considered a mathematical concept); determining, by applying a second distribution of the machine learning model, a second likelihood, that the certain gene, on which the candidate variant is located, will have at least one mutation based on observed data related to the certain gene (also considered a mathematical concept); considering the observed data related to the gene, the second distribution of the machine-learning model generated using a second training data set of nucleic acid fragments with one or more mutations from the population of training subjects across genes in the human genome (also considered a mathematical concept); determining a numerical score, by the machine learning mixture model, which describes an overall likelihood that the candidate variant is a somatic mutation unmatched in the genomic fluid sample(also considered a mathematical concept); comparing a measure of first properties of a distribution of the somatic mutations unmatched in genomic fluid to a measure of second properties of a distribution of somatic variants matched in genomic nucleic acid; using a product of first likelihood that the candidate variant is a somatic mutation and the second likelihood that the certain gene on which the candidate variant is located will have at least one mutation (also considered a mathematical concept); determining a classification of the candidate variant, by the machine learning mixture model, using the numerical score, as to whether the candidate variant is a somatic mutation that is predicted to be unmatched in genomic nucleic acid or a somatic variant that is predicted to be matched in genomic nucleic acid (also considered a mathematical concept). Independent claim 24 recites a system, computer processor, and a memory with computer program instructions to perform the abstract ideas as in claim 1.
Claim 2 recites a mental process of considering the first and second properties, of the distribution of, respectively, somatic mutations unmatched and matched in genomic nucleic acid, are modeled by general linearized models (GLM) (also considered a mathematical concept). Claim 3 recites a mental process of considering each GLM generates outcomes from a gamma distribution (also considered a mathematical concept). Claim 4 recites a mental process of considering each GLM generates outcomes from a normal distribution, binomial distribution, or Poisson distribution (also considered a mathematical concept). Claim 5 recites a mental process of considering the GLM are trained by modeling the true alternate frequency of the candidate variant as dependent on the true alternate frequency of the candidate variant in a cell-free nucleic acid sample (also considered a mathematical concept). Claim 6 recites the mental process of considering the numerical score is determined at least by modeling alternate allele counts of the candidate variant using a Poisson distribution after a gamma distribution (also considered a mathematical concept). Claim 7 recites the mental process of considering the measure of first or second properties represents a likelihood under a GLM using gamma distribution with Poisson counts (also considered a mathematical concept). Claim 8 recites the mental process of considering the first and second properties include depth, alternate frequency, and/ or trinucleotide context of a given nucleic acid sample. Claim 9 recites the mental process of determining the numerical score by the mental process of comparing the first, second, and third properties of a distribution of variants with a source different than the first and second properties (i.e., with a source different from the somatic mutations unmatched in genomic nucleic acid and the somatic variants matched in genomic nucleic acid). Claim 10 recites the mental process of considering the somatic variants matched in genomic nucleic acid are matched with variants in white blood cells (WBCs).
Claims 13 and 25 recite the mental processes of: determining an attribute of an individual whom the cell free nucleic acid sample was obtained; determining a third likelihood the individual will have the candidate variant based on training data of individuals associated with the attribute; considering the training data; and considering the information the product further including the third likelihood. Claim 14 recites the mental process of considering the information of the attribute is an age or age range. Claims 15 and 26 recite the mental process and mathematical concept of determining an integral of a plurality of negative binomial distributions over an expected distribution of alternate frequency of the candidate variant in a given cell free nucleic acid sample. Claim 16 recites the mental process of considering the negative binomial distributions model expected distributions of false positive and true positive mutations of the candidate variant in a given cell free nucleic acid sample. Claim 17 recites the mental process of considering negative binomial distributions account for depths of sequence reads of samples of the somatic mutations unmatched in genomic nucleic acid and the somatic variants matched in genomic nucleic acid. Claim 18 recites the mental process of considering the somatic variants matched in genomic nucleic acid are associated with clonal hematopoiesis. Claims 19 and 27 recites the mental processes of: determining a prediction that the candidate variant is a true mutation in the cell free nucleic acid sample based on the classification; and determining a likelihood that an individual has a disease based at least in part on the prediction.
Claim 28 recites the mental process of: considering the sequence read data obtained by enriching and NGS; and identifying a candidate variant. Claim 29 recites the mental process of determining a presence of cancer from the cell free nucleic acid sample based on the classification of the candidate variant.
Additionally, claim 19 and 27 recite a law of nature by the correlation of an individual having a disease with the individual’s candidate variant being a true mutation in cell free nucleic acid.
Step 2A, Prong One summary: The claims recite mental processes and mathematical concepts (as well as a law of nature recited in claims 19 and 27). When considering the broadest reasonable interpretation (BRI) of the claims, the mental processes recited in independent claims 1 and 24 include, e.g.: determining a first likelihood…based on an observed frequency; determining that the candidate variant is located on a certain gene; comparing a measure of first and second properties; determining classification of the candidate variant; etc., are directed to processes that may be performed mentally, as there are no particular limitations recited in claims 1 and 24 which would prevent the mental processes from being performed in the human mind or with pen and paper. Additionally, as an example, machine learning inherently recites mathematical concepts, which may include the algorithms and statistical methods as recited in Specification paragraphs [0026], [0141-0143]. Such analysis performed mentally, or with paper and pencil, may take considerable time and effort, and although a general-purpose computer can perform these calculations at a rate and accuracy that can far exceed the mental performance of a skilled artisan, the nature of the activity is essentially the same, and therefore constitutes an abstract idea. Therefore, the claims recite elements that constitute a judicial exception in the form of an abstract idea of mental processes and mathematical concepts, as well as a law of nature. (Step 2A, Prong One: Yes.)
Step 2A, Prong Two:
In Step 2A, Prong One above, claim steps and/or elements were identified as part of one or more judicial exceptions (JEs). Here at Step 2A, Prong Two, any remaining steps and/or elements not identified as JEs are therefore in addition to the identified JE(s), and are considered additional elements. Because the claims have been interpreted as being directed to judicial exceptions (abstract ideas in this instance) then Step 2A, Prong Two provides that the claims be examined further to determine whether the judicial exception is integrated into a practical application [see 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.
21. MPEP § 2106.04(d)(I) lists the following five example considerations for evaluating whether a judicial exception is integrated into a practical application:
(1) An improvement in the functioning of a computer or an improvement to other technology or another technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a).
(2) Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2).
(3) Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b).
(4) Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c).
(5) Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
The claims recite additional elements as follows:
Additional elements of data gathering, inputting, and outputting steps: Claims 1, 24, and 28 recite additional elements of: a cell free nucleic acid sample (claims 1 and 24); enriching fragments (claim 28); and next generation sequencing (claim 28). Data gathering steps are additional elements which perform functions of inputting, collecting, and outputting the data needed to carry out the abstract idea. These steps are considered insignificant extra-solution activity, and are not sufficient to integrate an abstract idea into a practical application as they do not impose any meaningful limitation on the abstract idea or how it is performed, nor do they provide an improvement to technology (see MPEP § 2106.04(d)(I)).
Additional elements of computer components: Claim 24 recites additional elements of a system, a computer processor, and a memory storing instructions. Claims 25 and 27 recite the additional element of a memory storing instructions. The claims require only generic computer components, which do not improve computer technology, and do not integrate the recited judicial exception into a practical application (see MPEP § 2106.04(d)(1) and MPEP § 2106.05(f)).
Step 2A Prong Two summary: Claims 1-10, 13-19, and 24-29 have been further analyzed with respect to Step 2A, Prong Two, and no additional elements have been found, alone or in combination, that would integrate the judicial exception into a practical application. At this point in examination, it is not yet the case that any of the Step 2A Prong Two considerations enumerated above clearly demonstrates integration of the identified JE(s) into a practical application. Referring to the considerations above, none of: (1) an improvement, (2) a treatment, (3) a particular machine, or (4) a transformation is clear in the record. For example, regarding the first consideration for improvement at MPEP 2106.04(d)(1), the record, including the Specification (even considering [0143, 0152. 0163, and 0195]), does not yet clearly disclose an explanation of improvement over the previous state of the technology field, and the claims do not yet clearly result in such an improvement. (Step 2A, Prong Two: No).
Step 2B:
Because the additional claim elements do not integrate the abstract idea or law of nature into a practical application, the claims are further examined under Step 2B, which evaluates whether the additional elements, individually and in combination, amount to significantly more than the judicial exception itself by providing an inventive concept. An inventive concept is furnished by an element or combination of elements that is recited in the claim in addition to the judicial exception, and is sufficient to ensure that the claim, as a whole, amounts to significantly more than the judicial exception itself (see MPEP § 2106.05).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exceptions because the claims recite additional elements that are well-understood, routine, and conventional. Those additional elements are as follows:
The additional elements of data gathering (cell-free DNA sample, performing next generation sequencing, and enriching fragments) of claims 1, 24, and 28 do not cause the claims to rise to the level of significantly more than the judicial exception. The courts have receiving or transmitting data over a network; storing and retrieving information in memory; analyzing DNA to provide sequence information or detect allelic variants; and using polymerase chain reaction to amplify and detect DNA, [see MPEP§2106.05(d)(II)], as well-understood, routine, conventional activity when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
Additionally, Hao et al., (BMC genomics, vol. 17, pages 217-226 (2016)), shows a method for analyzing enriched data from Illumina MiSeq sequencing to use with liquid biopsy and analyzing variants (p.218-219, p.224, and throughout). Kothen-Hill et al., (Deep learning mutation prediction enables early stage lung cancer detection in liquid biopsy. https://openreview.net/forum?id=H1DkN7ZCZ, p.1-24 (Feb 2018)) describes whole genome sequencing using Illumina HiSeq, obtaining reads, and enrichment in studying variants in cfDNA of lung cancer patients(p.3-4, fig.1, p. 6, and throughout).
Further, the instant Specification at paragraph [0097] discloses, “In step 140, sequence reads are generated from the enriched DNA sequences, e.g., enriched sequences 180 shown in FIG. lB. Sequencing data can be acquired from the enriched DNA sequences by known means in the art. For example, the method 100 can include next generation sequencing (NGS) techniques including synthesis technology (Illumina), pyrosequencing ( 454 Life Sciences), ion semiconductor technology (Ion Torrent sequencing), single-molecule real-time sequencing (Pacific Biosciences), sequencing by ligation (SOLiD sequencing), nanopore sequencing (Oxford Nanopore Technologies), or paired-end sequencing.
Thus, the data gathering steps are shown to be well-understood, routine, and conventional in the art, and as a result, do not provide an inventive concept by amounting to significantly more than the judicial exception.
The additional elements of a system, a computer processor, and a memory storing instructions of claims 24, 25, and 27 do not cause the claims to rise to the level of significantly more than the judicial exception; these are conventional computer components, which do not amount to significantly more than the judicial exception, as they do not provide an inventive concept.
Further regarding the conventionality of additional elements, the MPEP at 2106.05(b) and 2106.05(d) presents several points relevant to conventional computers and data gathering steps in regards to Step 2A Prong 2 and Step 2B, including:
A general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions, does not qualify as a particular machine (see MPEP 2106.05(b)(I)), as in the case of claims 24, 25, and 27. which are interpreted to recite conventional computer components.
Integral use of a machine to achieve performance of a method may integrate the recited judicial exception into a practical application or provide significantly more, in contrast to where the machine is merely an object on which the method operates, which does not integrate the exception into a practical application or provide significantly more (see MPEP 2106.05(b)(II). In claims 24, 25, and 27, instructions for the method are executed on a processor; here, the processor acts only as a tool to perform the judicial exception.
Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not integrate a judicial exception or provide significantly more (see 2106.05(b)(III). Data gathering steps (such as recited in claims 1, 24, and 28) do not impose meaningful limitations on the claims.
The courts have recognized “receiving or transmitting data over a network," “performing repetitive calculations," and “storing and retrieving information in memory," as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d)(II)). The gathering of data in claims 1, 24, and 28 is recited in a generic manner.
All the limitations of claims 1-10, 13-19, and 24-29 have been analyzed with respect to Step 2B, and none provides a specific inventive concept, as they all fail to rise to the level of significantly more than the identified judicial exception, and thus do not transform the judicial exception into a patent eligible application of the exceptions. (Step2B: NO.)
Therefore, the claims, when the limitations are considered individually and as a whole, are rejected under 35 U.S.C. § 101 as being directed to non patent-eligible subject matter.
Response to Applicant Arguments - 35 USC 101
The Applicant's arguments filed 01/23/2026 have been fully considered but they are not yet persuasive.
Step 2A Prong One arguments:
The Applicant asserts, p.11-13 (considered to pertain to Step 2A Prong One, in which judicial exceptions are identified):
• "Claim 1 recites limitations of 'determining...a first likelihood...,' 'determining...a second likelihood...,' and 'determining...a numerical score...' cannot be characterized as directed to any abstract idea." (Remarks, bridging p.11-12.)
• "... these limitations cannot be directed to mathematical concepts... Generation of these distributions is a data compilation step that surveys the datasets to compute parameters defining the distribution." (Remarks, p.12, ¶ 2.)
• "... these limitations are not mental processes... Though it may seem like a human mind can perform these limitations, it is impractical for the human mind to do so...The various steps of claim 1 relate to deployment of a machine-learning model, that is rooted in computer functionality." (Remarks, p.12, ¶ 3.)
The arguments are not persuasive because the claims are considered to recite mental processes as there is no detail recited which would prevent the performance in the human mind or with pencil and paper. When considering the recited mathematical concepts and mental processes, such steps and analysis performed mentally, or with paper and pencil, may take considerable time and effort, and although a general-purpose computer can perform these steps and analysis at a rate and accuracy that can far exceed the mental performance of a skilled artisan, the nature of the activity is essentially the same, and therefore constitutes an abstract idea. Further, regarding the machine learning model rooted in computer functionality, this can be seen as mere instructions to apply an exception on a computer (see MPEP 2106.05(f).
Step 2A Prong Two arguments:
The Applicant asserts, p.13-14:
• " The additional elements embody an improvement to the field of machine-learning." (Remarks, p.13, ¶ 4.)
• "This case can be analogized further to Ex parte Desjardins... As in Desjardins, the claimed model architecture ties the claims to a specific improvement in machine learning within the defined technical context cfNA variant source classification." (Remarks, bridging p.13-14.)
Regarding the 101 rejection, a nexus is lacking between the JEs and integration into a practical application, when considering the claim as a whole. At this point in examination, it is not yet the case that the Step 2A Prong Two consideration for an improvement to technology or to a technical field clearly demonstrates integration of the identified JE(s) (i.e., abstract ideas of statistical data analysis and machine learning in classification of candidate variants) into a practical application. Regarding the consideration for improvement (see MPEP §§ 2106.04(d)(1) and 2106.05(a)), the record, including the Specification (and even considering [0143, 0152. 0163, and 0195]), does not yet clearly disclose an explanation of improvement over the previous state of the technology field, and the claims do not yet clearly result in such an improvement. Merely reciting the words "apply it" (or an equivalent, (which in this case is “applying”) with the judicial exception (a first/second distribution of a machine-learning model), or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, does not integrate a judicial exception into a practical application. (See MPEP 2106.04(d), 2106.04(d)(1), and 2106.05(a)(II).)
To reiterate from the Step 2A, Prong Two analysis section above in the 101 rejection, an explanation of a technical improvement may help to overcome a 101 rejection, as discussed at Step 2A/2nd Prong, 1st consideration of the 101 analysis in MPEP 2106.04(d) and (d)(1). Such an improvement requires detailed explanation applicable to all embodiments reasonably within the claim scope. A detailed explanation of the particular improvement may include identification of the technology field, as well as clearly stating the improvement over the technology field. Submitting persuasive arguments supported by any necessary evidence (including showing improvement by comparison to other method(s) of dropout prediction) to demonstrate that one of ordinary skill in the art would understand that the disclosed invention improves technology may be helpful in successfully showing an improvement, and therefore integrating the abstract idea into a practical application. Additionally, in response to a rejection under 35 U.S.C. 101, an applicant could submit a declaration under § 1.132 providing testimony on how one of ordinary skill in the art would interpret the disclosed invention as improving technology and the underlying factual basis for that conclusion. See MPEP 2106.05(a).
As further examples, the argument may clearly and adequately explain cause and effect leading to improvement or, for example when such cause and effect explanation is not possible, then may include evidence (e.g. experimental data) comparing a claimed result to conventional results.
Also, arguments and evidence may be extrinsic to the original disclosure, including references available after the priority date, as long as it is clear that an argument applies to all embodiments of a properly supported claim.
Step 2B arguments:
The Applicant asserts, p.14-15:
• "...the additional elements are non-routine, unconventional, and not well understood activity in the technological field, thereby amounting to an inventive concept supporting eligibility under Step 2B." (Remarks, p.14, ¶ 5.)
• "... Critically, the prior art does not teach nor suggest the additional elements, specifically the architecture of the machine learning model..." (Remarks, p.14, ¶ 5.)
The arguments are not persuasive because the additional elements consist of a cell-free DNA sample, performing next generation sequencing, enriching fragments, and generically claimed computer components, which represent well-understood, routine, and conventional elements as put forth in the 101 rejection above.
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/M.A.V./Examiner, Art Unit 1687
/G. STEVEN VANNI/Primary patents examiner, Art Unit 1686
Prosecution Insights