DETAILED ACTION
Applicant’s response filed on 26 June 2026 has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 36-40, 42-43, 46-52, 56, 59, 61, 64, 66-67, and 69-71 are currently pending and under examination herein.
Claims 36-40, 42-43, 46-52, 56, 59, 61, 64, 66-67, and 69-71 are rejected.
Priority
The instant application also claims benefit to U.S. provisional application No. 73/018,304 filed on 04/30/2020. Domestic benefit is acknowledged. As such, the effective filing date of claims 36-43, 46-52, 56, 59, 61, 64, 65-67, and 69-71 is 04/30/2020.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/09/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. A signed copy of a list of references cited from each IDS is included in this Office Action.
Specification
The amended specification title is accepted. The specification filed on 6/26/2026 is accepted.
Claim Objections
Claim 69 is objected to because of the following informalities: Claim 67 recites “indeterminate benefit of treatment the first subject”. The recited claim is missing a preposition. The Examiner recommends that the claim be amended to “indeterminate benefit of treatment of the first subject with immunotherapy”. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 70-71 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. The amendments to claim 36 now include a step of measuring the transcripts. However, this is not something the a computer system or non-transitory computer readable medium that can perform nor is there a description of a computer system or non-transitory CRM that can perform this action on their own.
Claims 47-51 and 64 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 47 recites “wherein assaying the biological sample comprises determining a presence, level, or state of a protein or nucleic acid for each biomarker”. Of note, claim 47 is dependent on claim 36 and claim 36 has been amended to include measuring transcript levels. It is unclear if the claim intends to reference the measuring step in claim 36. Claims 48-51 have been rejected by virtue of dependency. Appropriate correction is required.
Claim 64 also recites an assaying step that is dependent on claim 36 where no such assaying step has been recited. Similarly, it is unclear if the claim intends to reference the measuring step recited in claim 36. Appropriate correction is required.
For the intents and purposes of compact prosecution, the Examiner will interpret assaying as referencing the measuring transcript levels step recited in claim 36.
Claims 47-51 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Regarding dependent claim 47, the assaying step broadens the measuring step by including determining a presence, level, or state of a protein or nucleic acid for each biomarker. Similarly, claim 49 also fails to further limit the assaying step as it recites the state of the nucleic acid comprises a sequence, mutation, polymorphism, deletion, insertion, substitution, translocation, fusion, break, duplication, amplification, repeat, copy number, transcript level, or any combination thereof. Regarding claim 50, the assaying step is not further limiting as it merely recites the same step and therefore has the same scope. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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.
Applicant's arguments, see page 11, filed 6/26/2026, with respect to claim 56, 67, and 69, has been fully considered and are persuasive. Therefore, the rejection of claims 56, 67, and 69 are withdrawn. See Response to Arguments at the end.
Claims 36-40, 42-43, 46-52, 59, 61, 66, and 70-71 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea and/or a natural phenomenon without significantly more. This rejection is newly recited and necessitated by claim amendment.
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES)
are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of
nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the
following limitations that equate to one or more categories of judicial exceptions:
Claim 36 recites a method for predicting benefit of immunotherapy for a cancer in a first subject, the method comprising: providing, by the one or more computers, the generated input data as input to a predictive model, the predictive model comprising at least one machine learning model, wherein each particular machine learning model of the at least one machine learning model is trained to generate output data that indicates whether a subject is likely to benefit from an immunotherapy based on the particular machine learning model processing of the set of features extracted from molecular data corresponding to transcript levels of the plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12; processing, by the one or more computers, the generated input data through the at least one machine learning model, to generate first data indicating whether the first subject is likely to benefit from the immunotherapy; determining, by the one or more computers and based on the generated first data, a likelihood that the first subject is to benefit from the immunotherapy.
Claim 37 recites a method, wherein determining, by the one or more computers and based on the generated first data, the likelihood that the first subject is to benefit from the immunotherapy includes calculating a probability.
Claim 38 recites a method further comprising: determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data satisfies one of the one or more thresholds, determining that the first subject is likely to benefit from the immunotherapy.
Claim 39 recites further comprising: determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data does not satisfy one of the one or more thresholds, determining that the first subject is not likely to benefit from the immunotherapy.
Claim 40 recites a method further comprising: determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data is (i) equal to one of the one or more thresholds or (ii) satisfies two of the one or more thresholds, determining that the first subject is likely to have an indeterminate benefit from the immunotherapy.
Claim 52 recites a method wherein the immunotherapy comprises an immune checkpoint therapy.
Claim 59 recites a method wherein the cancer comprises a lung bronchioloalveolar carcinoma (BAC), non-small cell lung cancer (NSCLC), or lung small cell cancer (SCLC).
Claim 61 recites a method wherein the at least one machine learning model comprises one or more of a random forest, support vector machine (SVM), logistic regression, K-nearest neighbor, artificial neural network, naive Bayes, quadratic discriminant analysis, Gaussian processes models, decision tree, or a combination thereof.
Claim 64 recites a method wherein at least one machine learning model consists of a support vector machine.
The limitations reciting providing, by the one or more computers, the generated input data as input to a predictive model, the predictive model comprising at least one machine learning model, wherein each particular machine learning model of the at least one machine learning model is trained to generate output data that indicates whether a subject is likely to benefit from an immunotherapy based on the particular machine learning model processing of the set of features extracted from molecular data corresponding to transcript levels of the plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12; processing, by the one or more computers, the generated input data through the at least one machine learning model, to generate first data indicating whether the first subject is likely to benefit from the immunotherapy; determining, by the one or more computers and based on the generated first data, a likelihood that the first subject is to benefit from the immunotherapy; and a method, wherein determining, by the one or more computers and based on the generated first data, the likelihood that the first subject is to benefit from the immunotherapy includes calculating a probability are verbal equivalents of mathematical computations and therefore fall under the “mathematical concept” grouping of ideas.
The limitations reciting determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data satisfies one of the one or more thresholds, determining that the first subject is likely to benefit from the immunotherapy; determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data does not satisfy one of the one or more thresholds, determining that the first subject is not likely to benefit from the immunotherapy; determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data is (i) equal to one of the one or more thresholds or (ii) satisfies two of the one or more thresholds, determining that the first subject is likely to have an indeterminate benefit from the immunotherapy fall under the “mental process” grouping of ideas. Evaluation of whether data passes thresholds can be practically performed in the human mind and is therefore a mental process.
The limitations reciting a method wherein the immunotherapy comprises an immune checkpoint therapy; a method wherein the cancer comprises a lung bronchioloalveolar carcinoma (BAC), non-small cell lung cancer (NSCLC), or lung small cell cancer (SCLC); wherein the at least one machine learning model comprises one or more of a random forest, support vector machine (SVM), logistic regression, K-nearest neighbor, artificial neural network, naive Bayes, quadratic discriminant analysis, Gaussian processes models, decision tree, or a combination thereof; and wherein at least one machine learning model consists of a support vector machine merely further limits the abstract idea.
Additionally, these limitations recite a correlation between biomarker expression and immunotherapy response, which are limited specifically to particular biomarkers found in claims 36-43, 46-52, 56, 59, 61, 64, 65-67, and 69-71 which is similar to the concept of a correlation between the presence of myeloperoxidase in a bodily sample and cardiovascular disease risk that the courts identified as a natural phenomenon in Cleveland Clinic Foundation V. True Health Diagnostics, LLC, 859 F.3d 1352, 1361, 123 USPQ2d 1081, 1087 (Fed. Cir. 2017). As such, claims 36-40, 42-43, 46-52, 56, 59, 61, 66, and 70-71 recite an abstract idea and a natural phenomenon (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to affect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or insignificant extra-solution activity. Specifically, the claims recite the following additional elements:
Claim 36 recites measuring transcript levels of a plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12 of a biological sample from the first subject; obtaining, by one or more computers, molecular data corresponding to the transcript levels of the plurality of biomarkers generating, by the one or more computers, input data that includes a set of features extracted from the obtained molecular data; based on the determined likelihood, generating, by the one or more computers, rendering data that, when rendered by a user device, causes the user device to display data that identifies the determined likelihood; and providing, by the one or more computers, the rendering data to the user device.
Claim 38 recites a method wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to benefit from the immunotherapy.
Claim 39 recites a method wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is not likely to benefit from the immunotherapy.
Claim 40 recites a method wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to have the indeterminate benefit from the immunotherapy.
Claim 42 recites a method wherein the biological sample comprises formalin-fixed paraffin-embedded (FFPE) tissue, fixed tissue, a core needle biopsy, a fine needle aspirate, unstained slides, fresh frozen (FF) tissue, formalin samples, tissue comprised in a solution that preserves nucleic acid or protein molecules, a fresh sample, a malignant fluid, a bodily fluid, a tumor sample, a tissue sample, or any combination thereof.
Claim 43 recites a method wherein the biological sample comprises cells from a solid tumor and/or wherein the biological sample comprises a bodily fluid.
Claim 46 recites a method wherein the bodily fluid comprises peripheral blood, sera, plasma, ascites, or urine.
Claim 47 recites a method wherein assaying the biological sample comprises determining a presence, level, or state of a protein or nucleic acid for each biomarker.
Claim 48 recites a method wherein the nucleic acid comprises cell free nucleic acid.
Claim 49 recites wherein the state of the nucleic acid comprises a sequence, mutation, polymorphism, deletion, insertion, substitution, translocation, fusion, break, duplication, amplification, repeat, copy number, transcript level, or any combination thereof.
Claim 50 recites wherein the state of the nucleic acid comprises a transcript level for all members of the plurality of biomarkers.
Claim 51 wherein assaying the biological sample comprises performing whole transcriptome sequencing (WTS} and wherein the molecular data comprises a transcript level for all members of the plurality of biomarkers obtained via the WTS.
Claim 64 recites the biological sample comprises cancer cells and/or cell free nucleic acid released from cancer cells and assaying the biological sample comprises performing WTS.
Claim 66 recites a method wherein further comprising generating a report displaying the rendering data, wherein the report identifies a likely benefit, lack of benefit or indeterminate benefits of treating the first subject with the immunotherapy.
Claim 70 recites a non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform the method.
Claim 71 recites a system comprising one or more computers and one or more storage media storing instructions that, when executed by the one or more computers, cause the one or more computers to perform each of the method.
Of note, there are no limitations to indicate that the claimed computer, processor, or memory require anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
The limitations of measuring transcript levels of a plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12 of a biological sample from the first subject; obtaining, by one or more computers, molecular data corresponding to the transcript levels of the plurality of biomarkers generating, by the one or more computers, input data that includes a set of features extracted from the obtained molecular data; based on the determined likelihood, generating, by the one or more computers, rendering data that, when rendered by a user device, causes the user device to display data that identifies the determined likelihood; providing, by the one or more computers, the rendering data to the user device; wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to benefit from the immunotherapy; wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is not likely to benefit from the immunotherapy; assaying the biological sample comprises determining a presence, level, or state of a protein or nucleic acid for each biomarker; assaying the biological sample comprises performing whole transcriptome sequencing (WTS} and wherein the molecular data comprises a transcript level for all members of the plurality of biomarkers obtained via the WTS; and generating a report displaying the rendering data, wherein the report identifies a likely benefit, lack of benefit or indeterminate benefits of treating the first subject with the immunotherapy equate to insignificant extra solution activity, namely, mere data gathering. Of note, the courts have ruled in Electric Power Group, LLC V. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) that the collection, analysis, and display of data are considered insignificant extra-solution activity and does not integrate the judicial exception into a practical application (see MPEP 2106.05(g)).
The limitations reciting the biological sample comprises formalin-fixed paraffin-embedded (FFPE) tissue, fixed tissue, a core needle biopsy, a fine needle aspirate, unstained slides, fresh frozen (FF) tissue, formalin samples, tissue comprised in a solution that preserves nucleic acid or protein molecules, a fresh sample, a malignant fluid, a bodily fluid, a tumor sample, a tissue sample, or any combination thereof; the biological sample comprises cells from a solid tumor and/or wherein the biological sample comprises a bodily fluid; the bodily fluid comprises peripheral blood, sera, plasma, ascites, or urine; the nucleic acid comprises cell free nucleic acid; the state of the nucleic acid comprises a sequence, mutation, polymorphism, deletion, insertion, substitution, translocation, fusion, break, duplication, amplification, repeat, copy number, transcript level, or any combination thereof; the state of the nucleic acid comprises a transcript level for all members of the plurality of biomarkers; the biological sample comprises cancer cells and/or cell free nucleic acid released from cancer cells; merely serve to further limit the insignificant data gathering step and does not integrate into a practical application. As such, claims 36-40, 42-43, 46-52, 59, 61, 66, and 70-71 do not integrate the abstract idea into a practical application.
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment. The instant claims recite the following additional elements:
Claim 36 recites measuring transcript levels of a plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12 of a biological sample from the first subject; obtaining, by one or more computers, molecular data corresponding to the transcript levels of the plurality of biomarkers generating, by the one or more computers, input data that includes a set of features extracted from the obtained molecular data; based on the determined likelihood, generating, by the one or more computers, rendering data that, when rendered by a user device, causes the user device to display data that identifies the determined likelihood; and providing, by the one or more computers, the rendering data to the user device.
Claim 38 recites a method wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to benefit from the immunotherapy.
Claim 39 recites a method wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is not likely to benefit from the immunotherapy.
Claim 40 recites a method wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to have the indeterminate benefit from the immunotherapy.
Claim 42 recites a method wherein the biological sample comprises formalin-fixed paraffin-embedded (FFPE) tissue, fixed tissue, a core needle biopsy, a fine needle aspirate, unstained slides, fresh frozen (FF) tissue, formalin samples, tissue comprised in a solution that preserves nucleic acid or protein molecules, a fresh sample, a malignant fluid, a bodily fluid, a tumor sample, a tissue sample, or any combination thereof.
Claim 43 recites a method wherein the biological sample comprises cells from a solid tumor and/or wherein the biological sample comprises a bodily fluid.
Claim 46 recites a method wherein the bodily fluid comprises peripheral blood, sera, plasma, ascites, or urine.
Claim 47 recites a method wherein assaying the biological sample comprises determining a presence, level, or state of a protein or nucleic acid for each biomarker.
Claim 48 recites a method wherein the nucleic acid comprises cell free nucleic acid.
Claim 49 recites wherein the state of the nucleic acid comprises a sequence, mutation, polymorphism, deletion, insertion, substitution, translocation, fusion, break, duplication, amplification, repeat, copy number, transcript level, or any combination thereof.
Claim 50 recites wherein the state of the nucleic acid comprises a transcript level for all members of the plurality of biomarkers.
Claim 51 wherein assaying the biological sample comprises performing whole transcriptome sequencing (WTS} and wherein the molecular data comprises a transcript level for all members of the plurality of biomarkers obtained via the WTS.
Claim 64 recites the biological sample comprises cancer cells and/or cell free nucleic acid released from cancer cells and assaying the biological sample comprises performing WTS.
Claim 66 recites a method wherein further comprising generating a report displaying the rendering data, wherein the report identifies a likely benefit, lack of benefit or indeterminate benefits of treating the first subject with the immunotherapy.
Claim 70 recites a non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform the method.
Claim 71 recites a system comprising one or more computers and one or more storage media storing instructions that, when executed by the one or more computers, cause the one or more computers to perform each of the method.
Of note, there are no additional limitations to indicate that the claimed computer, processor, or memory require anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible (Claims 70-71). Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
The limitations reciting obtaining, by one or more computers, molecular data corresponding to the transcript levels of the plurality of biomarkers generating, by the one or more computers, input data that includes a set of features extracted from the obtained molecular data; based on the determined likelihood, generating, by the one or more computers, rendering data that, when rendered by a user device, causes the user device to display data that identifies the determined likelihood; providing, by the one or more computers, the rendering data to the user device; wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to benefit from the immunotherapy; wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is not likely to benefit from the immunotherapy; assaying the biological sample comprises determining a presence, level, or state of a protein or nucleic acid for each biomarker; assaying the biological sample comprises performing whole transcriptome sequencing (WTS} and wherein the molecular data comprises a transcript level for all members of the plurality of biomarkers obtained via the WTS; and generating a report displaying the rendering data all equate to well-understood, routine and conventional activities. The courts have identified that receiving or transmitting data over a network, or storing and retrieving information in memory are well-understood, routine and conventional computer functions in Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC V. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., V. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. V. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014); and Versata Dev. Group, Inc. V. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
The limitations identifying measuring transcript levels of a plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12 of a biological sample from the first subject amount to well-understood, routine, and conventional activities as evidenced as evidenced by ScienceInsights (see attached document) and Alvandi et al. (see “Background” on page 1). In addition, the specific biomarkers and their related genes can be measured with TaqMan as ThermoFisher already provides a commercially available assay (see https://www.thermofisher.com/taqman/gene-expression/assay/query?keyword=&productType=ge&productSubtype=ge) and allows a user to search by gene name and for if the probes are included with the specified assay.
In addition, the limitations of the identification of the state of proteins or nucleic acids (claims 47 and 49) and biological samples (Claims 42-43 and 46) are all well-understood, routine, and conventional activities within the art as evidenced by Skog et al. (biological samples: gene expression profiling of blood samples or circulating tumor cells is current with publications in 2005 and 2006 and state of nucleic acids and proteins: knowledge of the state of nucleic acids and proteins is helpful for personalized medicine (see [0004]; [0010])).
Furthermore, the limitations of performing whole transcriptome sequencing (Claim 51) is a well-understood, routine and conventional activity as recited by Lin (Identification of latent biomarkers in hepatocellular carcinoma by ultra-deep whole-transcriptome sequencing. Oncogene 33, 4786–4794 (2014).
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, 36-40, 42-43, 46-52, 59, 61, 66, and 70-71 are not patent eligible.
Response to Arguments
Applicant's arguments, see pages 10-13, filed 6/26/2026, with respect to claim 36, has been fully considered but they are not persuasive.
With respect to Applicant’s argument on judicial exceptions regarding claim 36, the Applicant argues that the incorporation of “measuring transcript levels of a plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12of a biological sample from the first subject” as well as the various operations of machine learning models are also additional limitations. The Examiner respectfully disagrees. Although measuring the plurality of biomarkers is an additional element, it does not preclude the other features of the claim from reciting a judicial exception (e.g. determining a likelihood). Additionally, the recitation of a machine learning model without sufficient description of structure (i.e. hidden layers, convolutional layers, activation layers, etc.) does not qualify as an additional element and is merely a verbal equivalent of a mathematical computation which falls under the “mathematical concept” grouping of ideas.
With respect to Applicant’s argument on a practical application regarding claim 36, the Applicant argues that as currently amended, the claimed invention provides a technical improvement on prediction of immunotherapy benefit for a cancer patient by measuring transcript levels of a combination of 7 specific biomarkers: CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12 of a biological sample from the patent. In addition, the Applicant submits that the Examiner allegedly uses circular reasoning by applying the measuring step as insignificant solely because it is characterized as data gathering, and then relies on that characterization itself to conclude that the step is insignificant. The Examiner respectfully disagrees. Measuring transcript levels limited to a combination of biomarkers is merely further limiting and does not integrate the judicial exception into a practical application. In MPEP 2106.05(g), past Office guidance has held that when determining whether an additional element is insignificant extra-solution activity, examiners should consider: 3) Whether the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). Examples that the courts have found to be insignificant data gathering explicitly includes: vi. Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis). Furthermore, in MPEP 2106.05(h), the courts have held that a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) is considered to be both insignificant extra-solution activity and a field of use limitation. See, e.g., Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (limiting use of abstract idea to the Internet); Electric Power, 830 F.3d at 1354, 119 USPQ2d at 1742 (limiting application of abstract idea to power grid data); Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d 1315, 1328-29, 121 USPQ2d 1928, 1939 (Fed. Cir. 2017) (limiting use of abstract idea to use with XML tags). In addition, the assertation that the improved prediction of immunotherapy response being the improvement to the claimed invention is part of the judicial exceptions recited in the claim and MPEP 2106.05(a) indicates that the improvement cannot be in the judicial exception itself. Rather, the improvement can be provided by the one or more additional elements either alone or in combination with the judicial exception. However, there is no indication that the measuring process is improved or altered by the judicial exception. Therefore, the claims are not directed to eligible subject matter (Step 2A Prong 2).
The Applicant asserts that with respect to the third factor in the test under MPEP 2106.05(g)(3), the limitation does not amount to necessary data gathering and outputting. The Examiner respectfully disagrees. Applicant argues that all applications of the judicial exception do not require transcript levels for the specific seven-biomarker combination (e.g. Fig. 2C and Tables 2-8). However, as aforementioned, Applicant also argues in the next paragraph that the recited measurement of transcript levels for the specific seven-biomarker combination materially contributes to the claimed practical application and thus those particular genes are necessary for the improvement. Therefore, the asserted improvement is not commensurate of the claim because the claim encompasses applications that do not require transcript levels, while the asserted improvement appears to depend on features associated with transcript levels.
With respect to Applicant’s argument on conventionality regarding claim 36, the Applicant submits that "measuring transcript levels of a plurality of biomarkers comprising CD274, CD8A, PDCD], CD28, DDR2, STK11, and CDK12 of a biological sample from the first subject" is unconventional as paragraph [0219] merely refers to a low density assay such as a TaqManTM existing and does not indicate that such an assay for analyzing the specific 7 biomarkers is commercially available and paragraph [0219] of W02018175501 does not mention the specific panel including the 7 biomarkers: CD274, CD8A, PDCD1, CD28, DDR2, STK1 1, and CDK12. The Examiner respectfully disagrees. TaqMan Assays are the gold standard as it allows for the precise quantification of the starting genetic material and has advantages in specificity and flexibility compared to other methods as evidenced by ScienceInsights (see attached document) and Alvandi et al. (see “Background” on page 1). In addition, the specific biomarkers and their related genes can be measured with TaqMan as ThermoFisher already provides a commercially available assay (see https://www.thermofisher.com/taqman/gene-expression/assay/query?keyword=&productType=ge&productSubtype=ge) and allows a user to search by gene name and for if the probes are included with the specified assay. Therefore, as the Applicant has submitted, that the TaqMan assay had existed prior to the time of the application and it serves as the gold standard for many genetic material quantification pipelines, the insignificant data gathering step is well-understood, routine, and conventional in the art.
Applicant's arguments, see page 11, filed 6/26/2026, with respect to claims 56, 67, and 69, has been fully considered and are persuasive.
The Applicant has amended claims 56, 67, and 69 to overcome the broadest reasonable interpretation of contingent claims. According to MPEP 2106.04(d)(2), “treatment” and prophylaxis” limitations encompass limitations that treat or prevent a disease or medical condition, including, e.g., acupuncture, administration of medication, dialysis, organ transplants, phototherapy, physiotherapy, radiation therapy, surgery, and the like. As such, the limitations reciting the rendering data indicates the first subject is likely to benefit from the immunotherapy, the method further comprising administering the immunotherapy to the first subject; the report identifies the likely benefit of treating the first subject with immunotherapy, the method further comprising administering the immunotherapy to the first subject; a method wherein the report identifies the lack of benefit or indeterminate benefit of treatment the first subject with the immunotherapy, the method further comprising administering chemotherapy to the first subject are particular treatments as the administration of immunotherapy or chemotherapy are meant to treat patients based on biomarker data and thus integrate the abstract idea into a practical application.
Claim Rejections - 35 USC § 102
Response to Arguments
Applicant's arguments, see pages 14-15, filed 6/26/2026, with respect to claim 36, has been fully considered and is persuasive. Therefore, the rejection has been withdrawn. However, after further consideration, a new ground of rejection has been made in view of Bagaev and Skog et al. as necessitated by amendment.
Claim Rejections - 35 USC § 103
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.
The present rejection(s) reference specific passages from cited prior art. However,
Applicant is advised that the rejections are based on the entirety of each cited prior art. That is,
each cited prior art reference “must be considered in its entirety”. (See MPEP 2141.02(VI))
Therefore, Applicant is advised to review all portions of the cited prior art if traversing a
rejection based on the cited prior art.
Claim(s) 36-40, 42-43, 46-52, 56, 59, 61, 64, 66-67, and 69-71 is/are rejected under 35 U.S.C. 103 as unpatentable over Bagaev et al. (WO2018231762A1) in view of Morrison et al. (US 20180107786 A1).
Regarding claim 36, Bagaev teaches:
A method for predicting benefit of immunotherapy for a cancer in a first subject, the method comprising (techniques for analysis of data to determine whether treatments like immunotherapies are effective, page 17, lines 13-19):
obtaining, by one or more computers, molecular data corresponding to the transcript levels of the plurality of biomarkers (computer hardware processor obtains sequencing data corresponding to biomarker information, page 4, lines 18-30)
generating, by the one or more computers, input data that includes a set of features extracted from the obtained molecular data (sequencing data and biomarker information are used to determine a normalized score as input data, page 4, lines 18-30);
providing, by the one or more computers, the generated input data as input to a predictive model, the predictive model comprising at least one machine learning model, wherein each particular machine learning model of the at least one machine learning model is trained to generate output data that indicates whether a subject is likely to benefit from an immunotherapy based on the particular machine learning model processing of the set of features extracted from molecular data corresponding to transcript levels to the plurality of biomarkers (specifics of the input data calculation described as normalized biomarker data functions as input data to be fed a statistical model that can include a neural network model on page 38, line 27-35; page 39, lines 1-6)
processing, by the one or more computers the generated input data through the at least one machine learning model, to generate first data indicating whether the first subject is likely to benefit from the immunotherapy (subsequently, after processed by neural network, the scores are used as a predictive measure of a patient’s response to therapy on page 38, line 27-35; page 39, lines 1-6);
determining, by the one or more computers and based on the generated first data, a likelihood that the first subject is to benefit from the immunotherapy; based on the determined likelihood (generated therapy scores are indicative of the predicted response of the subject to the administration of therapy, page 3, lines 30-35; page 4, lines 1-2),
generating, by the one or more computers, rendering data that, when rendered by a user device, causes the user device to display data that identifies the determined likelihood; and providing, by one or more computers, the rendering data to the user device (presentation of data seen in figures 6A and 6B which can be displayed on computing device 112 such as a smartphone, desktop computer, etc.).
Bagaev does not explicitly teach measuring transcript levels of a plurality of biomarkers comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12 of a biological sample from the first subject and subsequent steps comprising CD274, CD8A, PDCD1, CD28, DDR2, STK11, and CDK12. Morrison teaches a method for determining the presence or absence of cancer cell sensitivity to one or more personalized oncology therapies using a combination of biomarkers. (explicitly recited in [0003]-[0006] and throughout disclosure for predicting response to immune checkpoint blocker based immunotherapies; see [0016] for the method of tumor analysis where a quantitative assessment of expression levels of at least four genes in a sample is described for subsequent tumor infiltrating lymphocytes (TILs) in [0032]; TIL analysis is integrated into the 54 gene model (see [0039]-[0044]; [0066]) which includes all of the listed biomarkers in Table 2 (see [0072]-[0074]); see also Fig. 10 where a report is produced comprising a patient’s tumor microenvironment in response to immunotherapy). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Morrison’s specific biomarker assaying into Bagaev’s existing pipeline as to address the need for a more profound deconvolution of the immunological tumor microenvironment as an in-depth characterization of the immunological configuration of malignancies may be necessary to assist clinical decision making, especially for patients that fail standard ICB-based immunotherapy (see [0003]). This incorporation could have been accomplished with reasonable expectation of success as both inventions operate in the same field of endeavor of cancer or disease research. The Examiner notes that after obtaining data from the specific biomarkers, the steps of the claimed invention would be performed on data limited to those biomarkers.
Regarding claim 37, Bagaev as modified teaches:
A method, wherein determining, by the one or more computers and based on the generated first data, the likelihood that the first subject is to benefit from the immunotherapy includes calculating a probability (Bayesian regression model is used to compute for a therapy score which is indicative of a patient’s response to therapy on page 38, line 27-35; page 39, lines 1-6). The Examiner notes that if a Bayesian regression model can be employed as stated above, it inherently makes use of probability values and therefore the output may be a probability indicative of a patient’s predicted response to therapy.
Regarding claim 38, Bagaev as modified teaches:
A method further comprising: determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data satisfies one of the one or more thresholds, determining that the first subject is likely to benefit from the immunotherapy (patient is recommended a number of therapies based on a threshold number of top-ranked therapies for the patient, page 93, lines 1-3), wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to benefit from the immunotherapy (impact scores are indicative of positive or negative response to therapy displayed with presentation of data seen in Figs. 6A and 6B in computing device 112; page 40, lines 32; page 41, lines 1-6; page 41, lines 12-13).
Regarding claim 39, Bagaev as modified teaches:
A method further comprising: determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data satisfies one of the one or more thresholds, determining that the first subject is likely to benefit from the immunotherapy, wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to benefit from the immunotherapy (see citations above, but impact scores may be either a positive or negative response, page 41, lines 12-13).
Regarding claim 40, Bagaev as modified teaches:
A method further comprising: determining, by the one or more computers, whether the first data satisfies one or more thresholds; and based on a determination that the first data is (i) equal to one of the one or more thresholds or (ii) satisfies two of the one or more thresholds, determining that the first subject is likely to have an indeterminate benefit from the immunotherapy (Therapy response rate predictions with thresholding cut-offs for various therapies shown, page 78; lines 14-28, see Table 3), wherein generating, by the one or more computers, the rendering data that, when rendered by the user device, causes the user device to display data that identifies the determined likelihood comprises: generating, by the one or more computers, rendering data that, when rendered, causes the user device to display data that indicates that the first subject is likely to have the indeterminate benefit from the immunotherapy (user device same as in claim 38, but Fig. 7C depicts therapy cores where patients are separated into progressive disease (negative), stable disease (positive), and partial response (indeterminate)).
Regarding claim 42, Bagaev as modified teaches:
A method wherein the biological sample comprises formalin-fixed paraffin-embedded (FFPE) tissue, fixed tissue, a core needle biopsy, a fine needle aspirate, unstained slides, fresh frozen (FF) tissue, formalin samples, tissue comprised in a solution that preserves nucleic acid or protein molecules, a fresh sample, a malignant fluid, a bodily fluid, a tumor sample, a tissue sample, or any combination thereof (All options of biological sample specified, pages 30-31).
Regarding claim 43, Bagaev as modified teaches:
A method wherein the biological sample comprises cells from a solid tumor and/or wherein the biological sample comprises a bodily fluid (see claim 42, pages 30-31).
Regarding claim 46, Bagaev as modified teaches:
A method wherein the bodily fluid comprises peripheral blood, sera, plasma, ascites, or urine (see claim 42, pages 30-31).
Regarding claim 47, Bagaev as modified teaches:
A method wherein assaying the biological sample comprises determining a presence, level, or state of a protein or nucleic acid for each biomarker (expression biomarkers from biological sample are analyzed via enzymatic activity of the nucleic acid or protein, page 95).
Regarding claim 48, Bagaev as modified teaches:
A method wherein the nucleic acid comprises cell free nucleic acid (expression biomarkers from biological sample are analyzed via enzymatic activity of the nucleic acid or protein wherein nucleic acid is obtained from the biological sample which is obtained from plasma, page 95). The Examiner notes that the biological sample is obtained from plasma which inherently contains circulating cell-free nucleic acids released from apoptotic and necrotic cells. Therefore, nucleic acids isolated from plasma necessarily comprise cell-free nucleic acids, even if not explicitly stated. (See MPEP 2112).
Regarding claim 49, Bagaev as modified teaches:
A method wherein the state of the nucleic acid comprises a sequence, mutation, polymorphism, deletion, insertion, substitution, translocation, fusion, break, duplication, amplification, repeat, copy number, transcript level, or any combination thereof (description of a genetic biomarker on page 20). The Examiner notes that although the prior art discloses the limitations of the claim as a “genetic biomarker”, it also mentions any product thereof such as RNA and proteins along with subsequent state changes such as mutations or deletions. Because RNA is a nucleic acid, the limitations of the claim are substantially anticipated by Bagaev.
Regarding claim 50, Bagaev as modified teaches:
A method wherein the state of the nucleic acid comprises a transcript level for all members of the plurality of biomarkers (Sequencing data provided can be RNA-sequencing data; page 31, lines 33-34; page 32, lines 1-12). The Examiner notes that RNA-seq inherently provides transcript levels for one or more biomarkers.
Regarding claim 51, Bagaev as modified teaches:
A method wherein assaying the biological sample comprises performing whole transcriptome sequencing (WTS} and wherein the molecular data comprises a transcript level for all members of the plurality of biomarkers obtained via the WTS (RNA expression data can be acquired via whole transcriptome sequencing for a plurality of genes originating from a sample; page 33, lines 2-23).
Regarding claim 52, Bagaev as modified teaches:
A method wherein the immunotherapy comprises an immune checkpoint therapy (anti-cancer therapeutic agent is an immunotherapy where proteins are blocked with a variety of different drugs (i.e. checkpoint therapy; page 60, lines 11-20); additional details on the nature of protein selection can be found on page 35; lines 6-19).
Regarding claim 56, Bagaev as modified teaches:
The method of claim 36, wherein the rendering data indicates the first subject is likely to benefit from the immunotherapy, the method further comprising administering the immunotherapy to the first subject (page 59; lines 24-28; where an effective amount of anti-cancer therapy is administered or recommended for administration to a subject in need of the treatment based on user device in claim Fig. 7C which depicts therapy cores where patients are separated into progressive disease (negative), stable disease (positive), and partial response (indeterminate); see also page 54 lines 3-5 for additional evidence of particular therapies being administered based on patient’s predicted response to that therapy using the patient’s biomarkers).
Regarding claim 59, Bagaev as modified teaches:
A method wherein the cancer comprises a lung bronchioloalveolar carcinoma (BAC), non-small cell lung cancer (NSCLC), or lung small cell cancer (SCLC) (lung cancer disclosed; page 59, lines 29-33).
Regarding claim 61, Bagaev as modified teaches:
A method wherein the at least one machine learning model comprises one or more of a random forest, support vector machine (SVM), logistic regression, K-nearest neighbor, artificial neural network, naive Bayes, quadratic discriminant analysis, Gaussian processes models, decision tree, or a combination thereof (see claim 36; neural network disclosed on page 38, line 27-35; page 39, lines 1-6).
Regarding claim 64, Bagaev as modified teaches:
A method wherein the plurality of biomarkers consists the biological sample comprises cancer cells and/or cell free nucleic acid released from cancer cells (All options of biological sample specified, pages 30-31); assaying the biological sample comprises performing WTS (RNA expression data can be acquired via whole transcriptome sequencing for a plurality of genes originating from a sample; page 33, lines 2-23) and the at least one machine learning model consists of a support vector machine (support vector regression model is used to compute for a therapy score which is indicative of a patient’s response to therapy on page 38, line 27-35; page 39, lines 1-6).
Regarding claim 66, Bagaev as modified teaches:
A method wherein further comprising generating a report displaying the rendering data, wherein the report identifies a likely benefit, lack of benefit or indeterminate benefits of treating the first subject with the immunotherapy (impact scores are indicative of positive or negative response to therapy displayed with presentation of data seen in Figs. 6A and 6B in computing device 112; page 40, lines 32; page 41, lines 1-6; page 41, lines 12-13).
Regarding claim 67, Bagaev as modified teaches:
The method of claim 66, wherein the report identifies the likely benefit of treating the first subject with the immunotherapy, the method further comprising administering the immunotherapy to the first subject (page 59; lines 24-28; where an effective amount of anti-cancer therapy is administered or recommended for administration to a subject in need of the treatment based on user device in claim Fig. 7C which depicts therapy cores where patients are separated into progressive disease (negative), stable disease (positive), and partial response (indeterminate); see also page 54 lines 3-5 for additional evidence of particular therapies being administered based on patient’s predicted response to that therapy using the patient’s biomarkers).
Regarding claim 69, Bagaev as modified teaches:
A method wherein report identifies the likely lack of benefit or indeterminate benefit of treatment the first subject with the immunotherapy, the method further comprising administering chemotherapy to the first subject (page 59; lines 24-28; where an effective amount of anti-cancer therapy is administered or recommended for administration to a subject in need of the treatment based on user device in claim Fig. 7C which depicts therapy cores where patients are separated into progressive disease (negative), stable disease (positive), and partial response (indeterminate); see also page 54 lines 3-5 for additional evidence of particular therapies being administered based on patient’s predicted response to that therapy using the patient’s biomarkers; see also last paragraph of page 106 for chemotherapy in the group of various therapies administered).
Regarding claim 70, Bagaev as modified teaches:
A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform the method (page 3, lines 21-35; page 4, lines 1-2).
Regarding claim 71, Bagaev as modified teaches:
A system comprising one or more computers and one or more storage media storing instructions that, when executed by the one or more computers, cause the one or more computers to perform each of the method (page 3, lines 21-35; page 4, lines 1-2).
Response to Arguments
Applicant's arguments, see pages 14-15, filed 6/26/2026, with respect to claim 36, has been fully considered and is persuasive. Therefore, the rejection has been withdrawn. However, after further consideration, a new ground of rejection has been made in view of Bagaev and Morrison et al. as necessitated by amendment.
Conclusion
No claims currently allowed.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Grimes et al. (US 20070254369) discloses a method and apparatus for identifying disease status using biomarkers. Jain et al. (US 11056242 B1) discloses predictive analysis and interventions to limit disease exposure.
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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/P.N./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
Prosecution Insights