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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 07/17/2026 has been entered.
Response to Amendments
Claim amendments have not overcome the 35 USC 101 rejections.
Response to Arguments
Applicant's arguments pertaining to the 35 USC § 101 have been fully considered but they are not persuasive. On page 9 of Applicant’s remarks, Applicant argues that:
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Examiner agrees that limitations “performing image analysis [[ on ]]by applying an artificial neural network” are non-judicial exception additional elements that cannot be interpreted as being performed in the human mind.
In the subsequent paragraph, Applicant argues that:
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Examiner respectfully disagrees. Firstly, the claim does not recite “pixel-level segmentation” or even “segmentation” or “counting” or “clinical classification”. Applicant’s characterizations, in these regards, are not commensurate with the claim scope, and so are moot points. Recall that claim limitations are given their broadest reasonable interpretation without reading limitations from the specification into the claims. However, even considering the original disclosure, the specification does not disclose “pixel-level segmentation” or an artificial neural network performing counting; thus, these limitations are not available for amending into the claims. Also note that the claim does not recite, “quantify”. However, the limitations “obtain image analysis results indicating CD8+ T-cell abundance in tumor parenchyma
and stroma in the histology image” can be reasonably be interpreted as a human observer, such as a pathologist or topologist, viewing a displayed histology image and visually observing differential staining of the tumor stroma and parenchyma and mentally indicating CD8+ T-cell abundance via visual perception of CD8+ T-cell density present within the stroma and parenchyma. Note that the claim does not require an interpretation of counting, but a human can visually count individual cells present in a displayed image. Never-the-less, “abundance”, as claimed is a high-level metric that does not require an interpretation of counting. Also, note that even if the claim generically recited “segmentation”, which it does not, that pathologists often mentally perform segmentation of tumor stroma and parenchyma, via visual perception, by view displayed stained histology images.
In the second paragraph on page 10 of Applicant’s remarks, Applicant argues that:
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Examiner agrees that these limitations cannot be interpreted as mental processes. However, these limitations are recited math abstract ideas.
In the subsequent paragraph, Applicant argues that:
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Examiner respectfully disagrees. “Polar coordinate transformations” are explicitly recited mathematical operations. They are mathematical transformations that transform data from another coordinate space (e.g. cartesian coordinate space) to polar coordinates. This is a mathematical relationship and calculation. Applicant refers to Example 39, but “training a neural network” is not recited math. Example 39 is not analogous to Applicant’s claim 61. Example 39 does not recite any judicial exceptions.
In the last paragraph on page 10 of Applicant’s remarks, Applicant argues that:
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Examiner respectfully disagrees. Claim 61 is comprised primarily of mental and recited math abstract ideas. The only non-judicial exception additional elements present in the claim are the computer component limitations, the insignificant extra-solution activity data gathering limitations, and the generically recited artificial neural network image analysis limitations. The limitations, “generating a recommendation for a treatment option”, themselves, can be reasonably interpreted as being mentally performed by a human observer, such as a pathologist, topologist, or physician, visually perceiving relevant plotted data in the feature coordinate space in conjunction with visually perceiving the lines through the coordinate space marking linear boundaries or linear cutoffs and mentally determining a suitable recommendation for a treatment option. The claims do not require an alternative interpretation and do not prohibit this interpretation. Note that judicial exceptions cannot incorporate judicial exceptions into a practical application or constitute significantly more than the judicial exceptions.
Beginning atop page 11 of Applicant’s remarks, Applicant argues that:
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Examiner respectfully disagrees. These excerpts indicate that humans can indeed perform these operations, which confirms the interpretation that the limitations “obtain image analysis results indicating CD8+ T-cell abundance in tumor parenchyma and stroma in the histology image” can be reasonably be interpreted as a human observer, such as a pathologist or topologist, viewing a displayed histology image and visually observing differential staining of the tumor stroma and parenchyma and mentally indicating CD8+ T-cell abundance via visual perception of CD8+ T-cell density present within the stroma and parenchyma. These excerpts explain why “performing image analysis by applying an artificial neural network” is an improvement on manual interpretation due to significant inter-reviewer variability. Thus, “performing image analysis by applying an artificial neural network to the histology image” is solving a problem but is recited at a high level of generality, i.e. generically recited, and thus cannot incorporate the mental process abstract idea of visual perception into a practical application. Also, “performing image analysis by applying an artificial neural network to the histology image” is well-understood, routine, conventional. These excerpts also state that the patient response model is an improvement or solution. However, the patient response model is recited math abstract idea judicial exception, and judicial exceptions cannot incorporate judicial exceptions into a practical application or constitute significantly more than the judicial exceptions.
Subsequently, in the third and fourth paragraphs on page 11 of Applicant’s remarks, Applicant argues that:
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Examiner respectfully disagrees. Here, the Desjardin memo is referring to the additional elements or ordered combination of additional elements or the ordered combination of additional elements as affected by and affecting the judicial exceptions. The broadest reasonable interpretation of the claims was carefully ascertained prior to the subject matter eligibility analysis. The interpretations were carefully explained in the rejection below and response to arguments above. See the paragraphs above concerning improvements or solutions.
On page 12 of Applicant’s remarks, Applicant argues that:
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Examiner respectfully disagrees. Let us carefully consider the referenced portion on page 4 of the August 4, 2025 Memo. The sentence here is, “An important consideration in determining whether a claim improves technology or a technical field is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome”. “performing image analysis by applying an artificial neural network to the histology image” is not a particular solution. These limitations are generically recited. Applicant refers to Claim 3 of Example 47. Let us carefully consider this example. Here is the synopsis for claims 1-3:
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Note that “Claim 2 is ineligible because it recites a judicial exception (abstract idea), and the claim as a whole does not integrate the exception into a practical application (and is thus directed to an abstract idea), and the claim does not provide significantly more than the exception (does not provide an inventive concept”.
Here is that claim 2:
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Example 47’s Claim 2 better matches the fact patterns of Applicant’s claim 61 than Example 47’s claim 3. See that that detection and analysis of anomalies is performed using the ANN and results of this analysis are output. Page 6 of the July 2024 Subject Matter Eligibility Examples explains:
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Page 7 of the July 2024 Subject Matter Eligibility Examples explains:
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The last paragraph on page 8 to the fifth paragraph on page 9 of the July 2024 Subject Matter Eligibility Examples explains:
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Page 10 of the July 2024 Subject Matter Eligibility Examples explains:
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Example 47 claim 2 matches the fact patterns of Applicant’s claim 61 because it involves performing detection and analysis using an ANN to perform actions disclosed as being mentally performed by humans. Analogous analysis is performed on claim 61. The key take away here is that, although an ANN is an additional element, it is a generic recitation for all the reasons provided above in the explanation of this example.
Regarding claim 3 of Example 47, “detecting source addresses, dropping malicious packets, blocking future traffic” are not generically recited. Here are the limitations in question:
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These limitations are clearly additional elements that are not judicial exceptions such as mental process or recited math abstract ideas. Also, these limitations are particularly recited. This is not analogous to Applicant’s claim 61.
Returning to our consideration of Ex Parte Desjardins, indeed Desjardins’ claims reflected improvements
to how a machine learning model itself operate. Considering the December 5, 2025 MEMORANDUM Advance notice of change to the MPEP in light of Ex Parte Desjardins, page 2 of the memo states:
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See that the claim limitations “adjust the first values of the plurality of parameters to optimize performance of the machine learning model on the second machine learning task while protecting performance of the machine learning model on the first machine learning task” are clearly non-judicial exception additional elements that are not mental process or recited math abstract ideas that are particularly recited and constitute an improvement or solution. The analysis for these limitations is not analogous to that of Applicant’s claim 61.
Also, returning to discussion of limitations “obtain image analysis results indicating CD8+ T-cell abundance in tumor parenchyma and stroma in the histology image” being reasonably interpretable as a human observer, such as a pathologist or topologist, viewing a displayed histology image and visually observing differential staining of the tumor stroma and parenchyma and mentally indicating CD8+ T-cell abundance via visual perception of CD8+ T-cell density present within the stroma and parenchyma, let us carefully consider Shimizu S, Hiratsuka H, Koike K, Tsuchihashi K, Sonoda T, Ogi K, Miyakawa A, Kobayashi J, Kaneko T, Igarashi T, Hasegawa T, Miyazaki A. Tumor-infiltrating CD8+ T-cell density is an independent prognostic marker for oral squamous cell carcinoma. Cancer Med. 2019 Jan;8(1):80-93. doi: 10.1002/cam4.1889. Epub 2019 Jan 1. PMID: 30600646; PMCID: PMC6346233 (Shimizu) provided by Applicant in information disclosure statement (IDS) filed 04/20/2026:
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Associated page 84 shows:
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These portions show that “obtain image analysis results indicating CD8+ T-cell abundance in tumor parenchyma and stroma in the histology image” can be mentally performed where cells are manually counted in determining density as abundance. These teachings of Shimizu are not necessary for the 35 USC 101 rejection, but are meant to be supplemental to further elucidate the point.
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 61-70 and 73-82 are rejected under 35 U.S.C. 101 because the claimed invention is directed to recited math and mental process abstract ideas without significantly more.
Claim(s) 61 recite(s):
“method for identifying a subject suitable for immunotherapy to treat a tumor of the subject”, which can be reasonably interpreted as being mentally performed by a human observer considering relevant data.
“obtain image analysis results indicating CD8+ T-cell abundance in tumor parenchyma and stroma in the histology image”, which can be reasonably be interpreted as a human observer, such as a pathologist or topologist, viewing a displayed histology image and visually observing differential staining of the tumor stroma and parenchyma and mentally indicating CD8+ T-cell abundance via visual perception of CD8+ T-cell density present within the stroma and parenchyma;
“processing a polar coordinate transformation of the image analysis results indicating the CD8+ T-cell abundance in tumor parenchyma and stroma to determine: a real inflammation score of the sample of the tumor; and a tumor infiltration score of the sample of the tumor”, which is recited math of polar coordinate transformation of coordinates to calculate a real inflammation score and a tumor infiltration score;
“determining, from a plurality of possible classifications of CD8 localization, a classification of CD8 localization in the sample of the tumor”, which can be reasonably interpreted as being mentally performed by a human observer visually perceiving relevant plotted data;
“by applying a patient response model to the polar coordinate transformation of the image analysis results that maps a value of the real inflammation score and a value of the tumor infiltration score in a feature space, the feature space comprising a plot having a first axis and a second axis and defining linear boundaries or linear cutoffs between the plurality of possible classifications of CD8 localization, wherein the linear boundaries or linear cutoffs are identified by iteratively fitting boundary defining values for the real inflammation score and the tumor infiltration score in the feature space based on patient response data”, which is recited math of applying a mathematical model, such as regression, in transforming the result of the polar coordinate transformation into a feature coordinate space with axes of real inflammation and tumor infiltration and calculated lines through the coordinate space marking linear boundaries or linear cutoffs; and
“generating a recommendation for a treatment option of the subject based on the classification of the CD8 localization in the sample of the tumor”, which can be reasonably interpreted as being mentally performed by a human observer visually perceiving relevant plotted data in the feature coordinate space in conjunction with visually perceiving the lines through the coordinate space marking linear boundaries or linear cutoffs.
This judicial exception is not integrated into a practical application because additional elements of:
“A computer-implemented method… the method executing on data processing hardware that causes the data processing hardware to perform operations comprising” are generically recited computer elements that do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer; and
“receiving a histology image of a sample of the tumor of the subject” are generically recited insignificant extra-solution activity of data gathering;
“performing image analysis by applying an artificial neural network to the histology image to obtain image analysis results” are generically recited;
“comprising retrospective clinical response data indicating whether or not each patient in a plurality of patients is responsive to a treatment or therapy” are generically recited insignificant extra-solution activity of data gathering;
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because additional elements of:
“A computer-implemented method… the method executing on data processing hardware that causes the data processing hardware to perform operations comprising” are mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f);
“receiving a histology image of a sample of the tumor of the subject” are insignificant extra-solution activity of data gathering;
“performing image analysis by applying an artificial neural network to the histology image to obtain image analysis results” are well understood, routine, conventional; and
“comprising retrospective clinical response data indicating whether or not each patient in a plurality of patients is responsive to a treatment or therapy” are insignificant extra-solution activity of data gathering;
Depending claims 62-72 do not remedy these deficiencies:
Claims 62-65 further recite limitations pertaining to mental process abstract idea of a human observer visually perceiving relevant plotted data in the feature coordinate space in conjunction with visually perceiving the lines through the coordinate space marking linear boundaries or linear cutoffs.
Claims 66, 69, and70 further recite limitations pertaining to recited math abstract ideas and insignificant extra-solution activity of data outputting additional elements.
Claims 67 further recites limitations pertaining to recited math abstract ideas.
Claim 68 further recites limitations pertaining to recited math abstract ideas and insignificant extra-solution activity of data gathering additional elements.
As per claim(s) 73-82, arguments made in rejecting claim(s) 61-70 are analogous, respectively. Claims 73-82 further recite, “A system comprising: data processing hardware; and memory hardware in communication with the data processing hardware and storing instructions that when executed on the data processing hardware causes the data processing hardware to perform operations”, which are additional elements that area generically recited computer elements that do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer and are mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Allowable Subject Matter
Claims 61-70 and 73-82 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter: The closest prior art is US 20210098082 A1 (Udyavar). Limitations pertaining to “determining, from a plurality of possible classifications of CD8 localization, a classification of CD8 localization in the sample of the tumor by applying a patient response model to the polar coordinate transformation of the image analysis results that maps a value of the real inflammation score and a value of the tumor infiltration score in a feature space, the feature space comprising a plot having a first axis and a second axis and defining linear boundaries or linear cutoffs between the plurality of possible classifications of CD8 localization”, in conjunction with other limitations present in the independent claim(s), distinguish over the prior art.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Atiba Fitzpatrick whose telephone number is (571) 270-5255. The examiner can normally be reached on M-F 10:00am-6pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Bee can be reached on (571) 270-5183. The fax phone number for Atiba Fitzpatrick is (571) 270-6255.
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Atiba Fitzpatrick
/ATIBA O FITZPATRICK/
Primary Examiner, Art Unit 2677
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