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 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, 91, and 187 are pending.
Claims 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, 91, and 187 are rejected.
Claims 9-10, 12-13, 16-20, 24-25, 27-29, 31-73, 75-77, 79-90, 92-186, and 188-224 are canceled.
No claims are allowed, new, or withdrawn.
Claims 1, 91, and 187 are independent.
Claims 3, 5, 6, 14-15, 21-23, 26, 30, 74, 78 are amended.
Office Action Outline
Rejections
Abbreviations
x
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/d
IDS
Information Disclosure Statement
x, x
102, 103
JE
Judicial Exception
x
101 JE(s)
112/a
35 USC 112(a) and similarly for 112/b, etc.
101 Other
N:N
page:line
Double Patenting
MM/DD/YYYY
date format
Priority
As detailed in the 04/19/2021 filing receipt, this application is a 371 of PCT/US2022/025438, filed 04/19/2022, which claims priority to Provisional 63/239,287, filed 08/31/2021; Provisional 63/188,963, filed 05/14/2021; and Provisional 63/176,826, filed 04/19/2021. At this point in examination, all claims have been interpreted as being accorded the priority date of 04/19/2021.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Instant claim limitations interpreted as PROPERLY invoking 112(f)
The following claim limitation are interpreted as invoking 112(f):
• The "tissue phenotype classification model" configured to classify, recited in claims 1 and 187, recites means and function (an equivalent, nonce term, here a "model", and function, here "to classify image patches") without reciting steps or structure to prevent invoking. The Specification does disclose sufficient structure, material, or acts and not just desired results, as exemplified at least at [0011-0016] and [0028-0033] and as such, is definite under 112/b as properly invoking 112/f. MPEP 2181.III-IV pertain.
• The "gene alteration state classification model" configured to determine, recited in claims 1, 2, and 187, recites means and function (an equivalent, nonce term, here a "model", and function, here "to determine a gene alteration state") without reciting steps or structure to prevent invoking. The Specification does disclose sufficient structure, material, or acts and not just desired results, as exemplified at least at [0018, 0022, 0034, 0038, 0135-0136] and as such, is definite under 112/b as properly invoking 112/f. MPEP 2181.III-IV pertain.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Instant claim limitations interpreted as NOT invoking 112(f)
The following limitations are interpreted as not invoking 112(f):
• The "tissue phenotype classification model configured to classify image patches," recited in claim 91 recites means (or an equivalent, nonce term, here a "model") and function and/or result (here "classify image patches"), but the recitation does not invoke 112/f because the claim is interpreted as reciting sufficient acts not to invoke. MPEP 2181.I.C pertains.
Claim Rejections - 35 USC § 112
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.
Claims 4, 21, and 23 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. Claims depending from rejected claims are rejected similarly, unless otherwise noted, and any amendments in response to the following rejections should be applied throughout the claims, as appropriate.
The following recitations of claims 4, 21, and 23, listed below, require but lack clear antecedent. If the recitations refer to previously instantiated instances, then it is not clear which instances those are. If the recitations instantiate the claim elements, this is not clear.
• "the same tissue type" (recited in claim 4)
• "the presence or absence" (recited in claim 21)
• "the mutation" (recited in claim 23)
These rejections might be overcome by, for example, amending "the" to "a" from the limitation lacking clear antecedent.
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 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, 91, and 187 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), 2106.04(a)(2), and 2106.04(b))
• 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 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, 91, and 187 are directed to 101 processes, here related methods, which fall under a category of statutory subject matter. (See MPEP § 2106.03). (Step 1: Yes.)
Step 2A, Prong One:
The claims are found to recite a judicial exceptions (JE) of abstract ideas in the form of mental processes and mathematical concepts, as well as a law of nature, as follows:
The independent claims recite mental processes (and mathematical concepts where noted) as follows:
• classifying image patches from pathology images of a tissue sample to generate a labeled data set (claims 1, 91, and 187)
• inputting the dataset into a gene alteration state classification model to determine a gene alteration state (claims 1 and 187)
• extracting image features from the image patches (claim 91)
• clustering the image patches based on the extracted features (claim 91) (also considered a mathematical concept)
• labeling the image patches based on an image patch cluster (claim 91)
• determining a disease type of the disease of the individual based on the gene alteration state (claim 187)
• determining a therapy for treating the disease (claim 187)
The dependent claims recite mental processes (and mathematical concepts where noted) as follows:
• training the tissue phenotype classification model using tissue phenotype classification model training image patches (claim 3) (also considered a mathematical concept)
• labeling image patches with a tissue phenotype class selected from tissue phenotype classes (claim 3)
• manually labeling the image patches (claim 5)
• labeling the image patches by clustering comprising extracting features from the patches (claim 6) (also considered a mathematical concept)
• assigning labels based on extracted image feature clusters (claim 7; also considered a mathematical concept)
• extracting the image features from the image patches using a pre-trained image feature extraction model (claim 8; also considered a mathematical concept)
• extracting the image features from the image patches using an unsupervised image feature extraction model (claim 11; also considered a mathematical concept)
• performing a dimensionality reduction on the extracted image features (claim 14; also considered a mathematical concept)
•training the gene alteration state classification model using gene alteration state classification model patches labeled with a tissue phenotype and a gene alteration state (claim 15) (also considered a mathematical concept)
• determining a gene alteration state of a gene of interest in an individual with cancer's tissue sample (claim 74)
•selecting a treatment based on the state (claim 74 and 78)
• Claims 2 and 21-23 further limit the abstract gene alteration state classification model of claim 1.
• Claim 26 further limits the abstract labeling of image patches with a tissue phenotype class of claim 3 to being selected from specific tissue phenotype classes
Additionally, claims 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, and 187 recite a law of nature which is the correlation between image patches derived from pathology images of a tissue samples and the determined gene alteration state for the tissue samples based on image patch data.
Step 2A Prong One Summary: The claims recite mental processes and mathematical concepts. When considering the broadest reasonable interpretation (BRI) of the claims, the mental processes recited in independent claim 1, 91 and 187 (e.g., classifying image patches; inputting the dataset into a gene alteration state classification model to determine a gene alteration state; extracting image features; clustering the image patches; labeling the image patches; determining a disease type; and/or determining a therapy, etc.) are directed to processes that may be performed in the human mind, or with pen and paper, as there are no particular limitations recited in claims 1, 91 and 187 which would prevent the mental processes from being performed. The claims recite inherent mathematical processes in, e.g., training the tissue phenotype classification model; clustering the image patches; performing dimensionality reduction; etc., while details of which are not explicitly shown in the claims, are discussed throughout the Specification, e.g., at [0245, 0251, 0256, 0271], etc. 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. Additionally, there is a law of nature recited in the correlation between image patches derived from pathology images of a tissue samples and the determined gene alteration state for the tissue samples based on image patch data. Therefore, the claims recite elements that constitute a judicial exception in the form of an abstract idea(s) and 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 and a law of nature 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.
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: The first inputting data step of claims 1, 91, and 187; and outputting data (claims 1and 187). 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: One or more processors (recited in claims 1, 91, and 187). 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)).
Additional element of therapy: Regarding the element of administering the selected treatment to an individual (claim 78), there is not yet a particular therapy in the sense of Prong Two, 2nd consideration recited because the nexus is insufficient between the output of the abstract idea (i.e., the determined gene alteration state) and the administering of treatment (MPEP § 2106.04(d)(2) as cited above). It is not clear that the gene alterations state for a gene of interest has a direct connection to the cancer. Therefore the element of administering the treatment of claim 78 is insufficient to integrate the abstract idea into a practical application of a particular therapy (see MPEP § 2106.04(d)(2)). Strengthening the nexus might result in claim 78 reciting a practical application of a particular therapy.
Step 2A Prong Two summary: The claims 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, 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. Additionally, the law of nature is not applied in a manner such that it is integrated into a practical application. (Step 2A, Prong Two: No).
Step 2B analysis:
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 exception because the claims recite additional elements that are well-understood, routine, and conventional. Those additional elements are as follows:
Additional elements of data gathering, inputting, and outputting steps: The additional elements of (the first step of) inputting data of claims 1, 91, and 187; and outputting data (claims 1and 187) do not cause the claims to rise to the level of significantly more than the judicial exception. The courts have recognized receiving or transmitting data over a network and storing and retrieving information in memory [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 extra-solution activity.
Additional elements of computer components: The additional elements of processors of claims 1, 91, and 187 do not cause the claims to rise to the level of significantly more than the judicial exception, and as such do not provide an inventive concept; these are conventional computer components.
Additional element of therapy: The additional element of administering treatment to the individual (claim 78) is a generic statement of therapy and does not cause the claims to rise to the level of significantly more than the judicial exception.
All limitations of claims 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, 91, and 187 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.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-5, 14-15, 21-23, 26, and 30 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Coudray (Nature medicine, vol. 24(10), pp.1559-1567 (2018); note: The 11/01/2023 IDS cites a 23 page long bioRxiv copy; however, the instant Office action refers to a 13 page copy published in Nature medicine and cited on the attached PTO form 892).
Regarding independent claim 1, the recited inputting image patches derived from tissue pathology samples into a tissue classification model to classify the image patches into a tissue phenotype class reads on "we used 1,634 whole-slide images from the Genomic Data Commons database: 1,176 tumor tissues and 459 normal tissues...split into three sets: training, validation and testing;" "the network was...trained, validated and tested using 512 × 512 pixel tiles, obtained from nonoverlapping ‘patches’ of the whole slide images" (Coudray, p.1560, col.1, ¶ 3); and "we develop classification models that classify whole-slide images into normal lung, LUAD (lung adenocarcinoma) or LUSC (lung squamous cell carcinoma)" (Coudray, p.1560, col.1, ¶ 4). The "tiles" of Coudray are interpreted as the "image patches" of the instant invention; Specification paragraphs [0116] and [0153] were considered when making this interpretation.
Regarding independent claim 1, the recited classifying the image patches to generate a labeled image patch data set for the tissue sample reads on "the ‘primary tumor’ images were classified between LUAD and LUSC types using a set of 567 and 608, respectively, of those whole-slide images. The labels provided by the TCGA database were used as our gold standard" (Coudray, p.1568, col.1, ¶ 1).
Regarding independent claim 1, the recited inputting the labeled image patch data set into a gene alteration state classification model to determine a gene alteration state for the tissue sample reads on "we modified the inception v3 to perform multitask classification ...Each mutation classification was treated as a binary classification...(which) allowed multiple mutations to be assigned to a single tile...We used the RMSProp algorithm for the optimization, and associated...a mutation and set to 1 or 0 depending on the presence or absence of the mutation (Coudray, p.1568, bridging cols.1-2); and "For the gene mutation prediction task, the t-SNE plot was generated using n = 24,144 tiles of 62 slides from 59 patients" (Coudray, p.1568, bridging col. 2, ¶2);
Regarding independent claim 1, the recited outputting the gene alteration state for the tissue sample reads on Figures 3a-c "Gene mutation prediction from histopathology slides," Coudray, p.1563, col.1.
Regarding claim 2, the recited gene alteration state classification model determines a gene alteration state for genes in the tissue sample based on the labeled image patch data reads on "each mutation classification was treated as a binary classification...(which) allowed multiple mutations to be assigned to a single tile...We used the RMSProp algorithm for the optimization, and associated...a mutation and set to 1 or 0 depending on the presence or absence of the mutation (Coudray, p.1568, bridging cols.1-2)
Regarding claim 3, the recited tissue phenotype classification model is trained using tissue phenotype classification model training image patches, each labeled with a tissue phenotype class selected tissue phenotype classes reads on "the ‘primary tumor images were classified between LUAD and LUSC types using a set of 567 and 608 (‘solid tissue normal’ and ‘primary tumor’ slides) respectively"(Coudray, p.1568, col.1, ¶ 1).
Regarding claim 4, the recited tissue phenotype classification model training image patches are derived from pathology images of tissue samples from the same tissue type reads on "studied the automatic classification of ‘solid tissue normal’ and ‘primary tumor’ slides using a set of 459 and 1,175, respectively, H&E- stained histopathology whole-slide images. Then, the ‘primary tumor’ images were classified between LUAD and LUSC types" (Coudray, p.1568, col.1, ¶ 1).
Regarding claim 5, the recited tissue phenotype classification model training image patches are manually labeled with tissue phenotype class reads on "we asked three pathologists to manually label the TCGA test LUAD and LUSC images" (Coudray (p.1568, col.2 ¶ 2).
Regarding claim 14, the recited performing a dimensionality reduction on the extracted image features prior to clustering the tissue phenotype classification model training image patches based on a reduced representation of the extracted image features reads on "we used the Barnes-Hit implementation of the t-SNE technique to reduce the dimensionality and facilitate the visualization of the classes" (Coudray, p.1568, col.2 ¶ 2).
Regarding claim 15, the recited gene alteration state classification model is trained using gene alteration state classification model training image patches, each of which is labeled with a tissue phenotype class and a gene alteration state reads on "three classifications: normal versus tumor, LUAD versus LUSC and normal versus LUAD versus LUSC" and "each mutation classification was treated as a binary classification, and our formulation allowed multiple mutations to be assigned to a single tile" (Coudray, (p.1568, col.1, ¶ 5-6).
Regarding claim 21, the recited output of the gene alteration state classification model is a determination of the presence or absence of a gene mutation in the tissue sample reads on "we modified the inception v3 to perform multitask classification ...Each mutation classification was treated as a binary classification...(which) allowed multiple mutations to be assigned to a single tile...We used the RMSProp algorithm for the optimization, and associated...a mutation and set to 1 or 0 depending on the presence or absence of the mutation (Coudray, p.1568, bridging cols.1-2; also see Fig, 3, p.1563).
Regarding claim 22, the recited output of the gene alteration state classification model is a probability that the tissue sample has a mutation in at least one gene reads on Figures 3a-c "Gene mutation prediction from histopathology slides," Coudray, p.1563, col.1.
Regarding claim 23, the recited output of the gene alteration state classification model is a probability that the tissue sample does not have the mutation in at least one gene reads on Figures 3a-c "Gene mutation prediction from histopathology slides," Coudray, p.1563, col.1.
Regarding claim 26, the recited tissue phenotype classes comprises one or more of: tumor phenotype classes, normal phenotype classes, stroma phenotype classes, immune phenotype classes, and necrosis phenotype classes reads on "we develop classification models that classify whole-slide images into normal lung, LUAD (lung adenocarcinoma) or LUSC (lung squamous cell carcinoma)" (Coudray, p.1560, col.1, ¶ 4); and "three classifications: normal versus tumor, LUAD versus LUSC and normal versus LUAD versus LUSC" (Coudray, (p.1568, col.1, ¶ 5-6).
Regarding claim 30, the recited pathology images are images of a cancerous tissue sample reads on "we used... whole-slide images from the Genomic Data Commons database: 1,176 tumor tissues" (Coudray, p.1560, col.1, ¶ 3).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 6-8, 11, 74, 78, 91, and 187 are rejected under 35 U.S.C. 103 as being unpatentable over Coudray as applied to claims 1-5, 14-15, 21-23, 26, and 30 in the 102 rejection above, and further in view of Chen (2020, Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis; bioRxiv doi: https://doi.org/10.48550/arXiv.1912.08937 ; cited on the attached PTO-892).
Regarding independent claims 91 and 187, the recited inputting image patches derived from tissue pathology samples (from an individual with disease in claim 187) into a tissue classification model to classify the image patches into a tissue phenotype class reads on "we used 1,634 whole-slide images from the Genomic Data Commons database: 1,176 tumor tissues and 459 normal tissues...split into three sets: training, validation and testing;" "the network was...trained, validated and tested using 512 × 512 pixel tiles, obtained from nonoverlapping ‘patches’ of the whole slide images" (Coudray, p.1560, col.1, ¶ 3); and "we develop classification models that classify whole-slide images into normal lung, LUAD (lung adenocarcinoma) or LUSC (lung squamous cell carcinoma)" (Coudray, p.1560, col.1, ¶ 4). The "tiles" of Coudray are interpreted as the "image patches" of the instant invention; Specification paragraphs [0116] and [0153] were considered when making this interpretation.
Regarding independent claims 91 and 187, the recited classifying the image patches to generate a labeled image patch data set for the tissue sample reads on "the ‘primary tumor’ images were classified between LUAD and LUSC types using a set of 567 and 608, respectively, of those whole-slide images. The labels provided by the TCGA database were used as our gold standard" (Coudray, p.1568, col.1, ¶ 1).
Regarding independent claim 91, the recited extracting image features from the image patches reads on "Visualization of features identified by the three-way classifier in high confidence tiles" and " the color of each tile corresponds to the class assigned by our algorithm (LUAD, LUSC or normal), and the color shade is proportional to the classification probability" (Coudray, p.1568, col.2, ¶ 3).
Regarding independent claim 187, the recited inputting the labeled image patch data set into a gene alteration state classification model to determine a gene alteration state for the tissue sample reads on "we modified the inception v3 to perform multitask classification ...Each mutation classification was treated as a binary classification...(which) allowed multiple mutations to be assigned to a single tile...We used the RMSProp algorithm for the optimization, and associated...a mutation and set to 1 or 0 depending on the presence or absence of the mutation (Coudray, p.1568, bridging cols.1-2); and "For the gene mutation prediction task, the t-SNE plot was generated using n = 24,144 tiles of 62 slides from 59 patients" (Coudray, p.1568, bridging col. 2, ¶2).
Regarding independent claim 187, the recited determining a disease type of the disease of the individual based on the determined gene alteration state reads on "the ‘primary tumor’ images were classified between LUAD and LUSC types using a set of 567 and 608, respectively, of those whole-slide images" (Coudray, p.1568, col.1, ¶ 1).
Regarding claim 74, the recited determining a gene alteration state of a gene of interest in a tissue sample from an individual with cancer reads on "(we) associated...a mutation and set to 1 or 0 depending on the presence or absence of the mutation" (Coudray, p.1568, bridging cols.1-2); and Fig. 3, "Gene mutation prediction from histopathology slides," Coudray, p.1563, col.1.
Coudray does not show training image patches are labeled using a clustering process comprising extracting image features from the patches and clustering the patches of claim 6 (shown by Chen).
Coudray does not show labels are assigned to the tissue phenotype classification model training image patches based on the extracted image feature clusters reads of claim 7 (shown by Chen).
Coudray does not show a pre-trained image feature extraction model of claim 8 (shown by Chen).
Coudray does not show an unsupervised image feature extraction model of claim 11 (shown by Chen).
Coudray does not show selecting a treatment based on the determined gene alteration state of claim 74 (shown by Chen).
Coudray does not show administering the treatment of claim 78 (shown by Chen).
Coudray does not show clustering the image patches based on the extracted image features of claim 91 (shown by Chen).
Coudray does not show labeling the image patches based on an associated image patch cluster of claim 91 (shown by Chen).
Coudray does not show determining a therapy for treating the disease type nor treating the individual with the therapy of claim 187 (shown by Chen).
Regarding claim 6, the recited tissue phenotype classification model training image patches are labeled using a clustering process comprising extracting image features from the patches and clustering the patches, and claim 7, the recited labels are assigned to the tissue phenotype classification model training image patches based on the extracted image feature clusters, reads on "cell graphs exhibit a hierarchical topology, in which the degree of eccentricity and clustered components of nodes in a graph define multiple views of how cells are organized in the tumor micro-environment... In order to encode the hierarchical structure of cell graphs, we adopt the self-attention pooling strategy SAGPOOL...which is a hierarchical pooling method that performs local pooling operations of node embeddings in a graph" (Chen, p.5, col.2, ¶ 2).
Regarding claim 8, the recited image features are extracted from the patches using a pre-trained image feature extraction model reads on "The Histology CNN was initialized using pretrained weights from ImageNet" (Chen, p.16, ¶ 5).
Regarding claim 11, the recited image features are extracted from the tissue phenotype classification model training image patches using an unsupervised image feature extraction model reads on "Unsupervised Cell Feature Extraction using Contrastive Predictive Coding" (Chen, p.5, col.1, ¶ 3).
Regarding claim 74, the recited selecting a treatment based on the determined gene alteration state, and claim 78, administering the treatment, reads on "Pathomic Fusion has the potential to refine gene signatures in cancers, and uncover new prognostic biomarkers that can be targeted in therapeutic treatments" (Chen, p.12, col.1, ¶ 1).
Regarding independent claim 91, the recited extracting image features from the image patches also reads on "Unsupervised Cell Feature Extraction using Contrastive Predictive Coding" (Chen, p.5, col.1, ¶ 3).
Regarding independent claim 91, the recited clustering the image patches based on the extracted image features reads on "CPC is designed to capture high-level representations shared among different portions (64 x 64 image patches) of the complete signal" (Chen, p.5, col.1, ¶ 3).
Regarding independent claim 91, the recited labeling the image patches based on an associated image patch cluster reads on "Histology CNN alone labels a majority of intermediate-to-high risk gliomas" (Chen, p.12, col.1, ¶ 1).
Regarding independent claim 187, the recited determining a therapy for treating the disease type based on the determined disease type, and the recited treating the individual with the therapy based on the determined therapy, reads on "Pathomic Fusion has the potential to refine gene signatures in cancers, and uncover new prognostic biomarkers that can be targeted in therapeutic treatments" (Chen, p.12, col.1, ¶ 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the methods for tissue/disease classification and mutation prediction of Coudray by using the feature extraction, clustering, unsupervised learning, and targeting therapeutic treatments of Chen. This is because Chen shows fusing deep features (including morphological features from histology images and genomic features) provides diagnostic, prognostic, and therapeutic relevance. One of ordinary skill in the art would have understood how to and been motivated to do modify, as Coudray and Chen are generally drawn to related teaching, and one of ordinary skill in the art would have understood how to and would have been motivated to modify the methods of Coudray with those of Chen, and as such, the combination would have been obvious.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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NSDP-1 (of 2):
Claims 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, 91, and 187 are rejected on the ground of nonstatutory double patenting as being unpatentable over one or more claims of: U.S. Patent No. 11,367,180 (from application 16/711,199), and U.S. Patent No. 12,694,972 (from application 18/506,905), in view of Chen (2020, Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis; bioRxiv doi: https://doi.org/10.48550/arXiv.1912.08937 ; cited on the attached PTO-892).
Although the claims at issue are not identical, they are not patentably distinct from each other because the '180 patent and the '972 patent, as well as the instant application, recite claims which involve analysis and classification of pathology images, and determining of a gene alteration state (e.g., mutation presence or absence).
While the instant claims recite limitations for clustering, unsupervised models, and treating an individual, these elements are shown by Chen (unsupervised learning, p.5, col.1, ¶ 3; clustering, p.5, col.2, ¶ 2; therapy, p.12, col.1, ¶ 1), such that this narrowing versus the '180 patent and the '972 patent is interpreted as obvious, and as such, the instant invention would have been prima facie obvious in view of the cited art.
NSDP-2 (of 2):
Claims 1-8, 11, 14-15, 21-23, 26, 30, 74, 78, 91, and 187 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over one or more claims of copending Application Nos. 19/680,073, 19/209,512, and 18/924,829 in view of Chen (2020, Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis; bioRxiv doi: https://doi.org/10.48550/arXiv.1912.08937 ; cited on the attached PTO-892).
Although the claims at issue are not identical, they are not patentably distinct from each other because the '073, '512, and '829 applications, as well as the instant application, recite claims which involve analysis and classification of pathology images, and determining of a gene alteration state (e.g., mutation presence or absence).
While the instant claims recite limitations for clustering, unsupervised models, and treating an individual, these elements are shown by Chen (unsupervised learning, p.5, col.1, ¶ 3; clustering, p.5, col.2, ¶ 2; therapy, p.12, col.1, ¶ 1), such that this narrowing versus the '073, '512, and '829 applications is interpreted as obvious, and as such, the instant invention would have been prima facie obvious in view of the cited art.
This is a provisional nonstatutory double patenting rejection.
Conclusion
No claims are allowed.
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/M.A.V./Examiner, Art Unit 1687
/G. STEVEN VANNI/Primary patents examiner, Art Unit 1686
