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 .
DETAILED ACTION
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office Action.
Status of Claims
Claims 1, 5, 13 and 19-22 are currently pending. Claims 1, 5, 13 and 19-22 have been amended by Applicants’ amendment filed 10-10-2025. Claims 23-35 have been canceled by Applicants’ amendment filed 10-10-2025. No claims have been added by Applicants’ amendment filed 10-10-2025.
Applicant's elects with traverse Group I, claims 1, 2, 5-8 and 12-15, drawn to a method for determining the selectivity of a test compound; and the election of Species with traverse as follows:
Species (A): wherein the test compound comprises one or more chemical substances (claim 5);
Species (B): Applicant did not make a species election with respect to claims 4 and 9 (claims 4 and 9); and
Species (C): wherein at least one part obtained in step (b) is further divided into at least two parts, wherein each of the at least two parts is incubated in step (c) with the test compound at different concentrations (claim 6), in the reply filed on November 23, 2022 was previously acknowledged.
Claims 3, 4, 9-11, 16-18 and 23-35 were previously withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a non-elected invention, there being no allowable generic or linking claim. Applicant timely traversed the restriction (election) requirement in the reply filed on November 23, 2022.
Claims 2, 7 and 8 were previously withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a non-elected species, there being no allowable generic or linking claim.
The restriction requirement was still deemed proper and was made FINAL.
The claims will be examined insofar as they read on the elected species.
A complete reply to the final rejection must include cancellation of nonelected claims or other appropriate action (37 CFR 1.144) See MPEP § 821.01.
Therefore, claims 1, 5, 13 and 19-22 are under consideration to which the following grounds of rejection are applicable.
Interview Summary
Applicant contacted the Examiner to set up an interview, where such telephonic interview was conducted between the Examiner, SPE Heather Calamita, and Applicant’s representatives Neil Horne and Keith Woffinden on September 17, 2025, where proposed amendments and the rejections of record were discussed.
Priority
The present application filed April 28, 2020 is a 35 U.S.C. 371 national stage filing of
International Application No. PCT/EP2018/079746, filed October 30, 2018; which claims the benefit of European Patent Application EP17199353.8, filed October 31, 2017.
Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 120 as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of the first paragraph of 35 U.S.C. 112. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, wherein the EP 17199353.8, filed October 31, 2017 filed April 4, 2019 fail to provide adequate support or enablement in the manner provided by the first paragraph of 35 U.S.C. 112 for one or more claims of this application. The specific method steps recited in independent claim 1 does not have support for; “wherein the first tissue sample part comprises a first portion of the cancerous cells and a first portion of the non-cancerous cells, and the second tissue sample part comprises a second portion of the cancerous cells and a second portion of the non-cancerous cells”; “cells exhibiting a viability phenotype”; “one or more microscopy machines”; and “selecting a compound for therapeutic treatment based on the compound-cancer selectivity metric”. Therefore, the priority date for the presently claimed invention is October 30, 2018, the filing date of International Application WO2019086476.
Applicants are invited to specifically indicate the location of the cited phrase pertinent to claim 1 of the instant application.
Response to Arguments
Applicant’s arguments filed October 10, 2025 have been fully considered but they are not persuasive. Applicants essentially assert that: (a) Applicant respectfully submits that the claimed subject matter was included in the original filing of EP 17199353.8, which can be obtained at WIPO, WO2019086476 (Applicant Remarks, pg. 9, first full paragraph).
Regarding (a), the Examiner respectfully notes that EP17199353.8 (See, certified copy filed April 29, 2020) is not the same document as international application WO2019086476. As noted supra, EP17199353.8 fails to provide support or enablement for the limitations as indicated; and the priority date for the claimed invention is determined to be the filing date of international application WO2019086476, wherein these limitations were determined to be taught.
Withdrawn Objections/Rejections
Applicants’ amendment and arguments filed October 10, 2025 are acknowledged and have been fully considered. The Examiner has re-weighed all the evidence of record. Any rejection and/or objection not specifically addressed below are herein withdrawn.
Maintained Objections/Rejections
Claim Interpretation: the term “a threshold” such as recited in claims 1, 19 and 22 is interpreted to refer to any threshold including, for example, a threshold value, a threshold range, a threshold metric, a reference threshold value, etc.
The term “selecting the test compound for therapeutic treatment of a patient having cancer based on the patient response prediction” such as recited in claim 1 is interpreted to mean that a test compound with any patient response prediction to a test compound can be selected for therapeutic treatment of any cancer including test compounds that fragment nuclei, test compounds that inhibit nuclei fragmentation, test compounds that exacerbate a cancer (e.g., increase cancer cell proliferation), have no effect on cancer cell nuclei and normal cell nuclei, etc.
The term “or cells derived from PBMCs or bone marrow cells” such as recited in claim 13 is interpreted to refer to cells derived from PBMCs, cells derived from bone marrow cells, and/or a non-adherent cell monolayer comprising cells derived from PBMCs or cells derived from bone marrow cells.
Claim Rejections - 35 USC § 112(b)
The rejection of claims 1, 5, 13 and 19-22 is maintained under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Claims 1, 19 and 22 are indefinite for the recitation of the term “comparing the test-compound-cancer selectivity metric to a threshold” such as recited in claim 1, lines 40-41 because the as-filed Specification and original claims do not teach “comparing the test-compound-cancer selectivity metric to a threshold.” The as-filed Specification teaches a threshold of cell subpopulations comprised in cell samples are well documented (pg. 19, first partial paragraph); and that the threshold is a distance parameter (pg. 44, first partial paragraph) and, thus, the metes and bounds of the claim cannot be determined.
Claim 1 is indefinite for the recitation of the term “administering the test compound” such as recited in claim 1, line 44. There is insufficient antecedent basis for the term “the test compound” in the claim because claim 1, line 42 recites the term “selecting the test compound.” Moreover, it is unclear whether the term “the test compound” refers to the administration of any test compound, or whether a ‘selected test compound’ is administered to the patient and, thus, the metes and bounds of the claim cannot be determined.
Claim 5 is indefinite for the for the recitation of the term “assess its effect on the viability phenotype” such as recited in claim 5, lines 3-4 because claim 5 depends from instant claim 1, wherein claim 1 does not recite a step of “assessing its effect on the viability phenotype.” Instead, claim 1 recites generating a non-test-compound viability phenotype measure, generating a test-compound viability phenotype measure, generating a test-compound-cancer selectivity metric, determining a patient response prediction, etc. and, thus, the metes and bounds of the claim cannot be determined.
Claim 20 is indefinite for the recitation of the term “fragmented states of nuclei” and “dead and or dying cells” such as recited in claim 20, lines 5 and 6 because claim 20 depends from claim 1, wherein claim 1 does not recite the presence of “fragmented states of nuclei” and “dead or dying cells”. Instead, claim 1 recites that the “viability phenotype” is a cell having non-fragmented nuclei. Thus, the step of “identifying” viability phenotype is directed to cells exhibiting non-fragmented nuclei and, thus, the metes and bounds of the claim cannot be determined.
Claim 21 is indefinite for the recitation of the term “generating the non-test-compound viability phenotype measure by…in the test-compound incubated tissue sample part” in claim 21, lines 2-10 because claim 21 depends from instant claim 1, wherein claim 1 clearly recites how the “non-test-compound viability phenotype measure” and the “test-compound viability phenotype measure” are generated, such that claim 21 recites a limitation that broadens the scope of claim 1 (e.g., claim 1 recites generating a ratio between the number of cancerous cells to non-cancerous cells; while claim 21 recites comparing the number of cancerous cells with an overall number of cells comprising cancerous and non-cancerous cells) and, thus, the metes and bounds of the claim cannot be determined.
Claim 22 is indefinite for the recitation of the term “administering the test compound to the patient to treat the cancer further comprises” such as recited in claim 22, lines 1-2 because the limitations recited in claim 22 have nothing to do with “administering the test compound”, such that it is completely unclear how “administering the test compound” can further comprise ‘selecting the test compound’ and ‘selecting the second test compound’. Moreover, claim 1 already recites the step of ‘selecting the test compound,’ which is also recited in claim 22, such that it is unclear whether the test compound must be selected twice before the second test compound is selected and, thus, the metes and bounds of the claim cannot be determined.
Claim 13 is indefinite insofar as they ultimately depend from instant claim 1.
Claim Rejections - 35 USC § 112(d)
The rejection of claim 22 is maintained, and claims 5, 20 and 21 are newly rejected under 35 U.S.C. 112(d) 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.
Claim 5 recites (in part): “wherein the one or more chemical substances comprise a known therapeutic agent or a therapeutic agent selected to assess its effect on the viability phenotype” in claim 5, lines 2-4 because claim 5 depends from claim 1, wherein claim 1 does not recite a step of assessing its effects on the viability phenotype. Instead, claim 1 recites steps including incubating, generating, identifying, generating, identifying, generating, determining, selecting, and administering. Thus, claim 5 is an improper dependent claims 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.
Claim 20 recites (in part): “detecting from the first set of microscopy images, fragmented states of nucleic in the first number of cancerous cells, wherein the fragmented states of nuclei indicate dead or dying cells” in claim 20, lines 5-6 because claim 20 depends from claim 1, wherein claim 1 recites that the viability phenotype comprises a cell having non-fragmented nuclei (e.g., not fragmented states). Thus, claim 20 is an improper dependent claims 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.
Claim 21 recites (in part): “generating the non-test-compound viability phenotype measure…in the test-compound incubated tissue sample part” in claim 21, lines 2-9 because claim 21 depends from claim 1, wherein claim 1 recites that the viability phenotype measure is obtained from generating a ratio of the number of cancerous cells to the number of non-cancerous cells exhibiting the viability phenotype, while claim 21 recites that the compound viability phenotype measure is more broadly generated by comparing the number of cancerous cells to an overall number of cancerous and non-cancerous cells. Thus, claim 21 is an improper dependent claims 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.
Claims 22 recites (in part): “wherein administering the test compound to the patient to treat the cancer further comprises…second patient response prediction to the second test compound” in claim 22, lines 1-7 because claim 22 depends from instant claim 1, wherein the step of “administering” does not ‘further comprise’ determining a second patient response prediction to a second test compound. These steps have nothing to do with ‘administering’. Additionally, claim 1 already recites “selecting the test compound for therapeutic treatment based on comparing the patient response prediction to the test compound,” such that it appears that this step is carried out twice before a second patient response prediction can be made. Thus, claim 22 is an improper dependent claims 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.
Applicant may cancel the claim, amend the claim to place the claim in proper dependent form, rewrite the claim in independent form, or present a sufficient showing that the dependent claim 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.
The rejection of claims 1, 5, 13 and 19-22 is maintained under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. An analysis with respect to the claims as a whole reveals that they do not include additional elements that are sufficient to amount to significantly more than the judicial exception. See Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 110 U.S.P.Q.2d 1976 (2014); Ass’n for Molecular Pathology v. Myriad Genetics, Inc., 133 S. Ct. 2107, 2116, 106 U.S.P.Q.2d 1972 (2013); Mayo Collaborative Svcs. v. Prometheus Laboratories, Inc., 132 S. Ct. 1289, 101 U.S.P.Q.2d 1961 (2012). See also 2014 Interim Guidance on Patent Subject Matter Eligibility, available at http://www.gpo.gov/fdsys/pkg/FR-2014-12-16/pdf/2014-29414.pdf (“2014 Interim Guidance”), and the Office’s examples to be considered in conjunction with the 2014 Interim Guidance in examination of nature-based products, available online at http://www.uspto.gov/patents/law/exam/mdc_examples_nature-based_products.pdf (“Nature-Based Products Examples”). This rejection is proper.
Analysis of subject-matter eligibility under 35 U.S.C. § 101 requires consideration of three issues: (1) whether the claim is directed to one of the four categories recited in §101; (2) whether the claim recites or involves a judicial exception (i.e., a law of nature, natural phenomenon, or natural product); and (3) whether the claim as a whole recites something that amounts to significantly more than the judicial exception. In this case, the claims as a whole are directed to a natural phenomenon in the form of naturally occurring tissue samples comprising cells that interact with naturally occurring and/or non-naturally occurring compounds to induce or inhibit a distinguishable phenotype; and to an abstract idea
In the form of mathematical concepts including mathematical relationships, formulas, and calculations; as well as, mental processes such as concepts performed in the human mind including observation, evaluation, judgement and opinion. Therefore, they must each be considered to determine whether, given their broadest reasonable interpretation, they amount to significantly more than the judicial exception.
The claimed invention is not directed to patent eligible subject matter. Based upon an analysis with respect to the claim as a whole, claim(s) 1, 5, 13 and 19-22 do not recite something significantly different than the judicial exception. The rationale for this determination is explained below:
In the instant case, the claims are broadly directed to a method for determining selectivity between cancerous cells and non-cancerous cells of a test compound, comprising: providing a tissue sample comprising cancerous cells and non-cancerous cells in a total population of cells; dividing the tissue sample into a first tissue sample part and a second tissue sample part, wherein the first tissue sample part comprises a first portion of the cancerous cells and a first portion of the non-cancerous cells and the second tissue sample part comprises a second portion of the cancerous cells and a second portion of the non-cancerous cells; incubating the first tissue sample part in an absence of a test compound to generate a non-test-compound incubated tissue sample part; incubating the second tissue sample part in a presence of the test compound to generate a compound incubated tissue sample part; generating a first set of microscopy images for the non-test-compound incubated tissue sample part utilizing one or more microscopy machines; generating a second set of microscopy images for the test compound incubated tissue sample part utilizing one or more microscopy machines; identifying from the first set of microscopy images, a first number of cancerous cells exhibiting a viability phenotype in the test-compound incubated tissue sample part utilizing a machine learning model, wherein the viability phenotype comprises a cell having non-fragmented nuclei; identifying from the second set of microscopy images, a second number of cancerous cells exhibiting the viability phenotype in the test-compound incubated tissue sample part utilizing the machine learning model; generating a test-compound viability phenotype measure by generating a ratio between the second number of cancerous cells exhibiting the viability phenotype in the test-compound incubated tissue sample part to a number of non-cancerous cells exhibiting the viability phenotype in the test compound incubated tissue sample part; generating a test-compound-cancer selectivity metric for the test compound by generating a ratio between the test-compound viability phenotype measure and the non-test-compound viability phenotype measure, wherein the test-compound-cancer selectivity metric indicates a measure to which the test compound induces or inhibits the viability phenotype in cancerous cells; determining a patient response prediction to the test compound by comparing the test-compound-cancer selectivity metric to a threshold; selecting the test compound for therapeutic treatment of a patient having cancer based on the patient response prediction; and administering the test compound to the patient to treat the cancer.
Beginning with Step I of the analysis, which asks whether the claimed invention falls within a statutory category, such that the instant claims are directed to a process, thus, the instant claims are directed to a statutory category. Step I: [YES].
Proceeding to Step IIA – Prong One of the analysis, which asks if the claimed invention is directed to a judicial exception, such that claims 1, 5, 13 and 19-22 are directed to a natural phenomenon in the form of naturally occurring tissue sample from subject comprising distinguishable cell populations including cancerous and non-cancerous cells comprising a naturally occurring viability phenotype comprising non-fragmented nuclei, wherein the cells are incubated with naturally occurring test compounds and/or non-naturally occurring test compounds, which do not possess markedly different characteristics such as different biological or pharmacological functions or activities, chemical or physical properties and/or structure/function and form as naturally occurring test compounds (e.g., toxins, atropine, aescin, DNA, RNA, ephedra sinica, proteins, peptides, antibodies, etc.), wherein the test compound, compound viability phenotype measure, and the test-compound cancer selectivity metric are correlated to the ability of the naturally occurring test compounds and/or the non-naturally occurring test compounds that are not markedly different from the naturally occurring test compounds to induce or inhibit the viability phenotype; and an abstract idea including: (1) mathematical concepts such as mathematical relationships, formulas and/or calculations (e.g., determining a number of cells; utilizing microscopy machines; utilizing a machine learning model; generating compound viability phenotype measures by generating a ratio; generating a test-compound-cancer selectivity metric; determining a patient response prediction to the test compound; comparing a test-compound-cancer selectivity metric to a threshold, selecting the test compound based on the patient response prediction, etc.); and/or (2) mental processes including concepts performed in the human mind such as observations, evaluation, judgement, and/or opinion (e.g., dividing a tissue sample into a first tissue sample part and a second tissue sample part; generating a non-test-compound selectivity metric; generating a test-compound-cancer selectivity metric; identifying a first number of cancerous cells and a second number of non-cancerous cells exhibiting the viability phenotype; and selecting a test-compound for therapeutic treatment, etc.). Thus, the claims are directed to a natural phenomenon and an abstract idea.
Step IIA - Prong Two of the analysis asks whether the claim recites additional elements that integrate the exception into a practical application of the exception. In the instant case, the claims are directed to a judicial exception in the form of a natural phenomenon and an abstract idea. Claim 1 recites: “a method for determining the selectivity of a test compound”; “providing a tissue sample comprising cancerous cells and non-cancerous cells in a total population of cells, wherein the tissue sample comprises at least I% of the cancerous cells and at least I% of the non-cancerous cells”; “dividing the tissue sample into a first tissue sample part and a second tissue sample part, wherein the first tissue sample part and the second tissue sample part comprise a first portion of the cancerous cells and a first portion of the non-cancerous cells”; “incubating the first tissue sample part in an absence of a test compound to generate a non-test-compound incubated tissue sample part; “incubating the second tissue sample part in a presence of the test compound to generate a compound incubated tissue sample part”;
“generating a first set of microscopy images for the non-test-compound incubated tissue sample part utilizing one or more microscopy machines”; “generating a second set of microscopy images for the test compound incubated tissue sample part utilizing one or more microscopy machines”; “identifying from the first set of microscopy images, a first number of cancerous cells exhibiting a viability phenotype in the test-compound incubated tissue sample part utilizing a machine learning model, wherein the viability phenotype comprises a cell having non-fragmented nuclei”; “generating a non-test-compound viability phenotype measure by generating a ratio between comparing the first number of cancerous cells exhibiting the viability phenotype in the non-test-compound incubated tissue sample part to a number of non-cancerous cells exhibiting the viability phenotype in the non-test-compound incubated tissue sample part”; “identifying from the second set of microscopy images, a second number of cancerous cells exhibiting the viability phenotype in the test-compound incubated tissue sample part utilizing the machine learning model; generating a test-compound viability phenotype measure by generating a ratio between the second number of cancerous cells exhibiting the viability phenotype in the test-compound incubated tissue sample part to a number of non-cancerous cells exhibiting the viability phenotype in the test compound incubated tissue sample part”; “generating a test-compound-cancer selectivity metric for the test compound by generating a ratio between the test-compound viability phenotype measure and the non-test-compound viability phenotype measure, wherein the test-compound-cancer selectivity metric indicates a measure to which the test compound induces or inhibits the viability phenotype in cancerous cells”; “determining a patient response prediction to the test compound by comparing the test-compound-cancer selectivity metric to a threshold; selecting the test compound for therapeutic treatment of a patient having cancer based on the patient response prediction”; and “administering the test compound to the patient to treat the cancer”, which resembles “obtaining and comparing intangible data” (i.e. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 99 U.S.P.Q.2d 1690 (Fed. Cir. 2011)), and are analogous to “organizing information through mathematical correlations” (i.e. Digitech Image Techs., LLC v Electronics for Imaging, Inc., 758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)); and are examples of “collecting information, analyzing it, and displaying certain results of the collection analysis” (i.e. Electric Power Group, LLC, v. Alstom, 830 F.3d 1350, 119 U.S.P.Q.2d 1739 (Fed. Cir. 2016)); and resembles “comparing information regarding a sample or test subject to a control or target data” (i.e. Univ. of Utah Research Found. v. Ambry Genetics Corp. (Also known as In re BRCA1– and BRCA2–Based Hereditary Cancer Test Patent Litigation), 774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014) or Association for Molecular Pathology v. USPTO (Also known as Myriad CAFC), 689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)). Additionally, the dependent limitations of claims 5, 13, 19 and 20-22 also suffer from the same issue. In other words, the dependent limitations do not rectify the rejection of the independent claim. By way of example, the limitations of claim 21 provides, “further comprising, generating the non-test-compound viability phenotype measure by comparing the first number of cancerous cells exhibiting the viability phenotype in the non-test-compound incubated tissue sample part to an overall number of cells exhibiting the viability phenotype in the non-test compound incubated tissue sample part; and generating the compound viability phenotype measure by comparing the second number of cancerous cells exhibiting the viability phenotype in the compound incubated tissue sample part to an overall number of cells comprising cancerous cells and non-cancerous cells that exhibit the viability phenotype in the non-test-compound incubated tissue sample part; and generating the test-compound viability phenotype measure by comparing the second number of cancerous cells exhibiting the viability phenotype in the test-compound incubated tissue sample part to an overall number of cells comprising cancerous cells and non-cancerous cells that exhibit the viability phenotype in the test-compound incubated tissue sample part” in lines 2-10, which are analogous to “obtaining and comparing intangible data” (i.e. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 99 U.S.P.Q.2d 1690 (Fed. Cir. 2011)); “collecting information, analyzing it, and displaying certain results of the collection analysis” (i.e. Electric Power Group, LLC, v. Alstom, 830 F.3d 1350, 119 U.S.P.Q.2d 1739 (Fed. Cir. 2016)); and “comparing information regarding a sample or test subject to a control or target data” (i.e. Univ. of Utah Research Found. v. Ambry Genetics Corp. (Also known as In re BRCA1– and BRCA2–Based Hereditary Cancer Test Patent Litigation), 774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014) or Association for Molecular Pathology v. USPTO (Also known as Myriad CAFC), 689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)). Thus, the claims do not integrate the judicial exceptions into a practical application of the exceptions. Step IIA – Prong Two [NO].
Proceeding to Step IIB of the analysis: the question then becomes what element or what combination of elements is sufficient to amount to significantly more than the abstract idea? The claims are broadly directed to the steps of a method including: (a) providing a tissue sample comprising cancerous and non-cancerous cells; (b) dividing the sample into at least two parts, wherein the first part and the second part comprise at least two distinguishable subpopulations; (c) incubating the first part in the absence of a test compound and incubating the second part in the presence of the test compound; (d) generating microscopy images using one or more microscopy machines; (e) identifying from the sets of microscopy images, the numbers of cancerous and non-cancerous cells exhibiting a viability phenotype utilizing a machine learning model; (f) generating compound viability phenotype measures by comparing the second number of cancerous cells exhibiting the viability phenotype to a number of non-cancerous cells exhibiting the viability phenotype; (g) generating a compound-cancer selectivity metric; (h) selecting a compound for therapeutic treatment; and (i) administering the test compound to the patient to treat the cancer.
For example, it was known that methods of PBMC monolayers composed of normal (e.g., healthy, cells) can be isolated from a sample obtained from a donor having a disease or predisposed to a disease, disease cells, e.g., the cells can have an abnormal phenotype or genotype themselves or representative of a disease state, such that the PBMC monolayers contain healthy cells that can act as a self-control in the methods, wherein the therapeutic response of the disease-state cells can be directly compared to the response of the healthy cells in the same sample; determining whether the disease is likely to respond or is responsive to treatment with a therapeutic agent; as well as, the steps of: (a) preparing the hematopoietic cell monolayer, in particular PBMC or bone-marrow cell monolayer, of the invention using hematopoietic cells, in particular PBMCs or bone marrow cells, of said individual; (b) determining one or more biological functions of one or more subpopulations comprised in the hematopoietic cell monolayer; (c) adding one of the at least two or more test compounds to the hematopoietic cell monolayer; and (d) determining-tracking-assessing-verifying changes of said one or more biological functions of the one or more subpopulations comprised in the hematopoietic monolayer, wherein the compound having the most advantageous effect on said one or more biological functions of said one or more subpopulations is selected for treatment of said individual; and that a physiologically-relevant state can be characterized by cell-cell interactions maintained during formation of the monolayer and/or viability of cells; an automated method is used to determine/track/assess/verify changes of viability and/or cell-cell interactions including identifying subpopulations using detectable labels, such that the fraction (e.g., ratio of cells of a subpopulation that is in contact with a further cells) is determined and the resulting number is compared to what would be expected by a random distribution function, wherein an interaction score can be calculated; the PBMC monolayer of the invention and the methods can also be used for following the course of a disease during treatment of a disease or in the absence of treatment; and that Figure 3 illustrates the results of a large viability screen in PBMCs as a measurement of global cell viability change, which is normalized to the ability of the drug to specifically target a single stained population, wherein all 1500 compounds sorted on cell number, and comparing the total number of PBMCs killed to the “specificity” of the ability of the compound to target one or more specific cell types present in the staining reduced and provided with a “specificity score”, such that the compounds highlighted are key anti-cancer candidate treatments as evidenced by Superti-Furga (WO2016046346; pg. 14, first and second full paragraphs; pg. 19, first full paragraph; pg. 23, first full paragraph, lines 5-15; pg. 47, first full paragraph; and pg. 54, last partial paragraph, Figure 3); and where it is known that a survival percentage can be calculated, wherein the following formula was used: Survival Percentage = (OD treatment /OD control) x 100; IC50 values (i.e. the extract concentration that exerts 50% inhibition with respect to untreated cells) were determined for all the cell lines; and the selectivity index (SI), which indicates the cytotoxic selectivity (i.e. drug safety) for Cyrtopodion scabrum extract (CsE) against cancer cells versus normal cells, was calculated from the following formula: Selectivity Index = IC50 calculated for normal / IC50 calculated for cancer wherein SI values more than 2 were considered as high selectivity as evidenced by Rashidi (International Journal of Cancer Management, April 2017, 10(5), 1-7; pg. 2, col 2; first and second full paragraphs). Moreover, methods for identifying potential therapeutically effective anti-cancer agents are known in the art, including methods related to the use of biochemical and cell based screening assays to identify compounds that directly or indirectly activate the apoptosis cascade and further a method for identifying those apoptosis inducers that are selective and effective apoptosis agents for use in treating cancer and other therapeutic indications characterized by a lack of appropriate apoptosis; the method is directed to identifying potentially therapeutically effective anti-cancer agents by determining the ability of one or more test compounds to selectively and differentially activate the apoptosis cascade in viable cultured cancer cells having an intact cell membrane when the cells are exposed to the test compounds for a predetermined, wherein a test compound is determined to have potential therapeutic efficacy if said caspase cascade activity is enhanced in response to the presence of said test compound; and calculating a first ratio of caspase cascade activity measured for the first volume to the caspase cascade activity measured for the second volume; and comparing the first ratio to at least one second ratio obtained with at least one second type of cultured cancer cells, and identifying those test compounds that have higher ratios for certain types of cultured cancer cells and are selective therefor; as well as, the results using different cancer cells tested separately are compared to identify anticancer agents that are selective for one or more particular cancers, which can be carried out by comparing the calculated ratios and identifying those test compounds having the highest ratio for particular cancer cells; alternatively or additionally, the selectivity may be determined by calculating the concentration of test compound necessary to give a 50% inhibition of growth (Gl50) of a first cell type and comparing that GI50 to the GI50 in at least one other cell type. Test compounds with lower GI50s in one or more particular cell types are selective therefor; and separately assessing the cell viability of the first volume and the second volume; and comparing the cell viability of the first volume to the cell viability of the second volume, wherein when the cell viability of the first volume is less than the cell viability of the second volume, the at least one test compound selectively kills the cancer cells and is identified as a selective anti-cancer agent as evidenced by Kasibhatla et al. (US2003027229; Abstract; paragraphs [0027]; and [0029]-[0031]).
Moreover, the instant independent claims are recited at a high level of generality, such that substantially all practical applications of the judicial exception are covered. For instance, the claims are recited without any specificity as to the type of selectivity; the method of providing; the type of cancerous cells (separately or individually including breast, lung, brain, stomach, mixtures thereof, etc.); the type of non-cancerous cells (e.g., normal, a patient with another disease including a virus, bacteria, etc.); the identity of the tissue samples (e.g., organ, skin, tumor, blood, etc.); the method of dividing; the type, amount, size, etc. of the first part and second parts; the method of incubating; the incubation conditions; the identity of the test compounds; the identity of non-test compounds; whether a reference compound is used; the identity of the threshold; the method of generating; the microscopy machines; the methods of generating; the methods of identifying a first number of cancerous cells; the first set of images; the second set of images; the method of extracting numbers; the machine learning model; the method of generating compound viability phenotype measure; the specific viability phenotype; the method of comparing the number of cancerous cells exhibiting the phenotype to the measure of non-cancerous cells exhibiting the phenotype; the method of generating the compound-cancer selectivity metric; whether the compound induces or inhibits the viability phenotype; how induction or inhibition is calculated for cancerous cells; the method of selecting a compound; the types of therapeutic treatments; the identity of the selected test compound; the cancers that can be treated with the selected test compound; the method of administration; the test-compound administered, etc. Step IIB: [NO].
In sum, when the relevant factors are analyzed, the claims as a whole do NOT recite additional elements that amount to significantly more than the judicial exception itself. Accordingly, claim 1 DOES NOT qualify as eligible subject matter.
Dependent claim(s) 5, 13 and 19-22 when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because they do not add anything that makes the natural phenomenon in claim 1 significantly different. For example, claim 5 encompasses the method of claim 1, wherein the test compound is one or more chemical substances, but it does not add anything that makes the natural phenomenon in claim 1 significantly different.
Thus, the claims as a whole do NOT recite additional elements that amount to significantly more than the judicial exception itself.
In light of the above consideration and the new guidance, claims 1, 5, 13 and 19-22 are non-statutory. This rejection is newly recited as necessitated by the new Guidance set forth in the Memorandum of July 30, 2015 updating the June 25, 2014 guidance (see June 25, 2014 memorandum from Deputy Commissioner for Patent Examination Policy Andrew Hirshfeld titled Preliminary Examination Instructions in view of the Supreme Court Decision in Alice Corporation Pty. Ltd. v. CLS Bank International, et al. (Alice Corp. Preliminary Examination Instructions).
Response to Arguments
Applicant’s arguments filed October 10, 2025 have been fully considered but they are not persuasive. Applicants essentially assert that: (a) the claims are not directed to a judicial exception; and the Examiner is required to analyze the claims as a whole to determine whether they are directed to the identified abstract idea, wherein a mental process must be something that can be performed in the human mind or by using a pen and paper (Applicant Remarks, Section A, pg. 18, last full paragraph through pg. 20, first full paragraph); (b) the amended claims do not recite a mathematical concept (Applicant Remarks, Section B, pg. 20, second full paragraph through pg. 21, first full paragraph); (c) to hold that the claims in the present case are directed to non-statutory subject matter of a natural phenomenon would amount to overgeneralizing the claims at a high level of abstraction and untethered from the language of the claims (Applicant Remarks, Section C, pg. 21, second full paragraph); (d) the amended claims recite a practical application of any purported judicial exception, includes an additional element that reflects an improvement in the functioning of a computer or other technology, and the claim integrates a judicial exception into a practical application including to effect a particular therapeutic treatment (Applicant Remarks, pg. 21, last full paragraph through pg. 24, last full paragraph); and (e) the Specification describes how the claimed invention may provide improvements to existing approaches, which does not require the measurement of absolute cell numbers, but relies on a comparison of cells, or using an EC50 to measure selectivity, where the claimed invention may rely on comparisons of cells to determine selectivity; as well as, conserving limited samples from primary patients (Applicant Remarks, pg. 24, last partial paragraph through pg. 26, first full paragraph).
Regarding (a), Applicant’s assertion that the claims are not directed to a judicial exception; and that a mental process must be something that can be performed in the human mind or by using a pen and paper, is not found persuasive. The Examiner has clearly outlined how the recited claims are directed to judicial exceptions including being directed to a natural phenomenon and an abstract idea in the form of mathematical concepts and/or mental processes. The mental processes highlighted by the Examiner include:
dividing a tissue sample into a first tissue sample part and a second tissue sample part;
generating a non-test-compound viability metric;
generating a test-compound-cancer selectivity metric;
identifying a first number of cancerous cells and a second number of non-cancerous cells exhibiting the viability phenotype utilizing microscopy images; and
selecting a test-compound for therapeutic treatment.
The as-filed Specification teaches that: detectable labels allow visualization of the label under visible or ultra-violet light (pg. 32, last line through pg. 33, first partial paragraph); and that determining, tracking, assessing, and/or verifying changes of viability and/or cell-cell interactions of the two or more distinguishable subpopulation…using microscopy, changes can be determined, tracked, assessed, and/or verified by optical perception (pg. 41, last partial paragraph to pg. 42, first partial paragraph). The Examiner maintains that these limitations can clearly be performed in the human mind or by using a pen and paper. Thus, the claims remain rejected for the reasons of record.
Regarding (b), Applicant’s assertion that the amended claims do not recite a mathematical concept, is not found persuasive. The Examiner has clearly outlined how the recited claims are directed to a judicial exception including being directed to a natural phenomenon and an abstract idea in the form of mathematical concepts and/or mental processes. Mathematical concepts include mathematical relationships, formulas, and/or calculations. Instant claim 1 recites numerous mathematical concepts including: (i) determining a number of cells; (ii) utilizing microscopy machines; (iii) utilizing a machine learning model; (iv) generating non-test compound viability phenotype measures and test-compound viability phenotype measures by generating a ratio; (v) generating a test-compound-cancer selectivity metric; (vi) determining a patient response prediction to the test compound; (vii) comparing a test-compound-cancer selectivity metric to a threshold, and (viii) selecting the test compound based on the patient response prediction.
The instant as-filed Specification teaches that quantification and further means and methods, for example determination of cell-cell interactions using microscopy (pg. 19, first partial paragraph); an average selectivity can be calculated in step (e) and used for determining the final selectivity (pg. 25, first full paragraph); the number of viable cancerous and noncancerous cells is determined using automated microscopy (pg. 32, second full paragraph); various computational methods exist that enable a person skilled in the art to analyze and interpret the microscopy images of cells or to establish automated protocols for their analysis…including the correction for illumination bias in microscopy images, the identification of individual cells from microscopy images and the measurement of marker intensities and textures as well as nuclear and cellular size and shape and position parameters, the opensource software CellProfiler (e.g. version 2.1.1) can be used; as well as, the cellHTS package in Bioconductor (e.g. version 2.14), or Pipeline Pilot (e.g. version 9.0; Accelrys), can both be used for the data analysis subsequent to the primary image analysis, including plate-effect normalization, control-based normalization, and hit selection (pg. 37, last full paragraph; and pg. 38, first and second full paragraphs); the viability of cells of population A and population B after treatment with compound X at different concentrations [X] , (log EC50 towards A = -2 and log EC50 towards B = 3 on an arbitrary concentration scale) was calculated (pg. 46, second full paragraph; and Figure 10); and the total number of live cells was quantified by counting intact DAPl-stained nuclei using the CellProfiler computational image analysis software whereas fragmented nuclei were discarded as dead or dying (pg. 48, first partial paragraph). The abstract ideas clearly fall within the groupings of abstract ideas discussed in MPEP 2106.04(a)(2). Thus, the claims remain rejected for the reasons of record.
Regarding (c), Applicant’s assertion that to hold that the claims in the present case are directed to non-statutory subject matter of a natural phenomenon would amount to overgeneralizing the claims at a high level of abstraction and untethered from the language of the claims, is not found persuasive. Applicant did not distinctly and specifically point out the supposed errors in the Examiner’s action as required by 37 CFR 1.111(b). Applicant has provided no argument regarding the rejection based on the claims being directed to a natural phenomenon. Thus, the claims remain rejected for the reasons already of record.
Regarding (d), Applicant’s assertion that the amended claims recite a practical application of any purported judicial exception, includes an additional element that reflects an improvement in the functioning of a computer or other technology, and the claim integrates a judicial exception into a practical application including to effect a particular therapeutic treatment, is not found persuasive. Regarding an additional element that reflects an improvement in the functioning of a computer or other technology, Applicant has not provided a single specific technology and/or improvement thereof accomplished by the instant method. Additionally, instant claim 1 does not integrate the judicial exception into a practical application of the exception. Instant claim 1 is very broadly recited, such that the claims provide no specificity regarding the identity of the particular patient; the specific tissue sample; the types of cells; the type of cancer; the one or more test compounds; the type of microscopy images and how they are evaluated; the identity of the machine learning model; how the machine learning model is interpreted; the methods of generating; the methods of identifying; the viability phenotype measures; the ratios obtained and what they mean; the test-compound-cancer selectivity metric; the specific viability phenotype measures that indicate inducement or inhibition of the viability phenotype in cancerous cells; the method of determining the patient response prediction to the test compound; the identity, ranges, and/or comparisons with the threshold; what number and/or metric of the patient response prediction leads to the selection of a test compound as a therapeutic compound; the identity of the compound(s) selected; the method of administration; the type of cancer being treated, etc. More specifically, it is noted that:
The instant claims do not recite any specific tissue sample.
The claims do not recite any specific test compounds.
The claims do not recite a specific tissue sample, specific cell types, numbers of cells, and/or specific sample preparation (e.g., whether they are tested as FFPE tissue slices, homogenized samples, carried out within vials, on a glass slide, attached to a polymer coating, etc.).
The claims do not recite any specific microscopy images, specific method of utilizing the microscopy images, and/or the generation of specific images (e.g., fluorescent images, simple microscope images, laser capture microscopy images, near-field scanning, photographs, computer models, etc.).
The claims do not recite any specific machine learning model or how it identifies a number of cancerous or non-cancerous cells (e.g., logistic regression, Naïve Bayes classier, linear regression, random forest, k-nearest neighbors algorithm, etc.).
The claims do not recite any specific ratio that generates compound viability phenotype measures.
The claims do not recite any specific method of generating a test-compound-cancer selectivity metric, determining a patient response prediction, and/or what metrics, values, ranges, etc. are used to select a specific therapeutic treatment for a patient.
The claims do not recite the specific calculations, measurements, metric values, ranges and/or threshold values that indicate that the viability phenotype is induced or inhibited by a specific test compound.
The claims do not recite the selection of any specific compound for any particular type of therapeutic treatment (e.g., lung cancer, SCLC, breast cancer, prostate cancer, glioblastoma, Ewing sarcoma, proteins, peptides, pharmaceutical cancer drugs, breast cancer drugs, kinases, hormone therapy, immunotherapy, etc.) for the treatment of any specific patient.
One of ordinary skill in the art could not use the method as recited in instant claim 1 to select a single test compound for administration and treatment of a specific disease including a specific cancer. The claims do not integrate the judicial exceptions into a practical application of the judicial exceptions. Moreover, the instant method as recited in instant claim 1 is well-known, purely conventional, or routine in the art as evidenced by Superti-Furga, Rashidi and Kasibhatla. Additionally, because the method cannot be used for the treatment of a single patient, there is no practical application of a second patient as recited in dependent claim 19. Thus, the claims remain rejected for the reasons of record.
Regarding (e), please see the discussion supra regarding the Examiner’s response to
MPEP 2112.01(II) indicates:
"Products of identical chemical composition cannot have mutually exclusive properties." In re Spada, 911 F.2d 705, 709, 15 USPQ2d 1655, 1658 (Fed. Cir. 1990). A chemical composition and its properties are inseparable. Therefore, if the prior art teaches the identical chemical structure, the properties applicant discloses and/or claims are necessarily present. Id. (Applicant argued that the claimed composition was a pressure sensitive adhesive containing a tacky polymer while the product of the reference was hard and abrasion resistant. "The Board correctly found that the virtual identity of monomers and procedures sufficed to support a prima facie case of unpatentability of Spada’s polymer latexes for lack of novelty") (underline added).
Applicant’s arguments. MPEP 716.02(b) states:
the evidence relied upon should establish "that the differences in results are in fact unexpected and unobvious and of both statistical and practical significance." Ex parte Gelles, 22 USPQ2d 1318, 1319 (Bd. Pat. App. & Inter. 1992) (Mere conclusions in appellants’ brief that the claimed polymer had an unexpectedly increased impact strength "are not entitled to the weight of conclusions accompanying the evidence, either in the specification or in a declaration."); Ex parte C, 27 USPQ2d 1492 (Bd. Pat. App. & Inter. 1992) (See also; In re Nolan, 553 F.2d 1261, 1267, 193 USPQ 641, 645 (CCPA 1977).
MPEP 716.02(c) indicates:
unexpected results must be weighed against evidence supporting a prima facie obviousness. In re May, 574 F.2d 1082, 197 USPQ 601 (CCPA 1978); and where the unexpected properties of a claimed invention are not shown to have a significance equal to or greater than the expected properties, the evidence of unexpected properties may not be sufficient to rebut the evidence of obviousness. In re Nolan, 553 F.2d 1261, 1267, 193 USPQ 641, 645 (CCPA 1977). “Expected beneficial results are evidence of obviousness of a claimed invention, just as unexpected results are evidence of unobviousness thereof.” In re Gershon, 372 F.2d 535, 538, 152 USPQ 602, 604 (CCPA 1967).
Applicant’s assertion that the Specification describes how the claimed invention may provide improvements to existing approaches, which does not require the measurement of absolute cell numbers, but relies on a comparison of cells, or using an EC50 to measure selectivity, where the claimed invention may rely on comparisons of cells to determine selectivity; as well as, conserving limited samples from primary patients, is not found persuasive. As an initial matter, Applicant does not actually assert any specific improvement over “existing approaches”. Instead, Applicant argues that the claimed invention may provide improvements over “existing approaches” and that the claimed invention may rely on comparisons of cells to determine selectivity. It is noted that mere recognition of latent properties in the prior art does not render nonobvious an otherwise known invention. In re Wiseman, 596 F.2d 1019, 201 USPQ 658 (CCPA 1979) and In re Baxter TravenoILabs., 952 F.2d 388, 21 USPQ2d 1281 (Fed. Cir. 1991). See MPEP § 716.02 - § 716.02(g). As an initial matter:
Evidence has not been provided that the asserted "superior results" were unknown in the prior art.
Applicant has not shown that there is a nexus and/or a co-extensiveness between what is recited in instant claim 1, and the unexpected or superior results asserted by Applicant.
Applicants have not clearly stated the nature of the unexpectedly improved properties that are not taught in the prior art.
The instant claims do not recite any of the potential improvements discussed by Applicant. For example, instant claim 1 does not recite determining an accurate measure of cancer cell selectivity; it does not recite a step of providing information about whether a subject suffering from cancer will respond or is responsive to treatment with a test compound; there is no step of determining AUROC or EC50; no steps of determining the sensitivity of cancer cells, determining the sensitivity of a total cell population, and/or determinations regarding classification accuracy based on comparative data. Furthermore, the as-filed Specification teaches that accurate classification is not possible for compound combinations using the metric, and indicates that the selectivity/value metric has a cut-off value of 0.92 and only allows for classification of patients into responders and non-responders. Testing indicated the metric was found to have a classification accuracy of 0.65 to 0.85. The selectivity metric does not appear to provide an accurate measure of selectivity of a test compound (pgs. 44-45, Figure 4). Thus, the claims remain rejected for the reasons of record.
Claim Rejections - 35 USC § 103
(1) The rejection of claims 1, 5, 13 and 19-22 is maintained under 35 U.S.C. 103 as being unpatentable over Clarke et al. (US Patent Application Publication No. US20160312302, published October 27, 2016; of record) in view of Ingram et al. (US Patent Application Publication No. 20140093953, published April 3, 2014; of record) as evidenced by Lovitt et al. (Biology, 2014, 3, 345-367; of record); and Tibshirani et al. (hereinafter “Tibshirani”) (PNAS, 2002, 99(10), 6567-6572; of record).
Regarding claims 1, 15 and 19-22, Clarke et al. teach methods for the diagnosis and prognosis of disease by analyzing expression of a set of genes obtained from single cell analysis, such that classification allows optimization of treatment, and determination of whether to proceed with a specific therapy, and how to optimize dose, choice of treatment, and the like, wherein single cell analysis also provides for the identification and development of therapies which target mutations and/or pathways in disease-state cells (Abstract). Clarke et al. teach that early disease diagnosis is of central importance to halting disease progression, and reducing morbidity, such that analysis of a patient samples to identify gene expression patterns provides the basis for more specific, rational disease therapy that can result in diminished adverse side effects relative to conventional therapies; and can provide a basis of therapeutics, diagnostics, prognostics, and/or thermometric; as well as, avoiding unnecessary therapies (paragraph [0006]). Clarke et al. teach analyzing a heterogeneous tumor biopsy from a subject, comprising: randomly partitioning cells from the biopsy into discrete locations; performing transcriptome analysis on at least 50 genes of the individually partitioned cells; and using transcriptome data to identify one or more characteristic of the tumor (interpreted as a phenotype), wherein a characteristic identified can be the presence, absence, or number of cancer cells; the presence, absence or number of stem cells, early progenitor cells, initial differentiated progenitor cells, late differentiated progenitor cells, or mature cells; the effectiveness of a therapeutic agent in eliminating one or more of the cells; and/or the activity of a signaling pathway, for example, a pathway specific to a cancer stem cell, a differentiated cancer cell, a mature cancer cell, or combination thereof; and the method can further comprise the step of using the characteristic to diagnose a subject with cancer or a cancer stage (interpreted as providing a sample; at least two sub-populations of cells divided into two parts; determining the number of cells exhibiting a phenotype in the presence or absence of a test compound; and determining selectivity by dividing (i) through (ii), claim 1) (paragraph [0013]). Clarke et al. teach that a single cell analysis device (SCAD) is modular and can perform the following steps in an integrated, fully automated fashion including: (1) digestion of the tissue; (2) separation of live cells from the debris; (3) staining, wherein the filtered single cell suspension is optionally stained using appropriate surface markers in a compartment of the microfluidic device including staining with up to five different markers can be useful in obtaining a high purity population of cancer cells; and (4) sorting, wherein he stained single-cell suspension is flowed into the next compartment of the microfluidic device to sort out the cancer cells from the rest of the cells (interpreted as providing a sample comprising distinguishable phenotypes; dividing the sample into at least two parts; encompassing non-fragmented nuclei; and fully automated as including automated microscopy, claims 1, 19 and 20) (paragraph [0050]). Clarke et al. teach in Figure 7A illustrates the steps of: (1) digestion of the tissue by appropriate enzymes are introduced and flowed to perform the digestion of the extracellular matrix in order to obtain a cell suspension; (2) separation of live cells from debris by flowing the digested tissue suspension through a microfluidic “metamaterial”; (3) staining: the filtered single cell suspension is stained using appropriate surface markers in a different compartment of the device, wherein staining with up to five different markers which can be useful in obtaining a high purity population of cancer cells; and (4) sorting: the stained single-cell suspension is flowed into the next compartment to sort out the cancer cells from the rest of the cells within a confidence level of 99% (interpreted as providing a tissue sample comprising two distinguishable subpopulations of cells including cancer, non-cancer, live, debris, etc.; dividing the tissue sample into at least two parts; ! % cancerous cells and !% non-cancerous cells, claims 1a and 1b) (paragraph [0176]). Figure 7A is shown below:
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Figure 7A
Clarke et al. teach that an obtained expression profile can be compared to a single reference/control profile to obtain information regarding the phenotype of the cell/ tissue being assayed; or the obtained expression profile can be compared to two or more different reference/control profiles to obtain more in-depth information regarding the phenotype of the assayed cell/tissue (paragraph [0056]). Clarke et al. teach that nucleic acids can be up-regulated or down-regulated as compared to another population or sub-population, a particular nucleic acid of known expression level, or a standard expression level; alternately, when analyzing the expression of multiple genes, a heatmap can be created by subtracting the mean and dividing by the standard deviation for each gene independently and numerical values are assigned based on the degree of deviation from the mean; for example, values of +/-1 can represent 2.5-3 standard deviations from the mean, wherein such analyses can be further refined, such that genes in the "+/-3” range can be used to cluster different types of populations (e.g., cancer is given the value "+3” and normal tissue is given the value “-3’ so that a clustering algorithm can discern between them), such that an upregulated gene can be a “+” value (interpreted as determining selectivity; dividing (i) through (ii); and interpreting upregulation or down-regulation as inhibits if less than 1, or induces if greater than 1; a tissue sample; comprising at least 1% cancer cells and/or at least 1% of non-cancer cells; generating a compound viability phenotype; comparing the number of cancerous cells; and determining patient response; and selecting a test compound, claims 1, 3, 21 and 22) (paragraph [0065]). Clarke et al. teach that the number of CSC in a patient sample can be determined relative to the total number of cancer cells (interpreted as a number ratio of at least two subpopulations relative to a total number of cells); and that a greater percentage of cancer stem cells (CSC) is indicative of the potential for continued self-renewal of cells with the cancer phenotype, such that the quantitation of CSC in a patient sample can be compared to a positive and/or negative reference sample such as a patient sample including a blood sample, a remission patient sample, etc., wherein the quantitation of CSC is performed during the course of treatment, where the number of cancer cells and the percentage of such cells that are CSC are quantitated before, during, and as follow-up to a course of therapy, wherein therapy targeted to cancer stem cells results in a decrease in the total number, and/or percentage of CSC in a patient sample (interpreted as at least 1% of cancerous or non-cancerous cells; generating a compound viability phenotype; comparing the number of cancerous cells; and determining patient response; and selecting a test compound, claims 1 and 19-22) (paragraph [0085], lines 1-3 and 10-22). Clarke et al. teach that once a sample is obtained, it can be used directly, frozen, or maintained in appropriate culture medium for short periods of time, wherein various media can be employed to maintain cells (interpreted as culturing tissue cells number ratio of a subpopulation relative to a total number of cells; and number ratio of a subpopulation relative to a total number of cells, claims 1 and 13) (paragraph [0089], lines 1-4). Clarke et al. teach that methods are also provided for optimizing therapy such as by first classification, and based on that information, selecting the appropriate therapy, dose, treatment modality, etc. which optimizes the differential between delivery of an anti-proliferative treatment to the undesirable target cells, while minimizing undesirable toxicity, wherein the treatment is optimized by selection for a treatment that minimizes undesirable toxicity, while providing for effective anti-proliferative activity (interpreted as determining a selectivity ratio of the test compound to induce the distinguishable phenotype in the first subpopulation over the rest of the subpopulations; a compound-cancer selectivity metric for inducing the phenotype; and encompassing non-fragmented nuclei, claims 1, 19 and 20) (paragraph [0097]). Clarke et al. teach that compounds which affect such phenotypic characteristics can be analyzed in addition to or in lieu of analyzing a compounds potential as a therapeutic agent such as, for example, analysis of changes in gene expression in a target population such as, for example, normal colon cells, normal breast cells, cancer cells, stem cells, cancer stem cells, etc. exposed to one or more test compounds can performed to analyze the effects of the test compounds on gene expression or other desired phenotypes marker expression including cell viability (interpreting the phenotype as cell viability; and encompassing non-fragmented nuclei, claims 19 and 20) (paragraph [0109]). Clarke et al. teach that in screening assays for biologically active agents such as anti-proliferative drugs, etc., a marker or a target cell composition is contacted with the agent of interest, and the effect of the agent assessed by monitoring output parameters on cells, such as expression of markers, cell viability, and the like; binding efficacy; or effect on enzymatic or receptor activity for polypeptides such that, for example, a breast cancer cell composition known to have a "cancer stem cell expression profile” is exposed to a test agent and exposed cells are individually analyzed as described herein to determine whether the test agent altered the expression profile as compared to non-treated cells (interpreting cells with the agent and without as providing at least two subpopulations exhibiting a distinguishable phenotype; interpreting treated and non-treated cells as being two subpopulations in the presence or absence of a test compound; and viability as the phenotype; and encompassing non-fragmented nuclei, claims 1, 19 and 20) (paragraph [0114], lines 1-12). Clarke et al. teach that any isolated cell population described herein or produced by the methods described herein can be freshly isolated, cultured, genetically altered, and the like, wherein the cells can be environmentally induced variants of clonal cultures: e.g., split into independent cultures and grown under distinct conditions, for example with or without drugs; in the presence or absence of cytokines or combinations thereof, such that the manner in which cells respond to an agent (e.g., a peptide, siRNA. Small molecule, etc.) including a pharmacologic agent, including the timing of responses, is an important reflection of the physiologic state of the cell (interpreted as culturing tissue cells; and encompassing a non-adherent cell monolayer, claim 13) (paragraph [0114], lines 12-23). Clarke et al. teach isolated cells are contacted with one or more agents and the level of expression of a nucleic acid of interest is determined, such that agents which alter the expression of the detected nucleic acids (e.g., where the cells exhibit an expression pattern more similar to a non- disease state cell), can be further analyzed for therapeutic potential; and that while most parameters (e.g., mRNA or protein expression) will provide a quantitative readout, in some instances a semi-quantitative or qualitative result is acceptable, wherein readouts can include a single determined value; mean; median value; the variance, etc. including a range of parameter readout values is obtained for each parameter from a multiplicity of the same assays, wherein variability is expected and a range of values for each of the set of test parameters are obtained using standard Statistical methods with a common statistical method used to provide single values (interpreted as determining test compound selectivity; and a compound-cancer selectivity metric for inducing the phenotype, claim 1) (paragraph [0115]). Clarke et al. teach that the cells are isolated into distinct positions for analysis, the cells can be sorted with a microfluidic sorter by flow cytometry, microscopy, etc., wherein the integrated cell sorter can incorporate various microfluidic functionalities including pumps, dampers, switch valves etc. including fluorescence activated cell sorters (FACS) (interpreted as automated microscopy, claim 19) (paragraphs [0046]; and [0091]). Clarke et al. teach that the plurality of assays can be run in parallel with different agent concentrations to obtain a differential response to the various concentrations, such that, as known in the art, determining the effective concentration of an agent typically uses a range of concentrations resulting from 1:10, or other log scale, dilutions, wherein the concentrations can be further refined with a second series of dilutions; and that, typically, one of these concentrations serves as a negative control, such as at zero concentration or below the level of detection of the agent or at or below the concentration of agent that does not give a detectable change in the phenotype (interpreted as incubating the sub-populations with different concentrations of the test compound; and repeating; phenotype selectivity ratio; and a number ratio more or less than one, claim 1) (paragraph [0125]). Clarke et al. teach the measurement of fluorescent labels including by immunoassay techniques such as radio-immunoassay (RIA) or enzyme-linked immunosorbance assay (ELISA) (paragraph [0127], lines 1-4 and 9-12). Clarke et al. teach that agents are screened for biological activity by adding the agent to at least one and usually a plurality of cell samples, usually in conjunction with cells lacking the agent, such that the change in parameters in response to the agent is measured, and the result evaluated by comparison to reference cultures including in the presence and absence of the agent, obtained with other agents, etc. (interpreting cells with the agent and without as providing at least two subpopulations exhibiting a distinguishable phenotype; interpreting splitting cultures dividing a sample; agents as the presence or absence of a test compound; and determining the number of cells that exhibit a phenotype; dividing (i) through (ii); and inhibits or induces the phenotype, claim 1) (paragraph [0122]). Clarke et al. teach that various methods for analysis of a set of data can be utilized including wherein (1) expression data is subjected to transformation and normalization, such that ratios are generated by mean centering the expression data for each gene (by dividing the intensity measurement for each gene on a given array by the average intensity of the gene across all arrays), (2) then log-transformed (base 2) the resulting ratios, and (3) then median centered the expression data across arrays then across genes (interpreted as determining a number ratio; and determining the number of cancerous cells exhibiting the viability phenotype, claims 1 and 21) (paragraph [0132]). Clarke et al. teach that a scaled approach may also be taken to the data analysis such as, for example, Pearson correlation of the expression values of genes can provide a quantitative score reflecting the signature for each cancer stem cell (CSC), wherein the higher the correlation value, the more the sample resembles a reference CSC phenotype; and that similar correlation can be done for any cell type, including normal cells, progenitor cells, autoimmune phenotype cells, inflammatory phenotype cells, infected cells, differentiated cancer cells, normal stem cells, normal mature cells, etc., such that a negative correlation value indicates the opposite behavior, wherein the threshold for the classification can be moved up or down from zero depending on the clinical goal including sensitivity and specificity for predicting metastasis as the first recurrence event can be calculated for every threshold between -1 and +1 for the correlation score in 0.05 increments, and the threshold value giving a desired sensitivity (e.g. 80%, 90%. 95%, etc. for metastasis) prediction can be selected (interpreted as a number ratio for when the test compound selectively induces the distinguishable phenotype for the determined selectivity ratio is greater than one, and the test compound that inhibits or reduces the distinguishable phenotype for the determined selectivity ratio is less than one, claim 1) (paragraph [0134]). Clarke et al. teach in Example 10 that isolated single cells are lysed and the lysates are divided into two portions, wherein the first portion is subjected to single-cell gene expression analysis by real-time PCR as described in Example 1, using a selection of genes which allow for distinguishing between HSCs and non-HSCs, either by level or presence of expression (e.g., CD34+, CD19-, CD17-), such that after identifying HSCs within the population lysates from the single cells identified as being HSCs are pooled (interpreted as providing a sample comprising two sub-populations of cells in a total population; dividing the sample into two part; determining the number of cells exhibiting a distinguishable phenotype by expression level; and determining selectivity, claims 1, 21 and 22) (paragraph [0186]). Clarke et al. teach in Example 11 the selection of candidate therapeutic agents is performed, wherein target cells such as colon cancer stem cells and colon cancer cells (differentiated) are isolated and analyzed at the single cell level as described; and target cells are separated from a biopsy specimen using markers specific for the target cells (e.g., FACS separation using target-cell-specific antibodies and/or fluorescent labeling of target-cell specific nucleic acids) previously identified (interpreting stem cells and cancer cells, target cells and non-target cells in a biopsy specimen as providing a sample comprising two sub-populations of cells, claim 1) (paragraph [0188]). Clarke et al. teach that target cells are separated into addressable positions comprising a single cell, and the isolated cells are then exposed to a library of candidate therapeutic agents (e.g., antibodies, toxin-conjugated antibodies, small molecules), cells are then collected and analyzed for gene expression patterns and/or cell viability, wherein successful candidate therapeutic agents can be those which target the cells for death or, alternately, candidate therapeutic agents can alter expression of genes known to be mis-regulated (e.g., up- or down-regulated) compared to expression patterns from non-disease state cells, such that exposure of a target cell to a candidate therapeutic agent can result in alteration of nucleic acid expression patterns which more closely resemble the patterns of normal (i.e., non-disease-state) cells, wherein candidate therapeutic agents which show promise in killing or altering target cells are then exposed to normal cells to determine their potential use as a therapeutic agent (e.g., if the candidate agent kills target cells and normal cells, it can be excluded as a possibly useful agent) (interpreting exposure to a library of candidate agents as incubating the cells in the presence or absence of a test compound; determining the number of cells that exhibit a distinguishable phenotype relative to the total population such as by expression pattern; determining selectivity; inhibits or induces the phenotype; and normal cells as viable cells including non-fragmented nuclei, claims 1, 19 and 20) (paragraph [0189]). Clarke et al. teach that cells and cell populations or subpopulations of interest can be further analyzed, wherein cell populations or subpopulations can comprise cells which comprise a portion of the original sample, for example cells which comprise 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10% or more of the original sample, such that using the methods described herein, cell populations or subpopulations of interest can be isolated from heterogeneous samples, such that the isolated populations or subpopulations can be 51%; 52%. 53%, 54%, 55%, 56%, 57%, 58%; 59%, 60%, 61%, 62%, 63%, 64%. 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or 100% free of cells which are not members of the target population or subpopulation (interpreting an original sample, and a portion of the original sample; as well as, interpreting heterogeneous samples including heterogeneous samples in isolated populations or subpopulations as at least two distinguishable sub-populations including those populations-subpopulations comprising isolated populations, populations comprising original cells, heterogeneous populations, subpopulations of interest, and/or populations free of cells that are not target members; and 1% or 99% as determining a number ratio of the cells exhibiting the same distinguishable phenotype, claim 1) (paragraph [0075]). Clarke et al. teach that the development of new and/or refined therapeutic agents can involve analyzing a target cell population (e.g., colon cancer stem cells, breast cancer cells, etc.) to determine nucleic acids which exhibit altered expression profiles as compared to “normal” cells, wherein such cells can be utilized to screen potential therapeutic agents for effects on expression by exposing isolated cells of the target population to candidate agents and testing for altered expression of the genes following exposure (interpreted as incubating the sample in the presence or absence of a test compound; patient response; and selecting a test compound, claims 1 and 22) (paragraph [0108]). Clarke teaches that a statistical analysis step can then be performed to obtain the weighted contribution of the set of genes including nearest shrunken centroids analysis can be applied as described in Tibshirani et al. (2002) P.N.A.S 99.6567-6572 (interpreted as generating, utilizing a machine learning model, a first and second number from a microscopy images, claim 1) (paragraph [0058]), wherein it is known that conventional diagnosis of cancer is based on the morphological appearance of stained tissue specimens in the light microscope; and that statistical methods include linear discriminant analysis, the neural network approach, and principle components regression, which incorporates methods for automatic threshold choice and graphical methods for application of the procedure to the results of an unsupervised clustering procedure as evidenced by Tibshirani (pg. 6567, col 1, first full paragraph; col 2, last partial paragraph; and pg. 6572, col 2, second and third full paragraphs). Clarke teaches that the cell sample to be analyzed is a primary sample, which can be freshly isolated, frozen, cultured, etc., wherein the sample is usually the sample is a heterogeneous mixture of cells, comprising a plurality of distinct cell types, distinct populations of cells, or distinct subpopulations of cells, for example 2, 3, 4, 5, 10, 15, 20 or more cell types, populations; or subpopulations, wherein the sample is a cancer sample from a solid tumor, leukemia, lymphoma, etc., which can be a biopsy, e.g. a needle biopsy, etc., a blood sample for disseminated tumors and leukemias, and the like, such that samples can be obtained prior to diagnosis, through a course of treatment, and the like (interpreted as numbers of cells exhibiting a cancerous viability phenotype when incubated with a compounds; and when not incubated with a compound, claim 1) (paragraph [0043]). Clarke et al. teach that by targeting all populations, one can eliminate a tumor by treating with drugs that affect each different population (interpreted as treating a patient, claim 22) (paragraph [0009], last 3 lines).
Regarding claim 13 (in part), Clarke et al. teach that clinical samples for use in the methods of the invention can be obtained from a variety of sources including blood and bone marrow, wherein a mononuclear fraction (PBMC) is used (interpreted as bone marrow cell; and cells derived from PBMCs, claim 13) (paragraph [0088], lines 1-4 and 13-14).
Regarding claim 5, Clarke et al. teach that candidate agents of interest for screening include known and unknown compounds that encompass numerous chemical classes, primarily organic molecules including: (i) complex biological agents; (ii) organic molecules comprising functional groups necessary for structural interactions; (iii) biomolecules including peptides; polynucleotides, saccharides, fatty acids, steroids, purines, pyrimidines, derivatives, structural analogs or combinations thereof; (iv) compounds that have known functions (e.g., relief of oxidative stress; but can act through an unknown mechanism or act on an unknown target; (v) pharmacologically active drugs; (vi) genetically active molecules; (vii) chemotherapeutic agents, hormones or hormone antagonists, etc.; (viii) all of the classes of molecules described above including samples of unknown content, such as complex mixtures of naturally occurring compounds derived from natural sources such as plants, fungi, bacteria, protists or animals (interpreting test compounds to comprise one or more chemical substances, claim 5) (paragraphs [0116]-[0118]).
Clarke et al. do not specifically exemplify a non-adherent cell monolayer (claim 13, in part).
Regarding claim 13 (in part), Ingram et al. teach a non-adherent cell support for use as a substrate in fluidic chambers used for cell culturing and assays, wherein the non-adherent cell support allows for the formation of sphere cultures from single cells, which can better mimic primary tumor-like behavior in the study of cancer stem cells (interpreted as a non-adherent monolayer culture, claim 13) (Abstract, lines 1-5), wherein it is known that cancer cell lines cultured in 2D monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner as evidenced by Lovitt et al. (Abstract). Ingram et al. teach that cell heterogeneity is a hallmark of multi-cellular life with heterogeneity being provided by asymmetric and symmetric division, and cancer has been shown to be no different, wherein the presence and behavior of cancer subtypes known as cancer stem cells (CSCs) or tumor initiating cells (TICs) are of great interest when screening cancer targeting therapeutic agents, and these CSCs/TICs are linked to drug resistance in cancer and can be the culprit for reemergence after therapy, such that drugs that target and selectively remove these drug resistance sub-populations have been shown to have great therapeutic potential, wherein the 3D spheroid provides for stronger correlations between drug effects and eventual patient outcomes (paragraphs [0004]; and [0006], lines 8-9). Ingram et al. teach a method of making a microfluidic device having a non-adherent cell support for use in cell assays, comprising the steps of providing a silicon wafer, spin coating and patterning said silicon wafer with photoresist, deep reactive ion etching the coated silicon wafer to produce a patterned mold, pouring an uncured biocompatible material onto the patterned mold resulting in an uncured non-adherent cell support curing the uncured non-adherent cell support, releasing the cured non-adherent cell support from the patterned mold, and joining the non-adherent cell support to one or more microfluidic chambers, wherein the non-adherent cell support disclosed herein allows for non-adherent cell culturing and assays using a hydrophobic support surface for the cells, such that useful applications include single cell spheroid formation inside a high-throughput microfluidic chip capable of long term chemical free non-adherent mammalian cell culture (interpreted as cultured as a non-adherent cell monolayer, claim 13) (paragraphs [0012]; and [0050], lines 1-6). Ingram et al. teach high-throughput arrays as shown in FIGS. 20 and 21 which can be useful in a variety of cell culture assays including those used for single cell phenotyping, clonal analysis, and spheroid drug assays (paragraph [0065], lines 35-38). Ingram teaches confocal laser microscopy images illustrating a non-adherent cell support comprising different shapes (interpreted as microscopy imaging, claim 1) (paragraph [0056], lines 7-9; and Figures 7 and 8).
“It is prima facie obvious to combine two compositions each of which is taught by the prior art to be useful for the same purpose, in order to form a third composition to be used for the very same purpose.... [T]he idea of combining them flows logically from their having been individually taught in the prior art.” In re Kerkhoven, 626 F.2d 846, 850, 205 USPQ 1069, 1072 (CCPA 1980). Moreover, “it is prima facie obvious to combine prior art elements according to known methods to yield predictable results; the court held that, "…a conclusion that a claim would have been obvious is that all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art. KSR International Co. v. Teleflex Inc., 550 U.S. ___, ___, 82 USPQ2d 1385, 1395 (2007); Sakraida v. AG Pro, Inc., 425 U.S. 273, 282, 189 USPQ 449, 453 (1976); Anderson’s-Black Rock, Inc. v. Pavement Salvage Co., 396 U.S. 57, 62-63, 163 USPQ 673, 675 (1969); Great Atlantic & P. Tea Co. v. Supermarket Equipment Corp., 340 U.S. 147, 152, 87 USPQ 303, 306 (1950)”. Therefore, in view of the benefits of using spheroids as a high throughput method for cancer drug screening as exemplified by Ingram et al., it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of screening agents for biological activity in a plurality of cell samples as disclosed by Clarke et al. to include the three-dimensional non-adherent sphere cultures from single cells as taught by Ingram et al. with a reasonable expectation of success in producing a method for high throughput screening of drug targets and/or drug resistant populations of cells; and/or in detecting, identifying, and/or quantifying differential cell phenotypes including gene expression profiles, pathway functioning, cell type or morphology and/or marker expression useful for the prognosis; diagnosis and/or treatment of diseases such as cancer.
Thus, in view of the foregoing, the claimed invention, as a whole, would have been obvious to one of ordinary skill in the art at the time the invention was made. Therefore, the claims are properly rejected under 35 USC §103 as obvious over the art.
Response to Arguments
Applicant’s arguments filed October 10, 2025 have been fully considered but they are not persuasive. Applicants essentially combines the arguments for all 35 USC 103 rejections. See below.
(2) The rejection of claims 1, 5, 12, 13 and 19-22 is maintained under 35 U.S.C. 103 as being unpatentable over Superti-Furga et al. (US Patent No. 11486876, issued November 1, 2022; also published as International Application WO2016046346, published March 31, 2016; of record) in view Clarke et al. (US Patent Application Publication No. US20160312302, published October 27, 2016; of record).
Regarding claims 1, 5, 13 and 19-22, Superti-Furga teaches that the invention relates to peripheral blood mononuclear cell (PBMC) monolayers or bone-marrow cell monolayers, and methods for its culture; and also relates to screening methods comprising the PBMC monolayer or bone marrow cell monolayer of the invention for determination of response or lack of response of a disease to a therapeutic agent and/or drug screening methods; as well as, methods for diagnosing a disease or predisposition to a disease in a PBMC donor or bone-marrow cell donor comprising the PBMCs/bone marrow cells cultured according to the method of the invention and/or to methods for determining whether the disease is likely to respond or is responsive to treatment with a therapeutic agent (interpreting bone marrow and bone marrow cell monolayer as a tissue sample; as cultured as non-adherent cell monolayers; and determining a patient response, claims 1, 13 and 22) (Abstract). Superti-Furga teaches monolayers obtained or obtainable by any method provided herein (interpreted as providing a tissue sample, claim 1a) (pg. 3, last full paragraph, lines 12-13). Superti-Furga teaches that none of the techniques known in the art take advantage of the entire patient sample, which includes healthy and cancerous cells (i.e., for a global perspective) (interpreted as a sample comprising at least two distinguishable subpopulations including cancerous and non-cancerous cells; and dividing the sample into a first part and a second part, claims 1a and 1b) (pg. 4, first partial paragraph, lines 5-7). Superti-Furga teaches that there is a need for means and methods for providing systems that reflect the in vivo situation, whereby these systems can be used for PBMCs and/or bone marrow cells to reflect the in vivo situation and/or an in vivo representation of cells, whereby the systems can be used in methods of diagnosis of disease or predisposition to disease, in drug screenings, and in the assessment of treatment results or predispositions to treatment (pg. 4, first full paragraph). Superti-Furga teaches provides an in vitro produced peripheral blood mononuclear cell (PBMC) monolayer or bone-marrow cell monolayer, wherein in said monolayers natural-occurring cell-cell interactions and/or the membrane integrity are maintained during formation of said monolayer (interpreted as non-fragmented nuclei, claim 20) (pg. 4, last full paragraph, lines 1-4). Superti-Furga teaches that the PBMC monolayers and bone-marrow cell monolayers of the present invention reflect a physiologically relevant state, as further evidenced by the ratio/number of cells present in the PBMC monolayers and bone-marrow cell monolayers of the invention, which reflect cell ratios/numbers found in vivo (interpreted as determining a number ratio of a number of cells in the first part and the second part; and total population of cells, claim 1d) (pg. 8, first partial paragraph). Superti-Furga teaches that in order to maintain numbers/ratios of cells of each subpopulation, pipetting is reduced and samples used comprise adherent and non-adherent cells (interpreted as ratios of numbers of cells; and non-adherent cell monolayers, claims 1 and 13) (pg. 10, first full paragraph, lines 1-3). Superti-Furga teaches that the present invention relates to a pharmaceutical composition comprising a compound for use in the treatment of a disease, in particular a hematologic malignancy and/or a malignancy of myeloid and/or lymphoid tissue of an individual (interpreted as cancerous), wherein said pharmaceutical composition is selected from at least two or more test compounds (interpreted as test compounds), which are tested in an assay comprising the steps of: (a) preparing the hematopoietic cell monolayer, in particular PBMC or bone-marrow cell monolayer, of the invention using hematopoietic cells, in particular PBMCs or bone marrow cells, of said individual; (b) determining one or more biological functions of one or more subpopulations comprised in the hematopoietic cell monolayer, in particular PBMC monolayer or bone marrow cell monolayer; (c) adding one of the at least two or more test compounds to the hematopoietic cell monolayer; and (d) determining/tracking/assessing/verifying changes of said one or more biological functions of the one or more subpopulations comprised in the hematopoietic monolayer, wherein the assay is repeated for each of the at least two or more compounds and wherein the compound having the most advantageous effect on said one or more biological functions of said one or more subpopulations is selected for treatment of said individual; and that a physiologically-relevant state can be characterized by cell-cell interactions maintained during formation of the monolayer and/or viability of cells comprised in the monolayer and/or membrane integrity maintained during formation of the monolayer (interpreted as cancerous and non-cancerous cells; test compounds; one or more chemical substances; assay with and without the test compound; two distinguishable subpopulations; non-adherent cell monolayer; and wherein the distinguishable phenotype is the number of viable cells, claims 1, 5, 13, and 20) (pg. 14, first and second full paragraphs). Superti-Furga teaches that the viability of cells comprised in the monolayers of the invention can be determined, assessed and/or verified using methods well-known in the art, wherein the skilled person is well-aware of methods how to determine/assess/verify the stadium of a cell, for example whether a cell is viable, live, dead or undergoing a process changing its stadium, for example dying as in apoptosis or necrosis including dyes/labels that are selective for cells with non-intact membranes or dyes/labels selective for late stage cell death or early apoptosis (interpreted as determining a number ratio of a number of cells in a first subpopulation of that of at least two distinguishable subpopulations of cells that exhibit the distinguishing phenotype; and determining a selectivity ratio, claims 1d and 1e) (pg. 18, last partial paragraph). Superti-Furga teaches that for high-throughput applications, an automated method is used to determine/track/assess/verify changes of viability and/or cell-cell interactions including identifying subpopulations using detectable labels, such that the fraction (e.g., ratio of cells of a subpopulation that is in contact with a further cells) is determined and the resulting number is compared to what would be expected by a random distribution function, wherein an interaction score can be calculated, which determines whether interaction is random or directed (interpreting assessing changes in viability as determining a selectivity of the test compound to induce the distinguishable phenotype; the phenotype is viability; and interpreting high-throughput label detection as encompassing automated microscopy, claims 1 and 19) (pg. 19, first full paragraph, 6-8 and 14-19). Superti-Furga teaches that the PBMC monolayers described herein can be composed of normal, e.g., healthy, cells and, where isolated from a sample obtained from a donor having a disease or predisposed to a disease, disease cells, e.g., the cells can thus have an abnormal phenotype or genotype themselves or representative of a disease state (e.g., having increased or decreased concentration relative to expected concentrations in a healthy individual), such that the PBMC monolayers described herein contain healthy cells or a healthy cell population that can act as a self-control in the methods provided herein, wherein the therapeutic response of the disease-state cells can be directly compared to the response of the healthy cells in the same sample, and without the need for comparison to baseline responses and/or without the need for establishing separate control cultures (interpreted as cancerous and non-cancerous cells; and determining a patient response, claims 1 and 22) (pg. 23, first full paragraph, lines 5-15). Superti-Furga teaches that the method for diagnosing a disease or predisposed to a disease and/or determining whether a subject suffering from a disease will respond or is responsive to a treatment with a therapeutic agent comprises: (a) isolating PBMCs from a blood sample obtained from a subject/donor; (b) incubating the PBMCs; (c) contacting said PBMCs with said therapeutic agent; and (d) assessing the response of the PBMCs to the therapeutic agent (interpreted as incubating the second part in the presence of the test compound, claim 1c) (pg. 23, last partial paragraph; and pg. 24, first partial paragraph, line 1). Superti-Furga teaches that the described methods require fewer cells and therefore less patient material, less liquid volume, and nearly no human intervention; pharmacoscopy thereby greatly increases the number of molecular perturbations which can be tested in parallel and yields more detailed assessments including without the need to sort cancerous cells from the inherent healthy populations, pharmacoscopy can track drug mediated biomarker changes while controlling, in parallel, the off-target drug effects (interpreted as a mixture of cancerous and non-cancerous cells, claim 1a) (pg. 27, first partial paragraph, lines 12-21). Superti-Furga teaches that the PBMC monolayer of the invention and the methods can also be used for following the course of a disease during treatment of a disease or in the absence of treatment (interpreted as the presence and absence of a test compound, claim 1c) (pg. 47, first full paragraph, lines 20-22). Superti-Furga teaches that the screening method determines population specific effects of drugs (interpreted as selectivity of the test compound, claim 1e) (pg. 64, first partial paragraph). Superti-Furga teaches a system for the detection of selection of compounds that specifically targets various subpopulations of PBMCs even using a healthy donor, which opens the door to the ability to begin screening even more libraries for even more specific population-targeting drugs (interpreted as selectivity of the test compound, claim 1e) (pg. 65, last full paragraph). Superti-Furga teaches that Figure 3 illustrates the results of a large viability screen in PBMCs as a measurement of global cell viability change, which is normalized to the ability of the drug to specifically target a single stained population, wherein all 1500 compounds sorted on cell number, and comparing the total number of PBMCs killed to the “specificity” of the ability of the compound to target one or more specific cell types present in the staining reduced and provided with a “specificity score”, such that the compounds highlighted are key anti-cancer candidate treatments (interpreting the ratio as determining the cell numbers reduced by dividing (i) by (ii); and interpreting the specificity score as a selectivity ratio less than 1, wherein the test compounds inhibits or reduces the distinguishable phenotype; cell viability; one or more chemical substance; and non-fragmented nuclei, claims 1d-e, 5, 19 and 20) (pg. 54, last partial paragraph, Figure 3; pg. 64, last partial paragraph; and Figure 3). Figure 3 is shown below:
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Superti-Furga et al. teach that antibodies conjugated to fluorescent markers are added, along with DAPI for nuclear detection, and the plates imaged on an automated microscope (interpreted as using automated microscopy; and determining the number of non-fragmented nuclei, claims 19 and 20) (pg. 56, first full paragraph; and Figure 11). Superti-Furga et al. teach that the sensitivity of the cancer cells (CD34 and pSTAT5 positive) to each drug was compared to the sensitivity on the healthy cells (NOT CD34 and pSTAT5 positive), wherein all results were normalized to the control, DMSO alone (interpreting the control as being incubated in the absence of test compound); and that Figure 12A shows the results of each dot is a drug, wherein these results are compared to the effect of healthy cells (i.e., marker negative) within the monolayer; and that Figure 12B shows data for one drug that was extracted, and highlights the per/cell phenotype of single treatment (right) vs control (left) from a treated monolayer (specific DC34 cell depletion) using counting cell number; that Figure 12C determines drug effect as to “prior art” only counting general cell death after incubation with drugs; and (C) total viable PBMCs after treatment with each drug screened for in (B) showing that, without the use of pharmacoscopy, the top hit is not the same (with no comparison as to what is sick or what is healthy) (interpreting the ratio as determining the cell numbers reduced by dividing (i) by (ii); and interpreting the specificity score as a selectivity ratio less than 1, wherein the test compounds inhibits or reduces the distinguishable phenotype; extracting data from microscopy images; cell viability; one or more chemical substance; a first number of cancerous cells and a second number of cancerous cells; generating a compound viability phenotype to an overall number of cells exhibiting the viability phenotype and non-fragmented nuclei, claims 1, 5, 19 and 21) (pg. 69, Example 9, first full paragraph; and Figure 12A-C). Figure 12A-C are shown below:
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Superti-Furga et al. teach that blood samples are treated shortly after isolation, which has several advantages: drug specificity and toxicity to cancer cells is directly compared to that of the healthy cells from the patient, and complex aspects of drug responses can be measured that arise from the cell-cell interactions present in human blood (interpreted as a tissue sample comprising at least 1% cancerous cells, at least 1% non-cancerous cells; and determining a patient response, claims 1 and 22) (col 33, lines 5-10). Superti-Furga et al. teach that more detailed assessments are needed without the need to sort cancerous cells from the inherent healthy populations, pharmacoscopy can track drug mediated biomarker changes while controlling, in parallel, the off-target drug effects, such that these important controls are done by tracking the viability of the healthy cells from the same donor, present in the same well, and in the same imaging field, to the viability and biomarker analysis of the targeted-cell populations (interpreted as dividing a tissue sample into two parts; distinguishable subpopulations of cells; as at least 1% cancerous and 1% non-cancerous cells; and viability, claims 1, 19 and 20) (pg. 27, first partial paragraph). Superti-Furga et al. teach that the PBMC monolayers described herein can be composed of normal, e.g., healthy, cells and, where isolated from a sample obtained from a donor having a disease or predisposed to a disease, disease cells, e.g., the cells can thus have an abnormal phenotype or genotype themselves or representative of a disease state (e.g., having increased or decreased concentration relative to expected concentrations in a healthy individual), such that the PBMC monolayers described herein contain healthy cells or a healthy cell population that can act as a self-control in the methods provided herein, wherein the therapeutic response of the disease-state cells can be directly compared to the response of the healthy cells in the same sample, and without the need for comparison to baseline responses and/or without the need for establishing separate control cultures (interpreted as a distinguishable phenotype; healthy cells and 1 % cancerous cells; PBMC monolayers and bone marrow monolayers; and determining a patient response, claims 1, 13 and 22) (pg. 23, first full paragraph). Superti-Furga et al. teach cellular response to the same perturbation (e.g., interpreted as a compound) can be characterized, wherein the complexity of cellular heterogeneity (in reference to the investigation of degree to which cancer cells react to anti-cancer drugs) reveals functional significance to the broad effect patients can have on a cellular level during chemotherapy (interpreted as a first number of cancerous cells; a second number of non-cancerous cells; and generating a compound-cancer selectivity metric, claim 1) (col 5, lines 50-56). Superti-Furga et al. teach that the PBMC monolayers and bone-marrow cell monolayers of the present invention reflect a physiologically-relevant state, as further evidenced by the ratio/number of cells present in the PBMC monolayers and bone-marrow cell monolayers of the invention, which reflect cell ratios/numbers found in vivo (interpreted as generating viability phenotype measure; a first number of cancerous cells; and a second number of non-cancerous cells) (col 5, lines 25-30). Superti-Furga et al. teach that a cell sample, in particular the monolayer of the invention, comprises cells of different subpopulations, wherein each cell of each subpopulation can be in a state of, inter alia, living, dead and/or dying, wherein the mono-layers of the present invention, the number/ratio of cells in each state, i.e. living, dead or dying, and each subpopulation preferably corresponds to the number/ratio that is found in vivo (interpreted as a viability phenotype, claim 1) (col 6, lines 31-38). Superti-Furga et al. teach that diseases including hematologic malignancies, number/ratios of subpopulations of cells comprised in PBMCs and/or bone-marrow cells, are well-documented (interpreted as generating viability phenotype measure; a number of cancerous cells; bone marrow cells or a monolayer of PMBCs; and a viability phenotype, claims 1 and 13) (col 6, lines 61-63). Superti-Furga et al. teach isolating peripheral blood mononuclear cells (PBMCs); incubating PBMCs in the form of a monolayer, such that the density maintains the PBMC monolayer culture during the entire culture time of the monolayer such as from introduction into the culture device until final processing prior to imaging, wherein the maximum density is such that the total number of cells (a) introduced into the culture device or (b) expected to be present in the culture device subsequent to culturing and prior to processing for imaging does not exceed that number present at maximum density for the cell PBMC monolayer as described herein including a density of about 100 cells/mm2 to about 30000 cells/mm2 (interpreted as incubating; generating viability phenotype measure; a first number of cancerous cells; a second number of non-cancerous cells; a selectivity metric; generating microscopy images; and a viability phenotype, claim 1) (col 13, lines 17-32). Superti-Furga et al. teach that Figure 3 illustrates the results of a large-scale viability screen in PBMCs; compounds sorted on cell number reduced and “specificity score”, wherein compounds highlighted are key anti-cancer candidate treatments (interpreted as generating viability phenotype measure; a compound-cancer selectivity metric; and selecting a compound for therapeutic treatment) (col 35, lines 13-16; and Figure 3). Superti-Furga et al. teach that the open-source software CellProfiler can be used for the identification of marker-positive cells (such as CD34+ progenitor cells or viability dye positive cells) can be performed by machine learning using the opensource software CellProfiler Analyst ( e.g. version 2.0) and double- or triple-positive cells can be identified by a sequential gating strategy, wherein plate-overviews for further analysis and hit selection can be created using CellProfiler Analyst (interpreted as generating microscopy images; and extracting numbers of cancerous cells using a machine learning model; and selecting compounds) (col 29, lines 65-67; and col 30, lines 1-5). Superti-Furga et al. teach that Figure 3 shows 1500 compounds, each represented by a dot, comparing the total number of PBMCs killed to the "specificity" of the ability for the compound to target one or more specific cell types present in the staining (interpreted as generating viability phenotype measure; a compound-cancer selectivity metric; and selecting a compound for therapeutic treatment) (col 41, lines 20-23; and Figure 3). Superti-Furga et al. teach that Figure 12B highlights the per/cell phenotype of single drug treatment versus control from a treated monolayer; while Figure 12C illustrates the determination of the drug effect as to only counting cell number, and general cell death after incubation with drugs (but not including a comparison as to what cell is sick or what cell is healthy), such that only cell death/cell number is determined (interpreted as generating viability phenotype measure; a first number of cancerous cells; a second number of non-cancerous cells; and compound-cancer selectivity metric) (col 44, lines 35-48; and Figures 12B and 12C). Superti-Furga et al. teach that Figure 5 illustrates a heat map of the top hit HDACi and their population specificity (interpreting a heat map and a microscopy image that is analyzed; generating a compound viability phenotype measure; generating a compound-cancer selectivity metric; and selecting a compound for therapeutic treatment) (col 35, lines 19-20; and Figure 5). Superti-Furga et al. teach that the means and methods provided herein allow the evaluation based on subpopulations comprised in the PBMC monolayers or bone-marrow cell monolayers of the invention using, for example, markers specific for such subpopulations, such that a treatment decision can be reached based on the effect of a drug on a particular subpopulation or subpopulations comprised in the PBMC monolayer or bone marrow cell monolayer of the invention including whether a patient is responsive to treatment including treatments such as Ruxolitinib and Azacitidine (interpreted as generating viability phenotype measure; a compound-cancer selectivity metric; selecting a compound for therapeutic treatment; and Ruxolitinib and Azacitidine as chemical substances for treating cancer; PMBC monolayer and bone marrow cells; and determining a patients responsiveness to treatment, claims 1, 5, 13 and 22) (col 12, lines 6-23).
Superti-Furga et al. do not specifically exemplify additional and/or different cancers or tissue samples (claim 1, in part).
Regarding claim 1 (in part), Clarke et al. teach methods for the diagnosis and prognosis of disease by analyzing expression of a set of genes obtained from single cell analysis, such that classification allows optimization of treatment, and determination of whether to proceed with a specific therapy, and how to optimize dose, choice of treatment, and the like, wherein single cell analysis also provides for the identification and development of therapies which target mutations and/or pathways in disease-state cells (Abstract). Clarke et al. teach that early disease diagnosis is of central importance to halting disease progression, and reducing morbidity, such that analysis of a patient samples to identify gene expression patterns provides the basis for more specific, rational disease therapy that can result in diminished adverse side effects relative to conventional therapies; and can provide a basis of therapeutics, diagnostics, prognostics, and/or thermometric; as well as, avoiding unnecessary therapies (paragraph [0006]). Clarke et al. teach analyzing a heterogeneous tumor biopsy from a subject, comprising: randomly partitioning cells from the biopsy into discrete locations; performing transcriptome analysis on at least 50 genes of the individually partitioned cells; and using transcriptome data to identify one or more characteristic of the tumor (interpreted as a phenotype), wherein a characteristic identified can be the presence, absence, or number of cancer cells; the presence, absence or number of stem cells, early progenitor cells, initial differentiated progenitor cells, late differentiated progenitor cells, or mature cells; the effectiveness of a therapeutic agent in eliminating one or more of the cells; and/or the activity of a signaling pathway, for example, a pathway specific to a cancer stem cell, a differentiated cancer cell, a mature cancer cell, or combination thereof; and the method can further comprise the step of using the characteristic to diagnose a subject with cancer or a cancer stage (interpreted as providing a sample; at least two sub-populations of cells divided into two parts; determining the number of cells exhibiting the same phenotype in the presence or absence of a test compound; and determining selectivity by dividing (i) through (ii), claim 1) (paragraph [0013]). Clarke et al. teach that a single cell analysis device (SCAD) is modular and can perform the following steps in an integrated, fully automated fashion including: (1) digestion of the tissue; (2) separation of live cells from the debris; (3) staining, wherein the filtered single cell suspension is optionally stained using appropriate surface markers in a compartment of the microfluidic device including staining with up to five different markers can be useful in obtaining a high purity population of cancer cells; and (4) sorting, wherein he stained single-cell suspension is flowed into the next compartment of the microfluidic device to sort out the cancer cells from the rest of the cells (interpreted as providing a sample comprising distinguishable phenotypes; dividing the sample into at least two parts; encompassing non-fragmented nuclei; and fully automated as including automated microscopy, claims 1, 19 and 20) (paragraph [0050]).Clarke et al. teach that agents are screened for biological activity by adding the agent to at least one and usually a plurality of cell samples, usually in conjunction with cells lacking the agent, such that the change in parameters in response to the agent is measured, and the result evaluated by comparison to reference cultures, e.g. in the presence and absence of the agent, obtained with other agents, etc. (paragraph [0122]).
“It is prima facie obvious to combine two compositions each of which is taught by the prior art to be useful for the same purpose, in order to form a third composition to be used for the very same purpose.... [T]he idea of combining them flows logically from their having been individually taught in the prior art.” In re Kerkhoven, 626 F.2d 846, 850, 205 USPQ 1069, 1072 (CCPA 1980). Moreover, “it is prima facie obvious to combine prior art elements according to known methods to yield predictable results; the court held that, "…a conclusion that a claim would have been obvious is that all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art. KSR International Co. v. Teleflex Inc., 550 U.S. ___, ___, 82 USPQ2d 1385, 1395 (2007); Sakraida v. AG Pro, Inc., 425 U.S. 273, 282, 189 USPQ 449, 453 (1976); Anderson’s-Black Rock, Inc. v. Pavement Salvage Co., 396 U.S. 57, 62-63, 163 USPQ 673, 675 (1969); Great Atlantic & P. Tea Co. v. Supermarket Equipment Corp., 340 U.S. 147, 152, 87 USPQ 303, 306 (1950)”. Therefore, in view of the benefits of screening agents for biological activity as exemplified by Clarke et al., it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of using PMBC monolayers and/or bone-marrow cell monolayers comprising adherent and non-adherent cells as taught by Superti-Furga et al. to include the method of screening agents for biological activity using a plurality of cell samples exhibiting the same distinguishable phenotype in the presence and absence of the agent as disclosed by Clarke et al. with a reasonable expectation of success in producing a high throughput method for screening drug therapies including for the determination of a response or the lack of a response of a disease to a therapeutic agent in a system that reflects the in vivo situation, which requires 1/10 of the material typically needed such that throughput and speed are maximized; and/or for personalized predictive pharmacology, drug screening and/or therapeutic evaluation including the optimization of personalized drug treatments including drug dose for the treatment of diseases such as cancer.
Thus, in view of the foregoing, the claimed invention, as a whole, would have been obvious to one of ordinary skill in the art at the time the invention was made. Therefore, the claims are properly rejected under 35 USC §103 as obvious over the art.
Response to Arguments
Applicant’s arguments filed October 10, 2025 have been fully considered but they are not persuasive. Applicants essentially combines the arguments for all 35 USC 103 rejections. See below.
(3) The rejection of claims 1, 5, 13, 19 and 20 is maintained, and claims 21 and 22 are newly rejected, under 35 U.S.C. 103 as being unpatentable over Superti-Furga et al. (hereinafter “Superti-Furga”) (International Application WO2016046346, published March 31, 2016; of record) in view of Rashidi et al. (hereinafter “Rashidi”) (International Journal of Cancer Management, April 2017, 10(5), 1-7; of record).
The teachings of Superti-Furga regarding claims 1, 5, 13 and 19-22 are discussed supra.
Superti-Furga et al. do not explicitly exemplify additional types of cancer cells (claim 1, in part).
Regarding claim 1 (in part), Rashidi teaches that human cancer cells lines were selected and the anti-cancer potential of Cyrtopodion scabrum extract (CsE) on their growth was studied (Abstract, Methods). Rashidi teaches that cancer is the leading cause of death world-wide including lung cancer, breast cancer, and colorectal cancer (pg. 1, col 1; first full paragraph, lines 1-6). Rashidi teaches that SW742 and HCT116 (colon cancer), HepG2 (liver cancer), Hep2 (head and neck cancer), LNcap (prostate cancer) and MKN45 (stomach cancer) cell lines were cultured in DMEM or RPMI-1640 (pg. 2, col 1, third full paragraph). Rashidi teaches a Survival Percentage and Selectivity Index (SI), such that to calculate the survival percentage, the following formula was used:
Survival Percentage = (OD treatment /OD control) x 100
IC50 values (i.e. the extract concentration that exerts 50% inhibition with respect to untreated cells) were determined for all the cell lines; and the selectivity index (SI), which indicates the cytotoxic selectivity (i.e. drug safety) for Cyrtopodion scabrum extract (CsE) against cancer cells versus normal cells, was calculated from the following formula:
[AltContent: connector] Selectivity Index = IC50 calculated for normal
IC50 calculated for cancer
wherein SI values more than 2 were considered as high selectivity (interpreted as generating a viability phenotype measure; generating a compound-cancer selectivity metric of the test compound; generating a non-test compound viability phenotype measure; inducing the distinguishable phenotype in the first subpopulation of cells over the rest of the at least two distinguishable subpopulations of cells by dividing the number ratio for (i) by the number ratio of (ii); wherein the test compound selectively induces the distinguishable phenotype for the determined selectivity ratio greater than 1; comparing the first number and the second number; and inhibits the distinguishable phenotype for determined selectivity in a ratio of less than 1, claim 1e) (pg. 2, col 2; first full paragraph). Rashidi teaches an apoptosis induction assay, wherein SW742 cells (4 x 106) were seeded into each 100 mm Petri dishes and incubated for 12 hours in a CO2 incubator, and the old media were replaced by different concentrations of CsE (250, 500 and 1000 mg/mL, representative of IC50, 2 x IC50 and 4 x IC50, respectively), 5-FU (50 mg/mL) as positive control, and intact media as negative control in each corresponding Petri dish, wherein the plates were then incubated in a 5% CO2 incubator at 37°C for 72 hours and prepared for DNA fragmentation assay or cell cycle analysis (interpreted as incubating cells in the presence or absence of the test compound; and incubating, claim 1c) (pg. 2, col 2, second full paragraph). Rashidi et al. teach that it was concluded that compared to 5-FU, the common chemotherapy drug, with a very low SI values (< 0.18), gecko extract is a better candidate for growth suppression of all the examined cell lines with SI values > 1 (interpreted as generating a viability phenotype measure; generating a compound-cancer selectivity metric of the test compound; comparing the first number and the second number; greater than 1 or less than 1, claim 1) (pg. 5, col 1, first partial paragraph).
“It is prima facie obvious to combine two compositions each of which is taught by the prior art to be useful for the same purpose, in order to form a third composition to be used for the very same purpose.... [T]he idea of combining them flows logically from their having been individually taught in the prior art.” In re Kerkhoven, 626 F.2d 846, 850, 205 USPQ 1069, 1072 (CCPA 1980). Moreover, “it is prima facie obvious to combine prior art elements according to known methods to yield predictable results; the court held that, "…a conclusion that a claim would have been obvious is that all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art. KSR International Co. v. Teleflex Inc., 550 U.S. ___, ___, 82 USPQ2d 1385, 1395 (2007); Sakraida v. AG Pro, Inc., 425 U.S. 273, 282, 189 USPQ 449, 453 (1976); Anderson’s-Black Rock, Inc. v. Pavement Salvage Co., 396 U.S. 57, 62-63, 163 USPQ 673, 675 (1969); Great Atlantic & P. Tea Co. v. Supermarket Equipment Corp., 340 U.S. 147, 152, 87 USPQ 303, 306 (1950)”. Therefore, in view of the benefits of testing a candidate compound against different cancer cell lines for anti-cancer potential including selective cytotoxicity and apoptosis-induction as exemplified by Rashidi, it would have been prima facie obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of using PBMC monolayers or bone-marrow cell monolayers to test the selectivity of one or more test compounds and/or pharmaceutical anti-cancer compositions as disclosed by Superti-Furga to include the human cancer cells and/or the method of calculating the selectivity of potential anti-cancer drugs with respect to untreated cells as taught by Rashidi, with a reasonable expectation of success in assessing the selectivity of potential and/or existing anti-cancer therapies; in assessing the viability of cancer cells and/or normal cells to a particular treatment; in assessing whether a person suffering from a disease such as cancer will be responsive to treatment with a particular therapeutic agent or regimen; and/or in performing drug screening assays to assess the selectivity of anti-cancer agents using in vitro produced physiologically-relevant cell monolayers that allow for the maintenance of cell membrane integrity and cell-cell interactions.
Thus, in view of the foregoing, the claimed invention, as a whole, would have been obvious to one of ordinary skill in the art at the time the invention was made. Therefore, the claims are properly rejected under 35 USC §103 as obvious over the art.
Response to Arguments
Applicant’s arguments filed October 10, 2025 have been fully considered but they are not persuasive. Applicants essentially assert that: (a) Clarke fails to teach any of the limitations are recited in claim 1, lines 20-44 (Applicant Remarks, pg. 12, last partial paragraph through pg. 14, first partial paragraph); (b) Ingram, Lovitt, and Tibshirani fail to remedy the deficiencies of Clark as none of these references describe the above recited claim limitations (Applicant Remarks, pg. 14, first full paragraph); and (c) Superti-Furga fails to teach the limitations as recited in claim 1, lines 24-44 including in combination with Clarke or Rashidi (Applicant Remarks, pg. 14, last full paragraph through pg. 17).
Regarding (a), although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26USPQ2d 1057 (Fed. Cir. 1993). Moreover, none of the references has to teach each and every claim limitation. If they did, this would have been anticipation and not an obviousness-type rejection. One cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). As noted in MPEP 2112.01(I),
where the claimed and prior art products are identical or substantially identical in structure or composition, or are produced by identical or substantially identical processes, a prima facie case of either anticipation or obviousness has been established. In re Best, 562 F.2d 1252, 1255, 195 USPQ 430, 433 (CCPA 1977). "When the PTO shows a sound basis for believing that the products of the applicant and the prior art are the same, the applicant has the burden of showing that they are not." In re Spada, 911 F.2d 705, 709, 15 USPQ2d 1655, 1658 (Fed. Cir. 1990).
Applicant’s assertion that Clarke fails to teach any of the limitations are recited in claim 1, lines 20-44, is not found persuasive. Moreover, Applicant has failed to address the rejections based on the teachings of the combination of both references including Clarke and Ingram including what is not taught by the combined references. Please see the Examiner’s response in the Office Acton mailed July 17, 2025. Applicant did not distinctly and specifically point out the supposed errors in the Examiner’s action as required by 37 CFR 1.111(b). Thus, the claims remain rejected for the reasons already of record.
Regarding (b), please see the discussion supra regarding the Examiner’s response to Applicant’s arguments. Applicant’s assertion that Ingram, Lovitt, and Tibshirani fail to remedy the deficiencies of Clark as none of these references describe the above recited claim limitations of claim 1, lines 20-44, is not found persuasive. Please see the Examiner’s response in the Office Acton mailed July 17, 2025. Applicant did not distinctly and specifically point out the supposed errors in the Examiner’s action as required by 37 CFR 1.111(b). Thus, the claims remain rejected for the reasons already of record.
Regarding (c), please see the discussion supra regarding the Examiner’s response to Applicant’s arguments. Applicant’s assertion that Superti-Furga does not teach the limitations of claim 1, lines 24-44 including in combination with Clarke or Rashidi, is not found persuasive. Moreover, Applicant has failed to address the rejections based on the teachings of the combination of both references including the combined references of Superti-Furga and Clarke including what is not taught by the combined references. Please see the Examiner’s response in the Office Acton mailed July 17, 2025. Applicant did not distinctly and specifically point out the supposed errors in the Examiner’s action as required by 37 CFR 1.111(b). Thus, the claims remain rejected for the reasons already of record.
The Examiner suggests that Applicant amend the claims to recite specific limitations that result in the identification and selection of specific active test compounds for the treatment of a specific type of cancer using the images, phenotype measures, ratios, threshold values, and selectivity metrics, followed by the administration of a specific treatment, drug, or class of drugs.
The Examiner suggests that Applicant address each 35 USC 103 rejection individually; and indicate the specific limitations Applicant believes are not taught by the combined references.
Conclusion
Claims 1, 5, 13 and 19-22 are rejected.
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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/AMY M BUNKER/Primary Examiner, Art Unit 1684