DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Priority
Acknowledgment is made of the present application as a proper National Stage (371) entry of PCT Application No. PCT/US2022/048753, filed 11/02/2022, which claims benefit under 35 U.S.C. 119(e) to provisional application Nos. 63/371,355, filed 08/12/2022 and 63/275,253, filed 11/03/2021.
Information Disclosure Statement
The information disclosure statements (IDS) filed 07/22/2024 and 10/10/2025 are considered, initialed and are attached hereto.
Status of the Claims
Claims 1-2, 32, 39, 42, 44, 57, 59, 63, 68, 73, 75, 80-81, 94, 108, 110, 116 and 122-123 are pending; claims 3-31, 33-38, 40-41, 43, 45-56, 58, 60-62, 64-67, 69-72, 74,76-79, 82-93, 95-107, 109, 111-115, 117-121 are canceled; claim 2, 32, 39, 42, 44, 57, 59, 63, 68, 73, 75, 81, 94, 108,1 110 and 116 are amended. No claims are withdrawn.
Claim Objections
Claim 2 is objected to because of the following informalities:
Claim 2 recites among the recited alternative cellular features, “proximity…wherein the two or more extracellular molecules are of the same target or different targets”, the claims do not earlier reference or use the language “target”, rather only “extracellular molecule”. It is suggested Applicant amend the claim in order to use consistent claim language (rather than target refer to extracellular molecule) in the interest of improving clarity of the record.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-2, 32, 39, 42, 44, 57, 59, 63, 68, 73, 75, 80-81, 94, 108, 110, 116 and 122-123 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites at the preamble that the method is “A method of generating a database comprising cellular features from a disease state cell and a non-disease state cell”, the method comprising “imaging a sample” and “generating a database comprising at least one cellular feature of a cell”, the method further recites “determining if the at least one cellular feature is indicative of the disease-state cell or the non-disease state cell”. This last determining step (“determining if the at least one cellular feature is indicative of…”) reads as a step that uses the generated database to achieve a determination. It is not readily clear from the claim language recited if the claimed “method of generating” involves the step of “determining” as indicated, or rather if the “determining step” is a subsequent step of using the database generated.
Furthermore, the claim language is indefinite because the claim both recites a step of “imaging a sample” and “generating a database” as part of the method of “A method of generating a database”, and subsequently determining if the at least on cellular feature (meaning the feature comprised in the database) is indicative of disease or non-disease cell. If it is Applicant’s intention that the “determining step” is distinct from the step of “generating a database”, then it appears that the imaged sample is a test sample and has nothing to do with/is not involved in the step of “generating a database”. This is confusing claim language since the claimed method is recited as “A method of generating a database”, but rather the claim language suggest the method is actually a method of determining if an imaged sample has at least one cellular feature indicative of a diseased-state cell. The claim is indefinite because it is not clear from the recited language what steps are involved in the intended use as set forth by the preamble of the claim, in achieving the intended use of “generating a database” (i.e., the steps for achieving the intended use are unclear).
Claim 2 recites, as an alternative option for the “at least one cellular feature”, the limitation “intensities for an extracellular molecule”. However, this claim limitation is indefinite because an “extracellular molecule” itself is not readily expected or predicted to have an “intensities”. The claim is indefinite because it is unclear what limitation “intensities” places on the claimed extracellular molecule (what this feature is considered to encompass or represent, such that boundaries of what is claimed are unclear).
Claim 2 also recites that the “at least one cellular feature comprises…all or part of a schematic or topical representation of an extracellular molecule on a cell or tissue”, the recited language is indefinite because it is unclear what limits this places on the claim, for example what is encompassed by a schematic or topical representation. It is not clear, for example, if this is related to the imaging of the sample contacted with an antibody, or is this a morphological observation, or what constitutes a “schematic” or “topical representation” beyond merely detecting the presence of the extracellular molecule. Put another way, it is not clear how this is distinct/different from merely “an image of an extracellular molecule” as earlier recited at this claim.
Claim 2 at the end of page 2 (and also top of page 3) recites “an individual extracellular molecule or pairs of extracellular molecules, wherein the individual extracellular molecule or pairs of extracellular molecules are adjacent or in contact with each other”, the claim is indefinite because it is not clear how an “individual” can be ‘adjacent or in contact with each other” since an individual is only a singular species.
Claim 2 at page 3 recites the limitations “oligomerization state” and “clustering state”, it is not clear what is meant or suggested by each of these limitations beyond merely observation of oligomerization or clustering of an extracellular molecule species. It is not clear what is meant by the addition of the limitation “state”, such that one can readily visualize what is and is not encompassed by this language (it is not clear what cellular feature is described by this language).
Claim 2 recites the limitation "the names of proteins clustering with an extracellular molecule” in 5th line from the bottom of page 3 as the “cellular feature”. There is insufficient antecedent basis for this limitation in the claim. The recited language is confusing and it is not readily clear what feature(s) is/are being tracked to indicate diseased from non-diseased state cells.
See also the limitations claim 2 on the end of page 3 and beginning of page 4, each recite “a change”, however the claim language is indefinite because it is not clear a change relative to what standard of measure/feature. For example, the claim does not clearly communicate if this is a change over time, or a change relative to an earlier measure, or merely a change in diseased state compared to non-diseased state.
Claim 2 makes reference to cellular features associated with extracellular molecule(s), however it is unclear from the recited language is the “antibody” (claim 1) is an antibody that is specific for/binds to the referenced extracellular molecule(s) or not (i.e., or if the extracellular molecule(s) recited is/are distinct features from the antibody contacted with sample during the imaging step.
Claim 32, the final limitation recite “or present on the same cell in tissue” referring to the “at least one cellular feature is present on a cell in tissue”. It is not clear what is meant by “or present on the same cell” (same cell as what, as it’s not clear what “same” is in reference to, particularly when the feature is “one” (singular)).
Claim 39, the limitation “predicts the presence of a cancer cell” and “predicts the presence of a normal cell” is indefinite because it is unclear from the language “predicts” if this is the same as indicating presence or if “predicts” is intended to communicate presence of cancer cell may happen (predicts for a future time).
Claim 42 recite “the at least one cellular feature is present on at least two different cells in tissue, and wherein the at least one cellular feature is within a distance or between cell distances of the at least two different cells”; the claim language is indefinite because it is unclear how the feature can be both present on, and between/within a distance between two cells simultaneously. It is not clear what feature this limitation would be describing (what types of cellular features are encompassed by this language).
Claims 57 and 59 are indefinite because it is unclear whether the wherein clauses are describing limitations specific to the claimed step of “generating the database” (i.e., if these limitation are features specific to how/generating the database), or if these limitations describe the sample of the method steps recited at claim 1 (which as discussed above, could be sample on which the database is used in order to achieve the claimed “determining” step as recited at claim 1). It is not readily clear what additional limitations/features the limitations of the claimed “wherein” clause add to the claimed method.
Claim 59 also recites “imaging the database of imaged cellular features”, it is not readily clear what or how one of ordinary skill would “image” the database as claimed. This language is also confusing considering the claimed method is directed to a method of “generating a database”; it is unclear how one would image the database in order to generate the database.
Claim 75 recites “optionally wherein the tissue microarray coverslip, flow cell, chip or microfluidic chamber is formed via a laser microdissection process”, the claimed language is indefinite because generally in the art these solid support substrate components that are a coverslip, flow cell, chip or microfluidic chamber, are not structures typically or conventionally formed using “laser microdissection process”.
Claim 81 recites “comprises an effector domain (e.g., CD3 or CD16A)”, the use of exemplary claim language is indefinite because it is not readily clear from such language if the exemplary limitations are specifically required of the claim (or merely exemplary), making the scope of the claims unclear.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 32, 39, 42, 44, 57, 59, 63, 68, 73, 75, 80-81, 94, 108, 110, 116 and 122-123 are rejected under 35 U.S.C. 103 as being unpatentable over Sugimoto et al., WO2020/081819A1 in view of Hewitt et al., WO2010/083252A3.
Sugimoto et al. teach a method comprising generating a database comprising cellular features from a disease-state cell and non-disease state cell, see specifically Sugimoto teach methods comprising imaging a sample that has been contacted by an antibody using microscopy (see for example, paras [0007]-[0008], steps a and b, see para [0013], b comprises imaging a cell, see also para [0016], see also paras [0017]-[0019], imaging labeled peptide, identifying morphological change in response to macromolecules expressed) and generating a database comprising at least one cellular feature of a cell in the sample and determining if the at least one cell feature (e.g., see para [0016], machine learning algorithm for morphological change, image information for a population positive and negative for the change) is present in a cell (see e.g., para [0089], cancer cell). Sugimoto’s methods encompass determining the morphological change using microscopy, such as super-resolution microscopy (see para [0070]). Sugimoto also describe imaging fluorescently tagged protein, e.g., detecting a protein target (e.g., para [0148], also claims 37-38)
Sugimoto’s description of using a machine learning algorithm comprises generating a collection of images having the morphological change and collection of images not having the change (i.e., a database), Sugimoto’s methods comprise determining if the cellular feature (morphological change) is present or not, and as cited above.
Although Sugimoto et al. does teach a method substantially as claimed, and does teach detecting morphological change in cells such as cancer/tumor cell, Sugimoto fails to teach determining if the cellular feature (i.e., the morphological change) is indicative of the disease-state cell or the non-disease state cell (i.e. cancer or not).
Hewitt et al. teach identifying biomolecules (proteins and nucleic acids) expressed in a sample that are associated with the presence, development or progression of disease, such as cancer (see abstract). See at page 44, paragraph 2, page 78, paragraph 2, quantifying cancer associated proteins with preservation of the morphological structure. See at page 4, paragraph 3, Hewitt et al. teach determining cancer by detecting in sample, level of cancer associated protein (e.g., PTEN, p-AKT, p-mTOR, pMAPK, EGFR, HER2, HER) compared to a non-cancerous sample.
It would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and generated database as taught by Sugimoto et al., in order to label and image a cancer associated biomarker, as in Hewitt et al., in order to determine a cancerous from non-cancerous cell in order to achieve determination of presence, development or progression of a patient’s cancer, the modification a simple substitution of one marker (markers as in Sugimoto) for another (markers detectable as taught by Hewitt), the motivation being to assess one’s cancer. One having ordinary skill in the art would have a reasonable expectation of success because Sugimoto specifically teach the ability to detect a biomarker present in a cancer/tumor sample.
Regarding claim 2, Hewitt as cited above teachings potential biomarkers (e.g., at least EGFR and HER2 can be expressed extracellularly).
Regarding claim 32, see Sugimoto et al. teach detecting biomarker (cell feature) present on a cell in cancer tissue (cited above).
Regarding claim 39, Sugimoto in view of Hewitt as set forth above addresses the feature predicts the presence of cancer, detecting biomarker present in cell with cancer compared to a normal cell (see citations and analyses above).
Regarding claim 42, Sugimoto in view of Hewitt is teaching detection of cancer cells (plural) in a sample, namely cells expressing tumor/cancer specific antigens (see for example cited above, and Hewitt page 11 to 12). As discussed previously above Hewitt also teach detection in samples such as cells in tissue (see also end of page 15 to 16, also Hewitt at page 18, sample).
Regarding claim 44, Sugimoto teach detecting present in a tissue structure (cells within a tissue structure, paras [0089] of Sugimoto, or see further Hewitt, e.g., page 58, last paragraph, page 62 last paragraph), the combination of the cited addressing cancer as a diseased state.
Regarding claim 57, Sugimoto is teaching different samples assessed for common feature/different features, see as Sugimoto is teaching see para [0016], machine learning algorithm for morphological change, image information for a population positive and negative for the change.
Regarding claim 59, the combination of Sugimoto in view of Hewitt addresses at least, characterizing based on intensity of an imaging agent (see addressing for example identifying by labeling with probes that emit an intensity, para [0078], flurophores quantum dots, FRET labels).
Regarding claim 63, Sugimoto teaching microscopy including STORM, GSD, STED (see para [0095]).
Regarding claim 68, the methods of Sugimoto encompass performed on fixed tissue cells (para [0097]).
Regarding claim 73, see as cited previously above, the combination of the cited teaching databased generated to determine diseased cells (tumor cells) from non-diseased state (normal cells).
Regarding claim 75, see also Sugimoto encompass imaging immobilized cells or flowing cells, i.e., in a flow cell (para [0091], and see as cited, can be fixed).
Regarding claims 80 and 81, for the detection of the cancer biomarkers (Hewitt, see referring to the analysis of claim 1 above), Hewitt et al. disclose antibody to the biomarker (see e.g., page 5, last paragraph, see also page 14, probe such as antibodies, see also page 30, second paragraph). See page 58, second paragraph e.g., single chain antibody (i.e., an antibody having at least one VH and VL domain).
Regarding claims 94 and 108, see as cited previously above, Sugimoto teach super-resolution microscopy, and as such addresses the claims (e.g., the species of super-resolution microscopy as taught by Hewitt et al. read on those limitations achieved by the cited prior art, see as cited above, Sugimoto include STED, STORM, GSD).
Regarding claim 110, Sugimoto teach high-throughput format for imaging data (see para [0004], [0085]).
Regarding claim 116, Sugimoto, see as cited above, teaches imaging populations, namely the algorithms are trained on populations of data, i.e., multiple features imaged. It would necessarily follow that imaging be one of sequentially or simultaneously (as these cover all possible options for imaging a plurality of specimens).
Regarding claims 122 and 123, see as cited above, Hewitt is teaching protein biomarkers.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELLEN J MARCSISIN whose telephone number is (571)272-6001. The examiner can normally be reached M-F 8:00am-4:30pm.
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/ELLEN J MARCSISIN/Primary Examiner, Art Unit 1677
