DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
2. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 03/18/2026 has been entered.
Claim Interpretation
3. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
4. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
Claim Rejections - 35 USC § 102
5. 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.
6. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
7. Claims 83-84, 86-88, 90-94, 96-97, and 99-101 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by INOUE et al. Patent Application No. US 2022/0215543 (hereinafter INOUE).
Regarding claim 83, INOUE discloses a method comprising:
obtaining or having obtained a cell; capturing one or more images of the cell (Figure 3: acquire cell image S100); and analyzing the one or more images using a predictive model to predict a cellular age of the cell (Abstract: "a predictor configured to input the images acquired by the acquirer to a model trained on data in which information indicating at least a neurodegenerative discase is associated with the image obtained by imaging the cells of the neurodegenerative disease differentiated from the pluripotent stem cells"), the predictive model trained to distinguish between morphological profiles of differently aged cells (paragraph [0082]: "in the present embodiment, since the prediction model MDL including the plurality of models WL implemented by the CNN is used, it is possible to expect that features such as minute changes in the cell structure and relative positional relationships between the cells, which are difficult to observe with the naked eye in the cell images, can be calculated as convolutional feature amounts in the hidden layer. As a result, neurodegenerative diseases can be detected at an early stage at which they cannot be caught by human visual checking of cell images", the examiner notes "changes in the cell structure and relative positional relationships" are the claimed "morphological profiles"), wherein analyzing the one or more images includes determining age effects imparted by a perturbation to the cell (paragraphs [0091] and [0133], Inoue teaches a perturbation is a therapeutic agent/test substance is administered and compare the cell reaction to determine the effectiveness of the agent/substance).
Regarding claim 84, INOUE discloses the method of claim 83, further comprising: prior to capturing one or more images of the cell, providing a perturbation to the cell; subsequent to analyzing the one or more images, comparing the predicted cellular age of the cell to an age of the cell known before providing the perturbation; and based on the comparison, identifying the perturbation as having one of a directed aging effect, directed rejuvenation effect, or no effect (paragraphs [0091] and [0133], Inoue teaches a perturbation is a therapeutic agent/test substance is administered and compare the cell reaction to determine the effectiveness of the agent/substance).
Regarding claim 86, INOUE discloses the method of claim 83, wherein the predictive model is one of a neural network, random forest, or regression model (paragraph [0055]: " prediction model MDL is implemented by various neural networks, such as a convolutional neural network (CNN").
Regarding claim 87, INOUE discloses the method of claim 83, wherein each of the morphological profiles of differently aged cells comprises values of imaging features that define an age of a cell (as explained above, "changes in the cell structure and relative positional relationships" derived from the captured images are the claimed values of imaging features in the "morphological profiles").
Regarding claim 88, INOUE discloses the method of claim 87, wherein the imaging features comprise one or more of cell features or non-cell features (paragraph [0038]: "a desired cell induced to differentiate from pluripotent stem cells").
Regarding claim 90, INOUE discloses the method of claim 88.
KAMENS teaches wherein the non-cell features comprise well density features, background versus signal features, and percent of touching cells in a well (paragraphs 24, 157, 173 of KAMENS).
Regarding claim 91, INOUE discloses the method of claim 88, wherein the cell features are determined via fluorescently labeled biomarkers in the one or more images (a fluorescent dye binds to the DNA to cause fluorescence; paragraph 112).
Regarding claim 92, INOUE discloses the method of claim 83, wherein the morphological profile is an embedding representing a dimensionally reduced representation of values of a layer of the neural network (paragraph [0058]: a fully-connected layer).
Regarding claim 93, INOUE discloses the method of claim 83, wherein the cellular age of the cell predicted by the predictive model is a classification of at least two categories (see Figure 3 for numerals S108 and S110 for die or not die).
Regarding claim 94, INOUE discloses the method of claim 83, wherein the cell is one of a stem cell, partially differentiated cell, or terminally differentiated cell (paragraph [0038]: "a desired cell induced to differentiate from pluripotent stem cells").
Regarding claim 96, INOUE discloses the method of claim 83, wherein the predictive model is trained by:
obtaining or having obtained a cell of a known cellular age; capturing one or more images of the cell of the known cellular age; and using the one or more images of the cell of the known cellular age, training the predictive model to distinguish between morphological profiles of differently aged cells (Figure 6 and paragraph [0008] and [0072]: "a model trained on data in which information indicating at least a neurodegenerative disease is associated with an image obtained by imaging cells of the neurodegenerative disease differentiated from pluripotent stem cells").
Regarding claim 97, INOUE discloses the method of claim 96, wherein the known cellular age of the cell serves as a reference ground truth for training the predictive model (paragraph [0074]: the compute error is based on the comparison of the output result of model and a reference ground truth).
Regarding claim 99, INOUE discloses the method of claim 83, further comprising:
prior to capturing the one or more images of the cell, staining or having stained the cell using one or more fluorescent dyes, wherein the one or more fluorescent dyes are Cell Paint dyes for staining one or more of a cell nucleus, cell nucleoli, plasma membrane, cytoplasmic RNA, endoplasmic reticulum, actin, Golgi apparatus, and mitochondria (paragraph [0112]).
Regarding claim 100, INOUE discloses the method of claim 83, wherein the steps of obtaining the cell and capturing the one or more images of the cell are performed in a high-throughput format using an automated array (see paragraph [0129] for green fluorescent channel, and the examiner notes capturing image data in a high-throughput format using an automated array is a standard practice in the industry).
Regarding claim 101, INOUE discloses a non-transitory computer-readable medium comprising instructions that (A program stored in a portable storage medium; paragraphs 46-47, 101), when executed by a processor (CPU, Figure 2), cause the processor to: obtain or having obtained one or more images of a cell (Figure 3: acquire cell image S100); and analyze the one or more images using a predictive model to predict the cellular age of the cell (Abstract: "a predictor configured to input the images acquired by the acquirer to a model trained on data in which information indicating at least a neurodegenerative discase is associated with the image obtained by imaging the cells of the neurodegenerative disease differentiated from the pluripotent stem cells"), the predictive model trained to distinguish between morphological profiles of differently aged cells (paragraph [0082]: "in the present embodiment, since the prediction model MDL including the plurality of models WL implemented by the CNN is used, it is possible to expect that features such as minute changes in the cell structure and relative positional relationships between the cells, which are difficult to observe with the naked eye in the cell images, can be calculated as convolutional feature amounts in the hidden layer. As a result, neurodegenerative diseases can be detected at an early stage at which they cannot be caught by human visual checking of cell images", the examiner notes "changes in the cell structure and relative positional relationships" are the claimed "morphological profiles"), wherein analyzing the one or more images includes determining age effects imparted by a perturbation to the cell (paragraphs [0091] and [0133], Inoue teaches a perturbation is a therapeutic agent/test substance is administered and compare the cell reaction to determine the effectiveness of the agent/substance).
Claim Rejections - 35 USC § 103
8. 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.
9. Claims 85, 89, 95, 98 and 102 are rejected under 35 U.S.C. 103 as being unpatentable over INOUE in view of KAMENS et al. Patent Application No. US 2019/0228840 (hereinafter KAMENS).
Regarding claim 85, INOUE discloses the method of claim 83, wherein analyzing the one or more images using a predictive model comprises separately applying the predictive model to each of the one or more images to predict cellular ages (Abstract: "a predictor configured to input the images acquired by the acquirer to a model trained on data in which information indicating at least a neurodegenerative discase is associated with the image obtained by imaging the cells of the neurodegenerative disease differentiated from the pluripotent stem cells").
INOUE does not explicitly disclose wherein the method further comprises: evaluating performances of the predictive model across the predicted cellular ages; ranking the one or more images according to the evaluated performances of the predictive model across the predicted cellular ages; and selecting a set of biomarkers corresponding to the ranked channels for inclusion in a cellular aging assay
However, KAMENS working in the same field endeavor teaches wherein the method further comprises: evaluating performances of the predictive model across the predicted cellular ages; ranking the one or more images according to the evaluated performances of the predictive model across the predicted cellular ages; and selecting a set of biomarkers corresponding to the ranked channels for inclusion in a cellular aging assay (ingredient or candidates for the active ingredient may be identified or evaluated based on performing; paragraphs 100-102 of KAMENS).
In view of the above, it would have been obvious to one having ordinary skill in the art at the time of the invention was made to combine the system of INOUE as taught by KAMENS to include: evaluating performances of the predictive model across the predicted cellular ages; ranking the one or more images according to the evaluated performances of the predictive model across the predicted cellular ages; and selecting a set of biomarkers corresponding to the ranked channels for inclusion in a cellular aging assay. By doing so, the combined system of KAMENS would have generated a greater understanding of the aging process and the mechanisms involved, such identification and experimental validation would be challenging and require novel computational approaches, especially for the development of effective therapeutics for aging (paragraph 003).
Regarding claim 89, INOUE discloses the method of claim 88.
INOUE does not explicitly disclose wherein the cell features comprise one or more of cellular shape, cellular size, cellular organelles, object-neighbors features, mass features, intensity features, quality features, texture features, and global features.
However, KAMENS teaches wherein the cell features comprise one or more of cellular shape, cellular size, cellular organelles, object-neighbors features, mass features, intensity features, quality features, texture features, and global features (paragraph 109 of KAMENS).
In view of the above, it would have been obvious to one having ordinary skill in the art at the time of the invention was made to combine the system of INOUE as taught by KAMENS to include: wherein the cell features comprise one or more of cellular shape, cellular size, cellular organelles, object-neighbors features, mass features, intensity features, quality features, texture features, and global features. By doing so, the combined system of KAMENS would have generated a greater understanding of the aging process and the mechanisms involved, such identification and experimental validation would be challenging and require novel computational approaches, especially for the development of effective therapeutics for aging (paragraph 003).
Regarding claim 95, INOUE discloses the method of claim 83.
INOUE does not explicitly disclose wherein the cell is a somatic cell, and the somatic cell is a fibroblast (at least paragraph 99 of KAMENS).
However, KAMENS teaches wherein the cell is a somatic cell, and the somatic cell is a fibroblast (at least paragraph 99 of KAMENS).
In view of the above, it would have been obvious to one having ordinary skill in the art at the time of the invention was made to combine the system of INOUE as taught by KAMENS to include: wherein the cell is a somatic cell, and the somatic cell is a fibroblast. By doing so, the combined system of KAMENS would have generated a greater understanding of the aging process and the mechanisms involved, such identification and experimental validation would be challenging and require novel computational approaches, especially for the development of effective therapeutics for aging (paragraph 003).
Regarding claim 98, INOUE discloses the method of claim 96.
INOUE does not explicitly disclose wherein the cell of the known cellular age is one cell in an age-diverse cohort of cells (e.g. shape, appearance, cell size, nuclear size, nucleolar size, number of multinucleated cells).
However, KAMENS teaches wherein the cell of the known cellular age is one cell in an age-diverse cohort of cells (e.g. shape, appearance, cell size, nuclear size, nucleolar size, number of multinucleated cells (paragraph 77 of KAMENS).
In view of the above, it would have been obvious to one having ordinary skill in the art at the time of the invention was made to combine the system of INOUE as taught by KAMENS to include: wherein the cell of the known cellular age is one cell in an age-diverse cohort of cells. By doing so, the combined system of KAMENS would have generated a greater understanding of the aging process and the mechanisms involved, such identification and experimental validation would be challenging and require novel computational approaches, especially for the development of effective therapeutics for aging (paragraph 003).
Regarding claim 102, INOUE discloses a method comprising:
obtaining or having obtained a cell; capturing one or more images of the cell (Figure 3: acquire cell image at S100); and analyzing imaging features derived from the one or more images using a predictive model to predict the cellular age of the cell (Abstract: "a predictor configured to input the images acquired by the acquirer to a model trained on data in which information indicating at least a neurodegenerative discase is associated with the image obtained by imaging the cells of the neurodegenerative disease differentiated from the pluripotent stem cells", the predictive model trained to distinguish between morphological profiles of differently aged cells (paragraph [0082]: "in the present embodiment, since the prediction model MDL including the plurality of models WL implemented by the CNN is used, it is possible to expect that features such as minute changes in the cell structure and relative positional relationships between the cells, which are difficult to observe with the naked eye in the cell images, can be calculated as convolutional feature amounts in the hidden layer. As a result, neurodegenerative diseases can be detected at an early stage at which they cannot be caught by human visual checking of cell images", the examiner notes "changes in the cell structure and relative positional relationships" are the claimed "morphological profiles"), wherein the morphological profiles of differently aged cells comprise values of imaging features that define an age of a cell (as explained above, "changes in the cell structure and relative positional relationships" derived from the captured images are the claimed values of imaging features in the "morphological profiles"), wherein the imaging features comprise cell features (paragraph [0038]: "a desired cell ").
INOUS does not explicitly disclose wherein the imaging features comprise non-cell features, wherein the non-cell features comprise well density features, background versus signal features, and percent of touching cells in a well.
However, KAMENS working in the same field of endeavor teaches wherein the imaging features comprise non-cell features, wherein the non-cell features comprise well density features, background versus signal features, and percent of touching cells in a well (paragraphs 157, 173, 184 of KAMENS).
In view of the above, it would have been obvious to one having ordinary skill in the art at the time of the invention was made to combine the system of INOUE as taught by KAMENS to include: wherein the non-cell features comprise well density features, background versus signal features, and percent of touching cells in a well. By doing so, the combined system of KAMENS would have generated a greater understanding of the aging process and the mechanisms involved, such identification and experimental validation would be challenging and require novel computational approaches, especially for the development of effective therapeutics for aging (paragraph 003).
Information Disclosure Statement
10. The information disclosure statement (IDS) submitted on 01/15/2026 was filed in compliance with the provisions of 37 CFR 1.97 and 1.98. Accordingly, the information disclosure statement is being considered by the examiner.
Cited Art
11. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
12. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALLEN H NGUYEN whose telephone number is (571)270-1229. The examiner can normally be reached M-F 7 am-4 pm.
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/ALLEN H NGUYEN/Primary Examiner, Art Unit 2683