DETAILED ACTION
Response to Amendment
Amendments and response received 11/07/2025 have been entered. Claims 1-13 and 15-17 are currently pending in this application. Claims 5, 6, 8 and 15 have been amended. Amendments and response are addressed hereinbelow.
Claim Rejections - 35 USC § 112
In light of the amendments to the claimed subject matter the previous grounds of rejection have been rendered moot with the cancelation of verbiage which implied features were not essential.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
Claims 1-4, 7, 12, 13 and 15-17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kenneth Giuliano et al (US 20090170091 1).
Regarding claim 1, Giuliano et al discloses a method of studying an effect of a test substance on a test sample of biological cells (¶ [6]) using a set of relevant parameters and a set of meta-features (fi, f2, fL) (¶ [6]), the method comprising:
exposing the test sample to the test substance (¶ [29] test substance);
determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample (¶ [31-33] cellular function classes: determining size, shape, quantity/count etc.); and
determining feature values of the set of meta-features (fi, f2, fL) for the test sample, wherein each of the feature values is calculated from the parameter values of a cluster (C1, C2, CL) of correlated parameters from the set of relevant parameters that is associated with the respective meta-feature (fi, f2, f1) (¶ [74]),
wherein a reference sample for determining the set of meta-features (f1, f2, fL) was exposed to a stimulus substance (¶ [7]).
Regarding claim 2, Giuliano et al discloses the method of claim 1, wherein the set of relevant parameters and the set of meta-features are determined by:
receiving parameter values of a set of cell parameters (p1, p2, pN) for each of a plurality of cells in a control sample and for each of a plurality of cells in the reference sample (¶ [35-36] determining values for parameter classes established previously based on image analysis);
identifying a set of relevant parameters from the set of cell parameters (p1, p2, pN) (¶ [51]) by comparing the parameter values from the control sample and the parameter values from the reference sample for at least one of the cell parameters (p1,p2, pN) (¶ [51-52]);
identifying clusters (C1, C2, CL) of correlated parameters within the set of relevant parameters based on correlations between the parameter values of the relevant parameters (¶ [40] and ¶ [76]); and
defining a meta-feature (fi, f2, fL) for at least one of the clusters (C1, C2, CL) as a mathematical function of the parameters of the respective cluster (¶ [40-41] profile used to create classifier).
Regarding claim 3, Giuliano et al discloses the method of claim 1, further comprising:
determining parameter values of the set of relevant parameters for each of a plurality of cells in a control test sample (¶ [32-33]);
determining feature values of the set of meta-features (fi, f2, fL) from the parameter values of the set of relevant parameters for the control test sample (¶ [74]; and
comparing feature values of meta-features (fi, f2, fL) for the test sample and feature values of meta-features (fi, f2, fL) for the control test sample to assess an effect of the test substance (¶ [47]).
Regarding claim 4, Giuliano et al discloses the method of claim 1, wherein the biological cells are cardiomyocytes (¶ [22]) and
the stimulus substance comprises a hypertrophy inducing substance, in particular at least one of phenylephrine, adrenaline, noradrenaline, isoproterenol, insulin, endothelin, and angiotensin and/or a mediator involved in one or more medical conditions, in particular in one or more cardiovascular conditions (¶ [22]), and/or
the test substance comprises a candidate substance to be tested as a potential inhibitor or modulator of the medical condition (¶ [26]).
Regarding claim 7, Giuliano et al discloses the method of claim 1, wherein the method is used to distinguish different cell types, in particular to distinguish one or more of: fibroblast, cardiomyocyte, immune cell, or others, and/or to distinguish different cell sub-types, in particular one or more of cardiomyocyte subtypes or target cells for potential therapeutic agents (¶ [22-23]).
Regarding claim 12, discloses the method of claim 1 (see rejection of claim 1), wherein determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample comprises obtaining a plurality of images of the plurality of cells at a plurality of time points (¶ [34]), wherein in particular the plurality of images are obtained using a microscope (¶ [73]).
Regarding claim 13, Giuliano et al discloses the method of claim 1, further comprising an initial step of staining or labelling the biological cells, a cell compartment, a cell structure, a specific protein or mRNA of interest and/or the test substance with a stain or dye or with an imaging marker (¶ [31]).
Regarding claim 15, Giuliano et al discloses a system comprising a processing device and a data storage coupled to the processing device, wherein the data storage stores a set of machine-readable instructions that, when executed by the processing device (¶ [73]), cause the processing device to:
receive at least one microscopic image of a test sample of biological cells and at least one microscopic image of a control test sample of biological cells;
determine parameter values of a set of relevant parameters for each of a plurality of cells in the test sample and for each of a plurality of cells in the control test sample from the at least one microscopic image of the respective sample (see rejection of claim 2);
determine feature values of a set of meta-features (fi, f2, fL) from the parameter values of the set of relevant parameters for the test sample (see rejection of claim 1); and
determine feature values for the set of meta-features (fi, f2, fL) from the parameter values of the set of relevant parameters for the control test sample, wherein the system further comprises the test sample and the control test sample, wherein the test sample is to be exposed to a test substance (see rejection of claim 1).
Regarding claim 16, Giuliano et al discloses the system of claim 15 (see rejection of claim 15), wherein the set of relevant parameters and the set of meta-features (fi, f2, fL) were determined by:
receiving parameter values of a set of cell parameters (p1,p2,pN) for each of a plurality of cells in a control sample and for each of a plurality of cells in a reference sample (see rejection of claim 2);
identifying a set of relevant parameters from the set of cell parameters (p1,p2,pN) by comparing the parameter values from the control sample and the parameter values from the reference sample for at least one of the cell parameters (p1,p2, pN) (see rejection of claim 2);
identifying clusters (C1, C2, CL) of correlated parameters within the set of relevant parameters based on correlations between the parameter values of the relevant parameters (see rejection of claim 2); and
defining a meta-feature (fi, f2, fL) for at least one of the clusters (C1, C2, CL) as a mathematical function of the parameters of the respective cluster (see rejection of claim 2).
Regarding claim 17, Giuliano et al discloses a non-transitory computer-readable storage medium comprising instructions stored thereon that, when executed by a computing device cause the computing device to perform operations (¶ [36]) of studying an effect of a test substance on a test sample of biological cells using a set of relevant parameters and a set of meta-features (fi, f2, fL) (see rejection of claim 1), the operations comprising:
exposing the test sample to the test substance (see rejection of claim 1);
determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample (see rejection of claim 1); and
determining feature values of the set of meta-features-for the test sample (fi, f2, fL), wherein each of the feature values is calculated from the parameter values of a cluster (C1, C2, CL) of correlated parameters from the set of relevant parameters that is associated with the respective meta- feature (fi, f2, f1) (see rejection of claim 1),
wherein a reference sample for determining the set of meta-features (f1, f2, fL) was exposed to a stimulus substance (see rejection of claim 1).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Kenneth Giuliano et al (US 20090170091 1) in view of Shawn T. Coyne et al (US 20170307596 A1).
Regarding claim 5, Giuliano et al discloses the method of claim 1 (see rejection of claim 1).
Giuliano et al fails to explicitly disclose wherein the test substance comprises patient-specific material, in particular a blood sample, blood components and/or human-induced pluripotent stem cell-derived cardiomyocytes, iPSC-CMs, in combination with one or more pharmacological substances, wherein the stimulus substance comprises patient specific material of one or more reference patients diagnosed with a medical condition to be tested, in combination with one or more pharmacological substances and/or the stimulus substance comprises patient specific material of one or more reference patients without the medical condition to be tested, in combination with one or more pharmacological substances and/or a mediator involved in one or more medical conditions, in particular in one or more cardiovascular conditions.
Coyne et al, in the same field of endeavor of conducting stimulus response studies on cells collected from donors (Abstract), teaches the test substance comprises patient-specific material, in particular a blood sample, blood components and/or human-induced pluripotent stem cell-derived cardiomyocytes, iPSC-CMs (¶ [12] and ¶ [26]), in combination with one or more pharmacological substances, wherein the stimulus substance comprises patient specific material of one or more reference patients diagnosed with a medical condition to be tested (¶ [49]), in combination with one or more pharmacological substances and/or the stimulus substance comprises patient specific material of one or more reference patients without the medical condition to be tested, in combination with one or more pharmacological substances and/or a mediator involved in one or more medical conditions, in particular in one or more cardiovascular conditions.
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the method as disclosed by Giuliano et al comprising exposing a test sample to a test substance, determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample, and determining feature values of the set of meta-features (fi, f2, fL) for the test sample to utilize the teachings of Coyne et al which teaches the test substance comprises patient-specific material, in particular a blood sample, blood components and/or human-induced pluripotent stem cell-derived cardiomyocytes, iPSC-CMs, in combination with one or more pharmacological substances, wherein the stimulus substance comprises patient specific material of one or more reference patients diagnosed with a medical condition to be tested, in combination with one or more pharmacological substances and/or the stimulus substance comprises patient specific material of one or more reference patients without the medical condition to be tested, in combination with one or more pharmacological substances and/or a mediator involved in one or more medical conditions, in particular in one or more cardiovascular conditions to conduct the stimulus-response experiment with adequate controls, such that variation is due to genetic differences, rather than variations in the experimental procedure.
Claims 6 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Giuliano et al in view of Georg Hess et al (US 20120164669 A1).
Regarding claim 6, Giuliano et al discloses the method of claim 1.
Giuliano et al fails to explicitly disclose wherein the test substance comprises a sample of a patient, in particular a blood sample of the patient, blood serum or blood plasma of the patient, wherein the method further comprises diagnosing a medical condition, assessing severity of a medical condition, assessing prognosis, and/or assessing a progress of therapeutic treatment against a medical condition based on the feature values of the set of meta-features (fi, f2, fL) for the test sample, in particular wherein the medical condition is hypertrophic cardiomyopathy, amyloidosis, ischemic cardiomyopathy, dilatative cardiomyopathy, hypertensive heart disease, cardiac arrest, and/or aortic stenosis.
Hess et al, in the same field of endeavor of diagnosing medical conditions using information from test samples (¶ [42]), teaches the test substance comprises a sample of a patient, in particular a blood sample of the patient, blood serum or blood plasma of the patient (¶ [49]), wherein the method further comprises diagnosing a medical condition, assessing severity of a medical condition, assessing prognosis, and/or assessing a progress of therapeutic treatment against a medical condition based on the feature values of the set of meta-features (fi, f2, fL) for the test sample (¶ [62] diagnosis), in particular wherein the medical condition is hypertrophic cardiomyopathy, amyloidosis, ischemic cardiomyopathy, dilatative cardiomyopathy, hypertensive heart disease, cardiac arrest, and/or aortic stenosis (¶ [73]).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the method as disclosed by Giuliano et al comprising exposing a test sample to a test substance, determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample, and determining feature values of the set of meta-features (fi, f2, fL) for the test sample to utilize the teachings of Hess et al which teaches the test substance comprises a sample of a patient, in particular a blood sample of the patient, blood serum or blood plasma of the patient, wherein the method further comprises diagnosing a medical condition, assessing severity of a medical condition, assessing prognosis, and/or assessing a progress of therapeutic treatment against a medical condition based on the feature values of the set of meta-features (fi, f2, fL) for the test sample, in particular wherein the medical condition is hypertrophic cardiomyopathy, amyloidosis, ischemic cardiomyopathy, dilatative cardiomyopathy, hypertensive heart disease, cardiac arrest, and/or aortic stenosis to aid in distinguishing subjects having certain conditions and facilitating therapeutic decisions based on the conditions.
Regarding claim 8, Giuliano et al discloses the method of claim 1 (see rejection of claim 1).
Giuliano et al fails to explicitly disclose wherein the method further comprises assessing suitability of therapeutic treatments for an individual patient, in particular regarding treatment efficacy, adverse events, time to treatment response, wherein the method is used for continuous therapeutic monitoring, and/or assessing a prognosis and/or a probability of major cardiac events and/or a time to major cardiac events and/or a probability of death and/or a time to death, wherein the test substance comprises patient specific material in combination with one or more pharmacological substances, wherein the stimulus substance comprises patient specific material of one or more reference patients with a known prognosis and/or a known probability of major cardiac events and/or a known time to major cardiac events and/or a known probability of death and/or a known time to death, in combination with one or more pharmacological substances.
Hess et al teaches the method further comprises assessing suitability of therapeutic treatments for an individual patient, in particular regarding treatment efficacy, adverse events, time to treatment response, wherein the method is used for continuous therapeutic monitoring, and/or assessing a prognosis and/or a probability of major cardiac events and/or a time to major cardiac events and/or a probability of death and/or a time to death, wherein the test substance comprises patient specific material in combination with one or more pharmacological substances, wherein the stimulus substance comprises patient specific material of one or more reference patients with a known prognosis and/or a known probability of major cardiac events and/or a known time to major cardiac events and/or a known probability of death and/or a known time to death, in combination with one or more pharmacological substances (¶ [190] monitoring therapy of treatment; ¶ [203] assessment to decide on therapy).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the method as disclosed by Giuliano et al comprising exposing a test sample to a test substance, determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample, and determining feature values of the set of meta-features (fi, f2, fL) for the test sample to utilize the teachings of Hess et al which teaches assessing suitability of therapeutic treatments for an individual patient, in particular regarding treatment efficacy, adverse events, time to treatment response, wherein the method is used for continuous therapeutic monitoring, and/or assessing a prognosis and/or a probability of major cardiac events and/or a time to major cardiac events and/or a probability of death and/or a time to death, wherein the test substance comprises patient specific material in combination with one or more pharmacological substances, wherein the stimulus substance comprises patient specific material of one or more reference patients with a known prognosis and/or a known probability of major cardiac events and/or a known time to major cardiac events and/or a known probability of death and/or a known time to death, in combination with one or more pharmacological substances to confirm the methods of treatment are providing the desired results.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Giuliano et al in view of John McLaughlin et al (US 20110169937 A1).
Regarding claim 9, Giuliano et al discloses the method of claim 1.
Giuliano et al fails to explicitly disclose the method further comprises performing a single-cell phenotyping by determining feature values of the set of meta-features (fi, f2, f1) and/or parameter values of the set of relevant parameters for at least one of the plurality of cells in the test sample, and/or performing a population-level phenotyping by determining average feature values of the set of meta-features (fi,f2, f1) and/or average parameter values of the set of relevant parameters averaged over a set of cells from the plurality of cells in the test sample.
McLaughlin et al, in the same field of endeavor of introducing test cells to a test substance and acquiring an image for analysis (¶ [47]), teaches performing a single-cell phenotyping (¶ [31]) by determining feature values of the set of meta-features (fi, f2, f1) and/or parameter values of the set of relevant parameters for at least one of the plurality of cells in the test sample (¶ [54-56]), and/or performing a population-level phenotyping by determining average feature values of the set of meta-features (fi,f2, f1) and/or average parameter values of the set of relevant parameters averaged over a set of cells from the plurality of cells in the test sample.
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the method as disclosed by Giuliano et al comprising exposing a test sample to a test substance, determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample, and determining feature values of the set of meta-features (fi, f2, f1) for the test sample to utilize the teachings of McLaughlin et al which teaches performing a single-cell phenotyping by determining feature values of the set of meta-features (fi, f2, f1) and/or parameter values of the set of relevant parameters for at least one of the plurality of cells in the test sample, and/or performing a population-level phenotyping by determining average feature values of the set of meta-features (fi,f2, f1) and/or average parameter values of the set of relevant parameters averaged over a set of cells from the plurality of cells in the test sample to understand unique characteristics of the cells and better distinguish cells.
Claims 10 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Giuliano et al in view of Albert Edge et al (US 20030113301 A1).
Regarding claim 10, Giuliano et al discloses the method of claim 1.
Giuliano et al fails to explicitly disclose wherein the plurality of cells include one or more of one or more cells extracted from mammalian hearts, in particular one or more of whole heart derived single cell suspensions, cardiomyocytes, fibroblasts, immune cells, and/or one or more mammalian stem-cell derived cardiomyocytes, in particular human induced pluripotent stem cell-derived cardiomyocytes.
Edge et al, in the same field of endeavor of analyzing medical cells (Abstract), teaches the plurality of cells include one or more of one or more cells extracted from mammalian hearts, in particular one or more of whole heart derived single cell suspensions, cardiomyocytes, fibroblasts, immune cells, and/or one or more mammalian stem-cell derived cardiomyocytes, in particular human induced pluripotent stem cell-derived cardiomyocytes (¶ [5-6]).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the method as disclosed by Giuliano et al comprising exposing a test sample to a test substance, determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample, and determining feature values of the set of meta-features (fi, f2, fL) for the test sample to utilize the teachings of Edge et al which teaches the plurality of cells include one or more of one or more cells extracted from mammalian hearts, in particular one or more of whole heart derived single cell suspensions, cardiomyocytes, fibroblasts, immune cells, and/or one or more mammalian stem-cell derived cardiomyocytes, in particular human induced pluripotent stem cell-derived cardiomyocytes to aid in the treatment of heart-related disease.
Regarding claim 11, Giuliano et al discloses the method of claim 1 (see rejection of claim 1).
Giuliano et al fails to explicitly disclose wherein a medical condition is chosen from the field of cardiovascular conditions, in particular wherein the medical condition is hypertrophic cardiomyopathy, amyloidosis, ischemic cardiomyopathy, dilatative cardiomyopathy, hypertensive heart disease, and/or aortic stenosis.
Edge et al discloses a medical condition is chosen from the field of cardiovascular conditions, in particular wherein the medical condition is hypertrophic cardiomyopathy, amyloidosis, ischemic cardiomyopathy, dilatative cardiomyopathy, hypertensive heart disease, and/or aortic stenosis (¶ [28]).
It would have been obvious to one of ordinary skill in the art before the invention was effectively filed for the method as disclosed by Giuliano et al comprising exposing a test sample to a test substance, determining parameter values of the set of relevant parameters for each of a plurality of cells in the test sample, and determining feature values of the set of meta-features (fi, f2, fL) for the test sample to utilize the teachings of Edge et al which teaches the medical condition is chosen from the field of cardiovascular conditions, in particular wherein the medical condition is hypertrophic cardiomyopathy, amyloidosis, ischemic cardiomyopathy, dilatative cardiomyopathy, hypertensive heart disease, and/or aortic stenosis to aid in the treatment of heart-related disease.
Response to Arguments
Applicant's arguments filed 11/07/2025 have been fully considered but they are not persuasive.
Applicant’s remarks: Giuliano discusses clustering cell data sets and compounds but not clustering "correlated parameters from the set of relevant parameters". Giuliano does not teach finding a correlation among the parameters and clustering them based on the obtained correlation. Giuliano simply combines features (e.g., in a vector or matrix) to produce a response profile for the test substance. This is verified from Fig. 9, which shows the heat map of response profiles for 30 different compounds, without considering any correlation between the cellular parameters. Fig. 9 shows clustering of compounds and the parameters in Fig. 9 are simply divided into three categories (acute, early, and chronic) without considering any statistic correlation among them. Thus, finding correlated parameters to define meta features, and determining the feature values of the meta features from clusters of correlated cellular parameters is not disclosed and not a part of Giuliano's method to assess biological responses to a test substance.
Examiner’s response: Giuliano discloses that the images of the cells are analyzed to measure or detect cellular features which are selected to be indicative of the functional classes appropriate to the property. Functional classes, in this manner, correlate to “relevant parameters” of the biological cell claimed. Parameter values of functional classes are dependent on the classes assayed as the information gathered from the functional class coincides with the properties exhibited by the particular functional class (e.g., toxicity, clinical pathology, etc.). Reporters (labels, dyes, etc.) are selected to target features appropriate for assaying the classes of cellular function. One or more assays can then be used to measure one or more cellular features indicating a response to the respective functional class. Depending on the selected functional class, “parameter values” are “clustered” wherein the average or mean is calculated for respective “clustered parameters” to provide the desired analyzed measurements of the cell in accordance with the specified functional class. The clustering of nuclear size or nuclear intensity, for example, indicates those specific parameters being “clustered” to determine an average or mean. The correlation of the selected/clustered parameters depends directly on the functional class selected by the user as the respective selected parameters provide the information required for determining cellular response for the functional class. The terms of the claim, including relevant parameters, meta-features, parameter values, feature values, and correlated parameters are not explicitly defined in a manner to preclude the interpretation as set forth in the rejection. Therefore, the examiner contends that the prior art of record addresses each element as mapped in the rejections above in accordance with the broadest reasonable interpretation of the claimed subject matter.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, 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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/JAMARES Q WASHINGTON/Primary Examiner, Art Unit 2681
January 30, 2026