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 .
Remarks
In response to communications sent September 22, 2025, claim(s) 1-9 is/are pending in this application; of these claim(s) 1 is/are in independent form.
Continued Examination Under 37 CFR 1.114
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 final rejection. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on September 22, 2025 has been entered.
Claim Interpretation
Regarding the element of “training… to model an escape profile… the escape profiling representing… a relative escape potential…”: The Examiner contemplated whether this is positively recited step followed by a mere intended result of the positively recited step that would not have patentable weight. Upon review of the next element, “generating a visualization… of escape potential…” the examiner interpreted that the escape potential is part of the next positively recited step of generating a visualization. As such, the model that is an intended result of the training should have patentable weight, as it is part of the positively recited step of generating a visualization.
Response to Arguments
Regarding 35 U.S.C. § 112(b):
Applicant’s arguments, see page 4 lines 10-17, filed September 22, 2025, with respect to the rejection(s) of claim(s) 1-17 and claim 9 under 35 U.S.C. § 112(b) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Applicant’s Remarks and 35 U.S.C. § 112(b). See page 5 last 3 lines of Applicant’s Remarks file September 22, 2025 regarding whether the claims encompass the architecture of a Bidirectional Long-Short-Term-Memory (BiLSTM) type of neural network architecture. Applicant’s Remarks argue against the idea that the Applicant’s independent claims recite a particular BiLSTM architecture. However, this contradicts Applicant’s dependent claim 8, which recites a “constrained semantic change search.” See Applicant’s Remarks, see page 5 last three lines, sent September 22, 2025. Compare the Applicant’s Remarks to Applicant’s Figure 1B and the description of Figure 1B on page 4 lines 9-12. Applicant’s Figure 1B suggests that the independent claim and dependent claim 8 does use a BiLSTM architecture. Hence the independent claims and dependent claims from the independent claims have unclear scope.
The Examiner suggests clarifying in Remarks whether the specific of the architecture in Sudol is what is not encompassed by the Applicant’s claims and clarifying whether the claims indeed encompass and/or involve BiLSTM architectures.
Applicant's arguments filed September 22, 2025 have been fully considered but they are not persuasive. The rejection of claim 8 is not withdrawn because the phrase “constrained semantic change search” is not defined in the specification using closed-ended language, nor is there a plain meaning to the inventor’s term at the time of filing.
Regarding 35 U.S.C. § 102:
Applicant’s arguments with respect to claim(s) 1-4 and 6-7 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
This is in view of Applicant’s amendment to the claims.
Although the issues are moot, the Examiner notes the following: Regarding Applicant’s response to the Examiner’s interpretation of MHC-peptide binding prerequisites must be in the reference itself and not a textbook, this argument would not apply to definitions of terms. Definitions are one example of knowledge available to one of ordinary skill in the art to interpret the reference.
Regarding double-patenting:
Applicant's arguments filed September 12, 2025 have been fully considered but they are not persuasive. No specific arguments were presented and no terminal disclaimer was filed.
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 1-9 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.
See page 5, last 3 lines of Applicant’s Remarks file September 22, 2025 regarding whether the claims encompass the architecture of a Bidirectional Long-Short-Term-Memory (BiLSTM) type of neural network architecture. Applicant’s Remarks argue against the idea that the Applicant’s independent claims recite a particular BiLSTM architecture. However, this contradicts Applicant’s dependent claim 8, which recites a “constrained semantic change search.” See Applicant’s Remarks, see page 5 last three lines, sent September 22, 2025. Compare the Applicant’s Remarks to Applicant’s Figure 1B and the description of Figure 1B on page 4 lines 9-12. Applicant’s Figure 1B suggests that the independent claim and dependent claim 8 do involve a BiLSTM architecture. Hence the independent claims and dependent claims from the independent claims have unclear scope relative to the claim interpretation suggested in the Applicant’s Remarks.
The Examiner suggests clarifying in Remarks whether the specific of the architecture in Sudol is what is not encompassed by the Applicant’s claims and clarifying whether the claims indeed encompass and/or involve BiLSTM architectures.
Claim 8 is 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.
Regarding claim 8, the phrase “constrained semantic change search (CSCS)” is described in the applicant’s specification using open-ended language. See applicant’s specification at page 8 lines 8-12. This is unclear because the Applicant is ambiguously using a term that does not have a plain and ordinary meaning in the art at the time of filing of the claimed invention. For example, a query to Google Books product reveals few hits for the quoted phrase “constrained semantic change search”. For the purpose of compact prosecution, the Examiner assumes that the algorithm is functionally described as identifying “grammatical mutations to the given protein that induce high semantic change” as required by the claim language itself.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(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.
Claim(s) 1-3 and 6-8 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by “Bepler”: Bepler T, Berger B. Learning protein sequence embeddings using information from structure (version 1). arXiv preprint arXiv:1902.08661. 2019 Feb 22. (Year: 2019)
As to claim 1, Bepler teaches a method of escape profiling for therapeutic or vaccine development (the intended use of the “escape profiling” that is recited in the preamble has little patentable weight because there is no positively recited step involving therapeutic or vaccine development), comprising:
training a language-based model (Bepler, Figure 1, caption: forming an encoder model; the Bepler’s Abstract clarifies that a bidirectional long short-term memory model is trained) against training data comprising a corpus of protein sequences of a given protein (Bepler Figure 1, caption: forming the encoder model using amino acids sequences) to model an escape profile (Bepler, Figure 1, caption: fitting the parameters of the encoder combines two error signals; see formula 4 on page 6 of Bepler for the multitask objective) of the given protein (Bepler Figure 1, the amino acid sequence X on the left), the escape profile representing, for one or more regions of the given protein (Bepler Figure 1: the multitask objective representing the entire region of the specified amino acid sequence), a relative escape potential of a mutation (Bepler Figure 1: the changed amino acid sequence X’ on the right), the relative escape potential being derived as a function that combines both semantic change (Bepler, Figure 1, caption: fitting the parameters of the encoder combines two error signals; see formula 4 on page 6 of Bepler), wherein semantic change is a non-zero degree to which the mutation is recognized by the human immune system (Bepler, Figure 1 caption: the similarity prediction score maps to the claimed semantic change), and grammaticality, wherein grammaticality is a degree to which the mutation affects infectivity (Bepler, Figure 1, caption: the contact loss score maps to the degree to the grammaticality, since infectivity depends on viral contact);
generating a visualization of the relative escape potential across the given protein (Bepler Figure 1, the escape potential is visualized by visualizing the components of the escape potential at various positions across the given protein; see the matrices plotted to indicate “contact prediction” and “pairwise comparison”), the visualization depicting areas of enrichment or depletion of escape potential (Bepler Figure 1: the matrix plots depicting various areas of the entire protein that has the escape potential value); and
based at least in part on the areas of enrichment or depletion of escape potential depicted in the visualization, identifying a region or sub-region of the given protein having an escape potential of interest (Bepler Figure 1, caption: based on the visualizable matrices of the learning framework of Bepler, identify the contact loss and similarity loss to determine the escape potential value for the region that is the whole amino acid sequence X).
As to claim 2, Bepler teaches the method as described in claim 1 wherein the corpus of protein sequences of the given protein comprises copies of amino acid sequences from multiple host species (Bepler page 4, section 3.1 “Pretrained language model”: the Pfam database of protein families is the corpus, which uses the multi-species protein data bank according to the definition of Pfam and the Protein Data Bank).
See the definition of Pfam in:
R. D. Finn, A. Bateman, J. Clements, P. Coggill, R. Y. Eberhardt, S. R. Eddy, A. Heger, K. Hetherington, L. Holm, J. Mistry, E. L. Sonnhammer, J. Tate, and M. Punta. Pfam: the protein families database. Nucleic Acids Res., 42(Database issue):D222–230, Jan 2014.
See the definition of the Protein Data Bank in:
Bernstein, Frances C., et al. "The Protein Data Bank: a computer-based archival file for macromolecular structures." Journal of molecular biology 112.3 (1977): 535-542.
As to claim 3, Bepler teaches the method as described in claim 1 wherein the language-based model is trained in an unsupervised manner, without data about known escape mutations (Bepler page 9 under “Encoder architecture and pretrained language model are important”; Bepler teaches that the language model is pretrained on a large unsupervised protein sequence database).
As to claim 6, Bepler teaches the method as described in claim 1 wherein the mutation is one of: a single mutation (this element is claimed in the alternative and does not need to be mapped), and a combinatorial mutation (Bepler Figure 1, the change from amino acid sequence X to amino acid sequence X’ is a combinatorial mutation).
As to claim 7, Bepler teaches the method as described in claim 1 wherein the function that combines both semantic change and grammaticality applies a weighting to a score representing one of: the semantic change, the grammaticality, and a combination of semantic change and grammaticality (Bepler page 6: see formula 4 for the multitask objective which includes the parameter lambda and (1-lambda) in order to combine the similarity-score and the contact-score).
As to claim 8, Bepler teaches the method as described in claim 1 wherein identifying the region or sub-region of the given protein performs a constrained semantic change search (CSCS) to identify grammatical mutations to the given protein that induce high semantic change (Bepler page 8 “Contact prediction improves embeddings”: using contact prediction, i.e., grammatical mutation impact to better identify improve embedding information, i.e. semantic changes, all performed using repeated training for the repeated study of these components, structure and embeddings in Bepler Section 4.2).
Claim Rejections - 35 USC § 103
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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) 4, 5, and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bepler in view of US 20090162383 A1 (“Padlan”)
Note the Bepler reference is: Bepler T, Berger B. Learning protein sequence embeddings using information from structure (version 1). arXiv preprint arXiv:1902.08661. 2019 Feb 22. (Year: 2019)
As to claim 4, Bepler teaches the method as described in claim 1 but does not teach wherein the escape potential of interest is a low escape potential, the method further including targeting the region or sub-region in a vaccine development.
Nevertheless, Padlan teaches wherein the escape potential of interest is a low escape potential, the method further including targeting the region or sub-region in a vaccine development (Padlan Para [0084]: an intentionally mutated virus already has realized high escape potential; the Examiner interprets that regarding the intentionally mutated virus, there is no longer escape potential left or the strain that is already so mutated; therefore Padlan’s teaching to vaccinate against such as a strain teaches a vaccination against a region with low escape potential, i.e. low escape potential relative to the intentionally mutated strain).
Bepler and Padlan are in the same field of bioinformatics. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Bepler to include the teachings of Pradhan because changing antigenicity while preserving structure provides improves flu vaccine’s ability to form antibodies despite dynamic mutations (See Padlan’s Abstract). There would be a reasonable expectation of success because the method of Bepler is ready for application to particular applications, and Padlan teaches that influenza is a target virus for searching antigenicity changes while constraining structure using older algorithms.
As to claim 5, Bepler teaches the method as described in claim 1 but does not teach wherein the escape potential of interest is a high escape potential, the method further including targeting the region or sub-region in an anti-viral therapeutic development.
Nevertheless, Padlan teaches wherein the escape potential of interest is a high escape potential, the method further including targeting the region or sub-region in an anti-viral therapeutic development (Padlan, Para [0091]: identifying regions which have potential for lower antigenicity while preserving structure and using the sequences of those regions for therapeutic antibody development).
Bepler and Padlan are in the same field of bioinformatics. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Bepler to include the teachings of Pradhan because changing antigenicity while preserving structure provides improves flu vaccine’s ability to form antibodies despite dynamic mutations (See Padlan’s Abstract). There would be a reasonable expectation of success because the method of Bepler is ready for application to particular applications, and Padlan teaches that influenza is a target virus for searching antigenicity changes while constraining structure using older algorithms.
As to claim 9, Bepler teaches the method as described in claim 1 but does not teach wherein the given protein is a viral protein that is one of: influenza hemagglutinin, HIV Env, and SARS-CoV-2 Spike.
Nevertheless, Padlan teaches wherein the given protein is a viral protein that is one of: influenza hemagglutinin (Padlan Para [0098]), HIV Env (this element is claimed in the alternative and does not need to be mapped), and SARS-CoV-2 Spike (this element is claimed in the alternative and does not need to be mapped).
Bepler and Padlan are in the same field of bioinformatics. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Bepler to include the teachings of Pradhan because changing antigenicity while preserving structure provides improves flu vaccine’s ability to form antibodies despite dynamic mutations (See Padlan’s Abstract). There would be a reasonable expectation of success because the method of Bepler is ready for application to particular applications, and Padlan teaches that influenza is a target virus for searching antigenicity changes while constraining structure using older algorithms.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-9 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3 and 7-12 of U.S. Patent No. 11,011,253. Although the claims at issue are not identical, they are not patentably distinct from each other because corresponding claims of the instant application is a genus of the species of the reference patent, with minor difference that are at once envisaged.
Instant Application 17/322,649
U.S. Patent 11,011,253
1. A method of escape profiling for use in association with therapeutic or vaccine development, comprising: training a language-based model against training data comprising a corpus of protein sequences of a given protein to model an escape profile of the given protein, the escape profile representing, for one or more regions of the given protein, a relative escape potential of a mutation, the relative escape potential being derived as a function that combines both semantic change, wherein semantic change is a non-zero degree to which the mutation is recognized by the human immune system, and grammaticality, wherein grammaticality is a degree to which the mutation affects infectivity;
generating a visualization of the relative escape potential across the given protein the visualization depicting areas of enrichment or depletion of escape potential; and
based at least in part on the areas of enrichment or depletion of escape potential depicted in the visualization, identifying a region or sub-region of the given protein having an escape potential of interest.
1. A method of escape profiling for use in association with therapeutic or vaccine development, comprising:
training a language-based model against training data comprising a corpus of protein sequences of a given protein to model an escape profile of the given protein, the escape profile representing, for one or more regions of the given protein, a relative escape potential of a mutation, the relative escape potential being derived as a function that combines both semantic change, representing a degree to which the mutation is recognized by the human immune system, and grammaticality, representing a non-zero degree to which the mutation affects infectivity;
identifying a region of the given protein having an escape potential of interest; and
outputting information regarding the region to one of: a vaccine design workflow, and a therapeutic design workflow.
2. The method as described in claim 1 wherein the corpus of protein sequences of the given protein comprises copies of amino acid sequences from multiple host species.
2. The method as described in claim 1 wherein the corpus of protein sequences of the given protein comprises copies of amino acid sequences from multiple host species.
3. The method as described in claim 1 wherein the language-based model is trained in an unsupervised manner, without data about known escape mutations.
3. The method as described in claim 2 wherein the language-based model is trained in an unsupervised manner, without data about known escape mutations.
4. The method as described in claim 1 wherein the escape potential of interest is a low escape potential, the method further including targeting the region or sub-region for vaccine development.
7. The method as described in claim 1 wherein the escape potential of interest is a low escape potential and the region is targeted for vaccine development.
5. The method as described in claim 1 wherein the escape potential of interest is a high escape potential, the method further including targeting the region or sub-region in an anti-viral therapeutic development.
8. The method as described in claim 1 wherein the escape potential of interest is a high escape potential and the region is targeted for anti-viral therapeutic development.
6. The method as described in claim 1 wherein the mutation is one of: a single mutation, and a combinatorial mutation.
9. The method as described in claim 1 wherein the mutation is one of: a single mutation, and a combinatorial mutation.
7. The method as described in claim 1 wherein the function that combines both semantic change and grammaticality applies a weighting to a score representing one of: the semantic change, the grammaticality, and a combination of semantic change and grammaticality.
10. The method as described in claim 1 wherein the function that combines both semantic change and grammaticality applies a weighting to a score representing one of: the semantic change, the grammaticality, and a combination of semantic change and grammaticality.
8. The method as described in claim 1 wherein identifying the region or sub-region of the given protein performs a constrained semantic change search (CSCS) to identify grammatical mutations to the given protein that induce high semantic change.
11. The method as described in claim 1 wherein identifying the region of the given viral protein performs a constrained semantic change search (CSCS) to identify grammatical mutations to the given protein that induce high semantic change.
9. The method as described in claim 1 wherein the given protein is a viral protein that is one of: influenza hemagglutinin, HIV Env, and SARS-CoV-2 Spike.
12. The method as described in claim 1 wherein the given protein is a viral protein that is one of: influenza hemagglutinin, HIV Env, and SARS-CoV-2 Spike.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bepler T, Berger B. Learning protein sequence embeddings using information from structure (version 2). arXiv preprint arXiv:1902.08661. 2019 Oct 16. (Year: 2019)
This document, filed less than on year before the effective filing date of the instant application, includes further edits and elaborations on the early ideas by some of the inventors.
US-20220172055-A1
Embeddings and sensitive positions of amino acids
US-11386324-B2
Recurrent neural network-based variant pathogenicity classifier, emphasis on convolutional neural network
Hie, Brian , Ellen D. Zhong, Bonnie Berger, and Bryan Bryson. "Learning the language of viral evolution and escape." Science 371, no. 6526 (2021): 284-288 (Year: 2021)
Applicant’s work.
Learning the language of viral evolution and escape. Brian Hie, Ellen Zhong, Bonnie Berger, Bryan Bryson. bioRxiv 2020.07.08.193946; doi: https://doi.org/10.1101/2020.07.08.193946
Applicant’s work as a pre-print.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jesse P Frumkin whose telephone number is (571)270-1849. The examiner can normally be reached Monday - Saturday, 10-5 ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Olivia Wise can be reached at (571) 272-2249. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JESSE P FRUMKIN/Primary Examiner, Art Unit 1685 December 4, 2025