DETAILED ACTION
Applicant’s response filed 11/11/2025 has been fully considered. The following rejections and/or objections are either reiterated or newly applied.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/11/2025 has been entered.
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 .
Claim Status
Claims 21-26 are cancelled by Applicant.
Claims 1-20 are currently pending and are herein under examination.
Claims 1-20 are rejected.
Claims 13 and 20 are objected.
Priority
The instant application does not claim benefit of priority to any earlier filed applications. As such, the effective filing date for claims 1-20 is 05/27/2021.
Information Disclosure Statement
The IDS filed 11/11/2025 follows the provisions of 37 CFR 1.97 and has been considered in full. A signed copy of the list of references cited from this IDS is included with this Office Action.
Claim Objections
Claims 13 and 20 are objected to because of the following informalities:
Claim 13, line 7, recites the phrase “on assignment process” which should be “on an assignment process”.
Claim 20, line 6, recites the phrase “based at least in part peptide properties” which should be “based at least in part on peptide properties”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
35 USC 112(b)
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.
Claim 17 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. This rejection is newly applied.
Claim 17, line 4, recites the phrase “determining that each group associated with the first vaccine plan” which renders the claim indefinite. Claim 16, line 9, associates a first group to a first vaccine plan. Claim 15, line 9, recites that the first group is comprised of “the first peptide associated with the first tier and a second peptide associated with the second tier”. Thus, it is unclear whether the phrase in claim 17 intends to provide a further limitation of the first group being comprised of different groups, or if the phrase actually refers to the different tiers in the first group. To overcome this rejection, clarify how the phrase should be interpreted.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Any newly recited portions herein are necessitated by claim amendment.
Step 2A, Prong 1:
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomena (Step 2A, Prong 1). In the instant application, claims 1-4 recite a system, claims 5-12 recite a method, and claims 13-20 recite a CRM. The instant claims recite the following limitations that equate to one or more categories of judicial exception:
Claim 1 recites “determine, for a subject, different peptides to be assigned to different groups of cancer vaccines for the subject, wherein each group comprises two or more different peptides; determine a peptide property of a peptide from the different peptides, the peptide property comprising at least one of: a class I immunogenicity score, a class II immunogenicity score, or an amino acid sequence length; define a first group of the different groups by assigning first peptides from the different peptides to the first group based at least in part on an assignment process, wherein: the first group has a first group property that comprises a measure of at least one of: class I immunogenicity scores, class II immunogenicity scores, or amino acid sequence lengths of the first peptides; the first group property is within a similarity range relative to a second group property of a second group from the different groups; and the assignment process assigns the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarly range; and generate information indicating that the first peptides are assigned to the first group, the information enabling manufacturing of a vaccine that includes the first group and the second group.”
Claim 2 recites “determine a sorted order of the different peptides based at least in part on individual peptide properties; associate, based at least in part on the sorted order, a first subset of the different peptides with a first tier and a second subset of the different peptides with a second tier, the peptide being a first peptide associated to the first tier; and assign, to the first group, the first peptide associated with the first tier and a second peptide associated with the second tier.”
Claim 3 recites “wherein the sorted order indicates that the first peptide has a top-ranked peptide property and the second peptide has a worst-ranked peptide property.”
Claim 4 recites “execute a combinatorial optimization algorithm configured to (i) determine potential assignments of the different peptides to the different groups, (ii) compute, for each group of the different groups, a group property based at least in part on peptide properties of peptides potentially assigned to the group, and (iii) reduce a difference between group properties of the different groups.”
Claim 5 recites “determining a peptide property of a peptide from different peptides that are to be assigned to different groups of vaccines; determining that the peptide is to be assigned to a first group from the different groups based at least in part on an assignment process, the first group having a first group property that is based at least in part on peptide properties of first peptides to be assigned to the first group, the first group property being within a similarity range relative to a second group property of a second group from the different groups, the assignment process assigning the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property is within the similarity range; and generating information indicating that the peptide is assigned to the first group, the information enabling manufacturing of a vaccine that includes the first group and the second group.”
Claim 6 recites “determining that the different peptides are associated with a subject, wherein the different groups are assigned a same number of peptides and are defined for a cancer vaccine of the subject.”
Claim 7 recites “determining that the peptide is also assigned to the second group; and removing the second group from a candidate set of groups of vaccines.”
Claim 8 recites “determining that the second group is assigned more than one peptide having a particular amino acid; and removing the second group from a candidate set of groups of vaccines.”
Claim 9 recites “defining the different groups by assigning the different peptides to the different groups, wherein only a subset of the different groups is assigned PADRE peptides, and wherein no more than one PADRE peptide is assigned per group of the subset.”
Claim 10 recites “defining the different groups by assigning the different peptides to the different groups, wherein the different peptides comprise a neo-antigen peptide, and wherein the neo-antigen peptide is assigned to only one of the different groups.”
Claim 11 recites “determining that the peptide is a neo-antigen peptide that has a peptide property score larger than a threshold score, wherein the peptide property score comprises at least one of: a class I immunogenic response score or a class II immunogenic response score; and defining the different groups by assigning the different peptides to the different groups, wherein the neo-antigen peptide is assigned to more than one group based at least in part on the peptide property score being larger than the threshold score.”
Claim 12 recites “determining that the different peptides are associated with a subject that has a tumor in an area; determining that the peptide is a neo-antigen peptide that has a peptide property score larger than a threshold score; and associating the first group with the area based at least in part on the neo-antigen peptide being assigned to the first group.”
Claim 13 recites “determining a peptide property of a peptide from different peptides that are to be assigned to different groups of vaccines; determining that the peptide is to be assigned to a first group from the different groups based at least in part on an assignment process, the first group having a first group property that is based at least in part on peptide properties of first peptides to be assigned to the first group, the first group property being within a similarity range relative to a second group property of a second group from the different groups, the assignment process assigning the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property is within the similarity range; and generating information indicating that the peptide is assigned to the first group, the information enabling manufacturing of a vaccine that includes the first group and the second group.”
Claim 14 recites “defining the different groups by assigning the different peptides to the different groups, wherein the different groups are assigned a same number of peptides.”
Claim 15 recites “determining a sorted order of the different peptides based at least in part on individual peptide properties; associating, based at least in part on the sorted order, a first subset of the different peptides with a first tier and a second subset of the different peptides with a second tier, the peptide being a first peptide associated to the first tier; and assigning, to the first group, the first peptide associated with the first tier and a second peptide associated with the second tier.”
Claim 16 recites “wherein the second tier is associated with second peptides having a second sorted order . . . determining an updated order of the second subset by shuffling the second sorted order; defining an updated first group based at least in part on the updated order; and associating the first group with a first vaccine plan and the updated first group with a second vaccine plan.”
Claim 17 recites “determining that each group associated with the first vaccine plan is not assigned more than one peptide having a particular amino acid; and generating information indicating that the first vaccine plan is preferred relative to the second vaccine plan.”
Claim 18 recites “wherein the first tier and the second tier are sorted in a second sorted order . . . determining an updated order of the first tier and the second tier by shuffling the second sorted order; and defining an updated first group based at least in part on the updated order.”
Claim 19 recites “determining a total number of peptides to assign to the different groups; generating a peptide set by associating the peptide with the peptide set and dissociating a second peptide from the different peptides with the peptide set, wherein a size of the peptide set is equal to the total number; defining the different groups by assigning subsets of the peptide set to the different groups; generating an updated peptide set by disassociating the peptide with the peptide set and associating the second peptide with the peptide set, wherein a size of the updated peptide set is equal to the total number; and defining additional groups by assigning subsets of the updated peptide set to the additional groups.”
Claim 20 recites “executing a combinatorial optimization algorithm configured to (i) determine potential assignments of the different peptides to the different groups, (ii) compute, for each group of the different groups, a group property based at least in part peptide properties of peptides potentially assigned to the group, and (iii) and reduce a difference between group properties of the different groups.”
Limitations reciting a mental process
The limitations cited directly above in claims 1-20 of determining, defining, generating information, associating, assigning, executing a combinatorial optimization algorithm, and removing are recited at such a high level of generality that they equate to a mental process because they are similar to the concepts of collecting information, analyzing it, and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), which the courts have identified as concepts that can be practically performed in the human mind.
The broadest reasonable interpretation (BRI) of these limitations includes using a dataset of peptides with associated peptide properties to group the peptides into different groups based upon their peptide properties. The BRI also includes determining whether some groupings are within a similarity range by, for example, calculating averages of the group properties. Information can be generated by using pen and paper to list the groupings. These limitations can be practically performed by a human using pen and paper because they merely require observation, evaluation, judgement, and opinion (MPEP 2106.04(a)(2)). Additionally, a human could also practically perform a combinatorial optimization algorithm, as recited in claims 4 and 20, such as a loss function, as recited in para. [50] of the instant specification, using pen and paper. Therefore, these limitations equate to reciting a mental process.
It is also noted that the following limitation in claims 1, 5 and 13 equates to an intended use and is thus not required by the claims: “the information enabling manufacturing of a vaccine that includes the first group and the second group.”
Limitations reciting a mathematical concept
The limitations cited directly above in claims 4 and 20 equate to a mathematical concept because these limitations are similar to the concepts of organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)), which the courts have identified as mathematical concepts.
The BRI of “(ii) compute, for each group of the different groups, a group property based at least in part on peptide properties of peptides potentially assigned to the group, and (iii) reduce a difference between group properties of the different groups” includes performing calculations. Computing a group property includes calculating an immunogenicity score. Reducing a difference between group properties includes using a loss function as recited in specification para. [50].
As such, claims 1-20 recite an abstract idea (Step 2A, Prong 1: Yes).
Step 2A, Prong 2:
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). The judicial exception is not integrated into a practical application because the claims do not recite additional elements that reflect an improvement to a computer, technology, or technical field (MPEP § 2106.04(d)(1) and 2106.5(a)), require a particular treatment or prophylaxis for a disease or medical condition (MPEP § 2106.04(d)(2)), implement the recited judicial exception with a particular machine that is integral to the claim (MPEP § 2106.05(b)), effect a transformation or reduction of a particular article to a different state or thing (MPEP § 2106.05(c)), nor provide some other meaningful limitation (MPEP § 2106.05(e)). Rather, the claims include limitations that equate to instructions to implement an abstract idea on a computer (MPEP § 2106.05(f)). The instant claims recite the following additional elements:
Claim 1 recites “A system, comprising: one or more processors; and one or more memories storing computer-readable instructions that, upon execution by the one or more processors, configure the system to:”
Claims 2 and 4 recite “The system of claim 1, wherein the one or more memories store further computer-readable instructions that, upon execution by the one or more processors, configure the system to:”
Claim 3 recites “The system of claim 2”.
Claim 13 recites “One or more non-transitory computer-readable storage media storing instructions that, upon execution on a system, cause the system to perform operations comprising:”
Claims 14 and 15 recite “The one more non-transitory computer-readable storage media of claim 13, further storing additional instructions that, upon execution on the system, cause the system to perform operations comprising:”
Claim 16 recites “The one more non-transitory computer-readable storage media of claim 15 . . . wherein one more non-transitory computer-readable storage media store further instructions that, upon execution on the system, cause the system to perform operations comprising:”
Claim 17 recites “The one more non-transitory computer-readable storage media of claim 16 storing additional instructions that, upon execution on the system, cause the system to perform additional operations comprising”
Claim 18 recites “The one more non-transitory computer-readable storage media of claim 15 . . . and wherein one more non-transitory computer-readable storage media store further instructions that, upon execution on the system, cause the system to perform operations comprising:”
Claims 19 and 20 recite “The one or more non-transitory computer-readable storage media of claim 13, further storing additional instructions that, upon execution on the system, cause the system to perform operations comprising:”
Regarding the above cited limitations in claims 1-4 and 13-20 of a system comprising one or more processors and one or more memories storing computer-readable instructions, one or more non-transitory computer-readable storage media storin instructions. There are no limitations that these systems or computer readable media require anything other than a generic computing system. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer, which the courts have established does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984.
As such, claims 1-20 are directed to an abstract idea (Step 2A, Prong 2: No).
Step 2B:
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). These claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because these claims recite additional elements that equate to instructions to apply the recited exception in a generic computing environment (MPEP § 2106.05(f)) and to well-understood, routine and conventional (WURC) limitations (MPEP § 2106.05(d)). The instant claims recite the following additional elements:
Claim 1 recites “A system, comprising: one or more processors; and one or more memories storing computer-readable instructions that, upon execution by the one or more processors, configure the system to:”
Claims 2 and 4 recite “The system of claim 1, wherein the one or more memories store further computer-readable instructions that, upon execution by the one or more processors, configure the system to:”
Claim 3 recites “The system of claim 2”.
Claim 13 recites “One or more non-transitory computer-readable storage media storing instructions that, upon execution on a system, cause the system to perform operations comprising:”
Claims 14 and 15 recite “The one more non-transitory computer-readable storage media of claim 13, further storing additional instructions that, upon execution on the system, cause the system to perform operations comprising:”
Claim 16 recites “The one more non-transitory computer-readable storage media of claim 15 . . . wherein one more non-transitory computer-readable storage media store further instructions that, upon execution on the system, cause the system to perform operations comprising:”
Claim 17 recites “The one more non-transitory computer-readable storage media of claim 16”
Claim 18 recites “The one more non-transitory computer-readable storage media of claim 15 . . . and wherein one more non-transitory computer-readable storage media store further instructions that, upon execution on the system, cause the system to perform operations comprising:”
Claims 19 and 20 recite “The one or more non-transitory computer-readable storage media of claim 13, further storing additional instructions that, upon execution on the system, cause the system to perform operations comprising:”
Regarding the above cited limitations in claims 1-4 and 13-20 of a system comprising one or more processors and one or more memories storing computer-readable instructions, one or more non-transitory computer-readable storage media storin instructions. These limitations equate to instructions to implement an abstract idea on a generic computing system, which the courts have established does not provide an inventive concept in Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). Additionally, storing code on a non-transitory computer readable medium as stated in claims 13-20 equates to storing information in memory, which the courts have established as a WURC function of a generic computer in Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
When these additional elements are considered individually and in combination, they do not provide an inventive concept because they all equate to WURC functions/components of a generic computer and/or generic computing system and because they equate to instructions to apply the judicial exception on a generic computer. Therefore, these additional elements do not transform the claimed judicial exception into a patent-eligible application of the judicial exception and do not amount to significantly more than the judicial exception itself (Step 2B: No).
As such, claims 1-20 are not patent eligible.
Response to Arguments under 35 USC 101
Applicant's arguments filed 11/11/2025 have been fully considered but are persuasive only in part.
Applicant argues that the following limitation is not a mental process because it uses methods that are too computationally complex, particularly when a number of peptides and possible groups increase exponentially: “the assignment process assigns the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarity range” (pg. 9, para. 3 – pg. 10, para. 1 of Applicant’s remarks). Applicant’s remarks are persuasive but only in part for the following reasons:
It is noted that claim 1 does not require that the number of peptides and possible groupings increase exponentially. Claim 1 also does not require use of a combinatorial optimization algorithm or a tournament style algorithm.
The above cited limitation in claim 1 still recites a mental process. A human can assign peptides to a group based on a peptide property. For example, a human can determine that a peptide has 8aa, then assign the peptide to a group with a group property of 7-10 aa. The same could be done with peptides that have associated immunogenicity scores.
Furthermore, a human can determine that adding the peptide of 8 aa to a group with a group property of an average aa length of 8, as opposed to adding a peptide with 5 aa, will keep an intergroup property within a similarity range of 12 aa relative to a second group with a second group property of an average aa length of 20. The same can be done with immunogenicity scores. This interpretation is reinforced by specification para. [47].
Applicant argues that the assignment process in claim 1 is not a mathematical concept (pg. 10, para. 2 of Applicant’s remarks). Examiner agrees that the assignment process, as recited in claim 1, does not recite a mathematical equation or calculation.
Applicant argues that claim 1 improves vaccine manufacturing technology, particularly enabling personalized cancer vaccines that are optimized (pg. 10, para. 3 of Applicant’s remarks). Applicant’s arguments are not persuasive for the following reasons:
It is noted that none of the independent claims require an active step of manufacturing a vaccine. Moreover, it appears that the alleged improvement is a result of the judicial exception itself. MPEP 2106.05(a) recites “the judicial exception alone cannot provide the improvement.” As such, none of the independent claims integrate the judicial exception into a practical application by improving technology.
Applicant argues that claim 1 solves a technological problem assigning patient-specific peptides into groups for vaccines such that each group meets strict similarity criteria, which are then used to manufacture a patient-specific vaccine (pg. 10, para. 4 of Applicant’s remarks). Applicant’s arguments are not persuasive for the following reasons:
It is noted that only claim 1, not claims 5 or 13, requires peptides be associated to a subject for use in a cancer vaccine. Moreover, the limitation in claims 1, 5 and 13 of “the information enabling manufacturing of a vaccine that includes the first group and the second group” is an intended use and is not required by the claim. It also appears that the solution to the proposed technological problem is a result of the judicial exception itself, which cannot provide the improvement (MPEP 2106.05(a)).
Applicant argues that the assignment process provides significantly more because it is not well-understood, routine, and conventional (pg. 10, last para. – pg. 11, para. 1 of Applicant’s remarks). Applicant’s argument is not persuasive for the following reasons:
Applicant appears to make an argument under Step 2B, which evaluates additional elements (MPEP 2106.05.I). However, the assignment process has been identified as reciting a judicial exception.
Applicant argues that the claims are not directed to mere instructions to apply a judicial exception on a generic computer because it achieves a technical result of optimized and manufacturable vaccines (pg. 11, para. 1 of Applicant’s remarks). Applicant’s remarks are not persuasive for the following reasons:
The additional elements of claim 1 are generic computer components that perform the judicial exception. As such, the additional elements equate to mere instructions to implement the abstract idea on a generic computer (MPEP 2106.05(f)).
Applicant appears to argue that claim 1 recites a practical application of the judicial exception by using optimized and manufacturable vaccines that do not cover all forms of peptide groupings or vaccine design (pg. 11, para. 1 of Applicant’s remarks). Applicant’s remarks are not persuasive for the following reasons:
The generated vaccine groups recite a judicial exception. Additional elements alone or in combination or the way in which the additional element(s) interact with the judicial exception may integrate into a practical application (MPEP 2106.04(d).III). However, the generic computer components of claim 1 merely apply the judicial exception, which cannot integrate into a practical application (MPEP 2106.05(f)).
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 5-6, 10, and 13-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Fritsch et al. (“Fritsch”; US 2016/0310584 A1; US App. No. 2 cited on IDS filed 10/03/2022; previously cited), as evidenced by Goodwine (“Computer Architecture”; published on 09/29/2002; previously cited).
The bold and italicized text below are the limitations of the instant claims, and the italicized text serves to map the prior art onto the instant claims.
Any newly recited portions herein are necessitated by claim amendment.
Claims 1, 5 and 13:
A system comprising: one or more processors; and one or more memories storing computer-readable instructions that, upon execution by the one or more processors, configure the system to:
Fritsch discloses methods for neoplasia vaccine and immunogenic composition formulation to treat neoplasia in a subject (abstract) and uses a computer [139]. Computers inherently contain processors and memory as evidenced by Goodwine (Figure 1).
determine, for a subject, different peptides to be assigned to different groups of cancer vaccines for the subject, wherein each group comprises two or more different peptides;
Fritsch formulates vaccines, wherein each vaccine contains a pool of peptides, each pool containing up to 5 peptides [514]. The peptides are identified from the patient [52-55].
determine a peptide property of a peptide from the different peptides, the peptide property comprising at least one of: a class I immunogenicity score, a class II immunogenicity score, or an amino acid sequence length;
Fritsch identifies a mutant peptide that binds to a class I HLA protein with a certain affinity and selects mutant peptides for vaccine composition based upon identifying them as binding to class I HLA protein [62-65]. Fritsch also recites “neoantigens are determined by their affinity to MHC molecules” (immunogenicity score) [139]. Affinities were predicted with netMHCpan which provides a binding affinity score [442-449].
define a first group of the different groups by assigning first peptides from the different peptides to the first group based at least in part on an assignment process, wherein: the first group has a first group property that comprises a measure of at least one of: class I immunogenicity scores, class II immunogenicity scores, or amino acid sequence lengths of the first peptides;
Fritsch shows in Figure 5 placing neoantigens into pools of 4 subgroups [75]. The composition of the pools is selected on the basis of the particular HLA allele to which each peptide is predicted to bind [531]. The table in para. [531] shows different pools with different peptides that bind to different HLA alleles. Affinities were predicted with netMHCpan which provides a binding affinity score to class I HLA allotypes [442-443].
the first group property is within a similarity range relative to a second group property of a second group from the different groups; and the assignment process assigns the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarity range; and
Fritsch teaches “For each patient, peptides predicted to bind up to four different HLA A and B alleles are identified ... The approach to distributing peptides to different pools is to spread each set of peptides associated with a particular HLA allele over as many of the four pools as possible. It is highly likely there are situations where there are more than 4 predicted peptides for a given allele, and in these cases it is necessary to allocate more than one peptide associated with a particular allele to the same pool” [531]. This is being interpreted as a similarity range between groups of 0 to 1. The number 0 represents each group containing only 1 peptide predicted to bind a particular HLA allele. The number 1 represents a group containing more than 1 peptide predicted to bind a particular HLA allele when there are more than 4 predicted peptides for a given allele.
Para. [532] shows a table of the 4 pools, wherein pools 1 and 2 each contain a peptide predicted to bind to HLA A0101, thus pools 1 and 2 contain a predicted property that is within a similarity range (the first group property is within a similarity range relative to a second group property of a second group from the different groups; and the assignment process assigns the first peptides to the first group based at least in part on the peptide property).
Two peptides that bind the same HLA allele in the same group is within the range of 1, as opposed to three peptides that bind the same allele in the same group, which would be outside the range of 0 to 1 (a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarity range).
generate information indicating that the first peptides are assigned to the first group, the information enabling manufacturing of a vaccine that includes the first group and the second group.
Fritsch shows in Figure 5 and in the table in para. [531] assigning peptides to a pool. The pools are prepared and labeled with the specific drug information of the vaccine [533]. Fritsch discusses preparing a pharmaceutical composition comprising the peptides from the pools and administrating it to the patient [65] [516-526].
Claim 2:
determine a sorted order of the different peptides based at least in part on individual peptide properties;
Fritsch discloses predicting which peptides will bind to a specific HLA allele [443-452].
associate, based at least in part on the sorted order, a first subset of the different peptides with a first tier and a second subset of the different peptides with a second tier, the peptide being a first peptide associated to the first tier; and assign, to the first group, the first peptide associated with the first tier and a second peptide associated with the second tier.
All peptides used in a vaccine are distinct [464]. Each peptide is predicted to bind to a specific HLA allele, such as HLA A (first subset with first tier) or HLA B (second subset with second tier). The table in para. [532] shows how a peptide predicted to bind to HLA A (first tier) and HLA B (second tier) is grouped in the same pool (the first group).
Claim 5:
determining a peptide property of a peptide from different peptides that are to be assigned to different groups of vaccines; determining that the peptide is to be assigned to a first group from the different groups based at least in part on an assignment process,
Fritsch discloses formulating vaccines, wherein each vaccine contains a pool of peptides, each pool containing up to 5 peptides (groups of vaccines) [514]. Each peptide has a predicted binding affinity to an HLA allele (peptide property) [442-453]. The composition of the pools is selected on the basis of the particular HLA allele to which each peptide is predicted to bind [531].
the first group having a first group property that is based at least in part on peptide properties of first peptides to be assigned to the first group, the first group property being within a similarity range relative to a second group property of a second group from the different groups, the assignment process assigning the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarity range the first group property is within the similarity range; and
Fritsch teaches “For each patient, peptides predicted to bind up to four different HLA A and B alleles are identified ... The approach to distributing peptides to different pools is to spread each set of peptides associated with a particular HLA allele over as many of the four pools as possible. It is highly likely there are situations where there are more than 4 predicted peptides for a given allele, and in these cases it is necessary to allocate more than one peptide associated with a particular allele to the same pool” [531]. This is being interpreted as a similarity range between groups of 0 to 1. The number 0 represents each group containing only 1 peptide predicted to bind a particular HLA allele. The number 1 represents a group containing more than 1 peptide predicted to bind a particular HLA allele when there are more than 4 predicted peptides for a given allele.
Para. [532] shows a table of the 4 pools, wherein pools 1 and 2 each contain a peptide predicted to bind to HLA A0101, thus pools 1 and 2 contain a predicted property that is within a similarity range (the first group property is within a similarity range relative to a second group property of a second group from the different groups; and the assignment process assigns the first peptides to the first group based at least in part on the peptide property).
Two peptides that bind the same HLA allele in the same group is within the range of 1, as opposed to three peptides that bind the same allele in the same group, which would be outside the range of 0 to 1 (a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarity range).
generating information indicating that the peptide is assigned to the first group, the information enabling manufacturing of a vaccine that includes the first group and the second group.
Fritsch shows in Figure 5 and in the table in para. [531] the peptides that have been assigned to a pool. The pools prepared and labeled with the specific drug information of the vaccine [533]. Fritsch discusses preparing a pharmaceutical composition comprising the peptides from the pools and administrating it to the patient [65] [516-526].
Claim 6:
determining that the different peptides are associated with a subject, wherein the different groups are assigned a same number of peptides and are defined for a cancer vaccine of the subject.
Fritsch discloses generating 20 distinct peptides that are personalized neoantigen peptides unique to each patient [468], wherein 4 pools of peptides contain up to 5 peptides each [464] and are used to create a vaccine [10].
Claim 10:
defining the different groups by assigning the different peptides to the different groups,
Fritsch states that up to 20 distinct peptides may be used to generate 4 distinct pools [464] [468] (Figure 5).
wherein the different peptides comprise a neo-antigen peptide, and wherein the neo-antigen peptide is assigned to only one of the different groups.
Fritsch states that the pharmaceutical composition comprises at least one neo-antigenic peptide [11] (claim 1).
Claim 13:
One or more non-transitory computer-readable storage media storing instructions that, upon execution on a system, cause the system to perform operations comprising:
Fritsch discloses using a computer to perform the analysis of their method [139], wherein computers inherently contain processors and memory as evidenced by Goodwine et al. (Figure 1).
determining a peptide property of a peptide from different peptides that are to be assigned to different groups of vaccines; determining that the peptide is to be assigned to a first group from the different groups based at least in part on an assignment process,
Fritsch discloses formulating vaccines, wherein each vaccine contains a pool of peptides, each pool containing up to 5 peptides [514]. The peptides are identified from the patient [52-55]. The composition of the pools is selected on the basis of the particular HLA allele to which each peptide is predicted to bind [531].
the first group having a first group property that is based at least in part on peptide properties of first peptides to be assigned to the first group, the first group property being within a similarity range relative to a second group property of a second group from the different groups, the assignment process assigning the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that the first group property is within the similarity range; and
Fritsch teaches “For each patient, peptides predicted to bind up to four different HLA A and B alleles are identified ... The approach to distributing peptides to different pools is to spread each set of peptides associated with a particular HLA allele over as many of the four pools as possible. It is highly likely there are situations where there are more than 4 predicted peptides for a given allele, and in these cases it is necessary to allocate more than one peptide associated with a particular allele to the same pool” [531]. This is being interpreted as a similarity range between groups of 0 to 1. The number 0 represents each group containing only 1 peptide predicted to bind a particular HLA allele. The number 1 represents a group containing more than 1 peptide predicted to bind a particular HLA allele when there are more than 4 predicted peptides for a given allele.
Para. [532] shows a table of the 4 pools, wherein pools 1 and 2 each contain a peptide predicted to bind to HLA A0101, thus pools 1 and 2 contain a predicted property that is within a similarity range (the first group property is within a similarity range relative to a second group property of a second group from the different groups; and the assignment process assigns the first peptides to the first group based at least in part on the peptide property).
Two peptides that bind the same HLA allele in the same group is within the range of 1, as opposed to three peptides that bind the same allele in the same group, which would be outside the range of 0 to 1 (a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarity range).
generating information indicating that the peptide is assigned to the first group, the information enabling manufacturing of a vaccine that includes the first group and the second group.
Fritsch shows in Figure 5 and in the table in para. [531] the peptides that have been assigned to a pool. The pools prepared and labeled with the specific drug information of the vaccine [533]. Fritsch discusses preparing a pharmaceutical composition comprising the peptides from the pools and administrating it to the patient [65] [516-526].
Claim 14:
defining the different groups by assigning the different peptides to the different groups, wherein the different groups are assigned a same number of peptides.
Four pools of patient-specific peptides consisting of 5 peptides are prepared [464], wherein the 20 peptides are distinct [468].
Claim 15:
determining a sorted order of the different peptides based at least in part on individual peptide properties;
Fritsch discloses predicting which peptides will bind to a specific HLA allele [443-452].
associating, based at least in part on the sorted order, a first subset of the different peptides with a first tier and a second subset of the different peptides with a second tier, the peptide being a first peptide associated to the first tier; and assigning, to the first group, the first peptide associated with the first tier and a second peptide associated with the second tier.
All peptides used in a vaccine are distinct [464]. Each peptide is predicted to bind to a specific HLA allele, such as HLA A (first subset with first tier) or HLA B (second subset with second tier). The table in para. [532] shows how a peptide predicted to bind to HLA A (first tier) and HLA B (second tier) is grouped in the same pool (the first group).
Response to Arguments under 35 USC 102
Applicant's arguments filed 11/11/2025 have been fully considered but they are not persuasive.
Applicant argues that Fritsch does not disclose the following limitation in claim 1: “the assignment process assigns the first peptides to the first group based at least in part on the peptide property and a determination by the assignment process that assigning the first peptides instead of a different set of peptides to the first group results in the first group property being within the similarity range.” Applicant appears to state that this limitation in claim 1 requires a comparative, algorithmic, or optimization step that selects among different possible groupings to achieve a group property similarity between groups (pg. 11, para. 2 – pg. 13, para. 3 of Applicant’s remarks). Applicant’s remarks are not persuasive for the following reasons:
It is noted that the above recited limitation in claim 1 does not require any comparative, algorithmic, or optimization steps to evaluate different sets of peptides in a group to then select a set of peptides that results in the group being within a similarity range relative to another group. Nor does the limitation require an active step of making a determination by the assignment process. Rather, the limitation under its BRI includes using a previously made determination that assigning one set of peptides rather than another set of peptides (containing different peptides) to a group will keep the group within a similarly range relative to another group. As discussed in the rejection above, Fritsch appears to disclose the above recited limitation in claim 1.
Applicant’s arguments regarding claims 2, 5-6, 10 and 13-15 are not persuasive for the same reasons stated above regarding claim 1 (pg. 13, last para. of Applicant’s remarks).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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.
Claims 3-4, 11-12 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Fritsch et al. (“Fritsch”; US 2016/0310584 A1; US App. No. 2 cited on IDS filed 10/03/2022; previously cited), as evidenced by Goodwine (“Computer Architecture”; published on 09/29/2002; previously cited), as applied to claims 1-2, 5, and 13, in view of Mo et al. (“Mo”; US 2023/0338491 A1; effective filing date 03/08/221; previously cited on PTO892 mailed 04/04/2025).
Any newly recited portions herein are necessitated by claim amendment.
The limitations of claims 1-2, 5, and 13 have been taught by Fritsch and Goodwine in the rejection above in section Claim Rejections - 35 USC § 102.
The bold and italicized text below are the limitations of the instant claims, and the italicized text serves to map the prior art onto the instant claims.
Claim 3:
wherein the sorted order indicates that the first peptide has a top-ranked peptide property and the second peptide has a worst-ranked peptide property.
Fritsch discloses predicting which peptides will bind to a specific HLA allele wherein the peptides are ordered based upon their predicted binding [442-452]. However, Fritsch does not teach ranking the peptides from top-ranked to worst-ranked.
Mo discloses methods for screening individualized tumor neoantigen peptides and vaccines thereof (abstract). Mo arranges the antigen peptides in descending order according to their iNeo_Score and then selecting antigen peptides from top to bottom (abstract).
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Fritsch for grouping neoantigens based on their predicted binding to specific HLA alleles with the method of Mo for ranking neoantigens based on an iNeo_Score. Motivation for doing so is taught by Mo states that their screening method is capable of deriving neoantigens that have good anti-tumor effects [154]. One of ordinary skill in the art would have had a reasonable expectation of success because Fritsch groups neoantigens based on binding affinity to HLA alleles, wherein the combination would rank the neoantigens by iNeo_Score.
Claims 4 and 20:
execute a combinatorial optimization algorithm configured to (i) determine potential assignments of the different peptides to the different groups,
Fritsch discloses grouping peptides into pools (Figure 5), but Fritsch does not disclose potential assignments of peptides into pools.
Mo discloses screening candidate peptides for use in vaccines (abstract). Mo teaches “in a first step, the number of the antigen peptides is known to be p, and according to grouping rules, the number of the groups is determined to be g, and the number of the antigen peptides in each group is expressed by ai, i being 1, 2, 3, . . . , g; a1+a2+ . . . +ag=p. The computer system can list all possible grouping results (a1, a2, . . . , ag) of polypeptides divided into each group according to two data of p and g,” [46].
(ii) compute, for each group of the different groups, a group property based at least in part peptide properties of peptides potentially assigned to the group, and
Fritsch discloses generating group properties based on which HLA allele a peptide binds to [452-453], but Fritsch does not disclose computing group peptide properties based on potentially assigned peptides.
Mo teaches “the system can calculate variance of each group according to grouping results of the polypeptides divided into each group, and rank all of the grouping results of the polypeptides according to the variance in a descending order” [46].
(iii) reduce a difference between group properties of the different groups.
Fritsch does not disclose reducing a difference between group properties of different groups.
Mo also teaches “in a second step, it is checked whether polypeptides with cysteine are evenly distributed in each group, and if the polypeptides with cysteine are not evenly distributed in each group, grouping is continued, if the polypeptides with cysteine are evenly distributed in each group” [47-48].
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Fritsch for grouping peptides based on their predicted binding to HLA alleles by grouping the peptides using the grouping method of Mo. The motivation for doing so is taught by Mo states that their screening and selection process generated vaccines with excellent tumor inhibition effects [63-64]. One of ordinary skill in the art would have had a reasonable expectation of success because the peptides of Fritsch could be sorted in the same way as the peptides in Mo.
Claim 11:
determining that the peptide is a neo-antigen peptide that has a peptide property score larger than a threshold score, wherein the peptide property score comprises at least one of: a class I immunogenic response score or a class II immunogenic response score; and
Fritsch states that the patient-specific peptides may be neonantigenic peptides [13] wherein the neoantigens binding affinity for an HLA allele is predicted [531]. However, Fritsch does teach the binding affinity having a score larger than a threshold score.
Mo calculates an iNeo_Score for a plurality of neoantigen peptides, wherein peptides with a iNeo_Score of 0 are removed [75].
defining the different groups by assigning the different peptides to the different groups,
Fritsch discloses predicting which peptides will bind to a specific HLA allele [126], wherein the peptides are ordered based upon their predicted binding. All peptides used in a vaccine are distinct [464] and peptides predicted to bind to the same MHC allele are placed into separate pools whenever possible [532].
wherein the neo-antigen peptide is assigned to more than one group based at least in part on the peptide property score being larger than the threshold score.
Fritsch shows in the table in para. [531] that a neoantigen predicted to bind a particular HLA allele can be placed into at least two pools (e.g., A1 in pools 1 and 2). However, Fritsch does not assign the neoantigen to different groups if its binding score is above a threshold.
Mo states that a peptide’s iNeo_Score must be greater than 0 in order to be considered a candidate antigenic peptide [6]. Thus, the combination of Fritsch and Mo teach placing a peptide that binds a particular allele into separate groups based on a score being above 0.
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Fritsch for grouping neoantigens based on their predicted binding to specific MLA alleles by
using a threshold of greater than a 0 iNeo_Score as taught by Mo. The motivation for doing so is taught by Mo states that neoantigens selected for vaccine composition using the iNeo_Score showed improved anti-tumor effects as compared to adjuvant groups [154] (Figure 1). One of ordinary skill in the art would have had a reasonable expectation of success because the combination would have resulted in providing further metrics to group peptides.
Claim 12:
determining that the different peptides are associated with a subject that has a tumor in an area;
Fritsch discloses generating neoplasia vaccines that contain peptides designed to be administered to a patient that suffers from a metastatic neoplasia [46].
determining that the peptide is a neo-antigen peptide that has a peptide property score larger than a threshold score; and
Fritsch discloses a neoantigen peptide with predicted properties of binding to different HLA alleles [13] [442-452]. However, Fritsch does not disclose that the predicted properties must be larger than a threshold.
Mo calculates an iNeo_Score for a plurality of neoantigen peptides, wherein peptides with a score of 0 are removed [12].
It would have been prima facie obvious to one of ordinary skill in the art before to have modified the method of Fritsch for grouping neoantigens based on their predicted binding to specific HLA alleles by calculating an iNeo_Score and removing peptides with a score of 0 as taught by Mo because Mo states that neoantigens selected for vaccine composition using the iNeo_Score showed improved anti-tumor effects as compared to adjuvant groups [154] (Figure 1). One of ordinary skill in the art would have had a reasonable expectation of success because the peptides of Fritsch could have been screened using the peptide screening techniques of Mo.
associating the first group with the area based at least in part on the neo-antigen peptide being assigned to the first group.
Fritsch discloses generating neoplasia vaccines that contain neonantigenic peptides designed to be administered to a patient [6] [39]. The vaccine composition can be applied directly to an area of interest including directly on organ or tissue that contains the neoplasia [235] [331].
to stimulate immunity at the tumor site.
Claim 19:
determining a total number of peptides to assign to the different groups;
Fritsch discloses using 20 distinct peptides to generate vaccines that are distributed equally in 4 pools [464] [468].
generating a peptide set by associating the peptide with the peptide set and dissociating a second peptide from the different peptides with the peptide set, wherein a size of the peptide set is equal to the total number;
Fritsch teaches that the five peptides that are placed in a pool are associated with the pool (peptide set) (Figure 5). Each peptide that is moved from the initial 20 peptides into a pool is thus being dissociated from the initial 20 peptides [464] [468].
defining the different groups by assigning subsets of the peptide set to the different groups;
Fritsch teaches that each pool has 5 peptides taken from an initial set of 20 peptides [532].
generating an updated peptide set by disassociating the peptide with the peptide set and associating the second peptide with the peptide set, wherein a size of the updated peptide set is equal to the total number; and defining additional groups by assigning subsets of the updated peptide set to the additional groups.
Fritsch discloses sets of peptides as pools [464] [468]. However, Fritsch does not disclose updating the peptide sets by dissociating and associating peptides nor defining additional groups by assigning subsets of the updated peptide set to the additional groups.
Mo teaches “in a first step, the number of the antigen peptides is known to be p, and according to grouping rules, the number of the groups is determined to be g, and the number of the antigen peptides in each group is expressed by ai, i being 1, 2, 3, . . . , g; a1+a2+ . . . +ag=p. The computer system can list all possible grouping results (a1, a2, . . . , ag) of polypeptides divided into each group according to two data of p and g” [45-46].
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Fritsch for grouping peptides by generating potential groups through an iterative process because Mo states that their screening and selection process generated vaccines with excellent tumor inhibition effects [63-64]. One of ordinary skill in the art would have had a reasonable expectation of because Fritsch already discloses sorting and grouping peptides, wherein the addition of Mo would have added further criteria to sort and group peptides for vaccines.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Fritsch et al. (“Fritsch”; US 2016/0310584 A1; US App. No. 2 cited on IDS filed 10/03/2022; previously cited), as evidenced by Goodwine (“Computer Architecture”; published on 09/29/2002; previously cited), as applied to claim 5, in view of Stanford et al. (“Stanford”; US 11,260,116 B2; effective filing date 05/23/2019; previously cited on PTO892 mailed 04/04/2025).
Any newly recited portions herein are necessitated by claim amendment.
The limitations of claim 5 have been taught by Fritsch and Goodwine in the rejection above in section Claim Rejections - 35 USC § 102.
The bold and italicized text below are the limitations of the instant claims, and the italicized text serves to map the prior art onto the instant claims.
Claim 9:
defining the different groups by assigning the different peptides to the different groups,
Fritsch teaches that 20 peptides are evenly distributed into 4 vaccine pools [39].
wherein only a subset of the different groups is assigned PADRE peptides, and wherein no more than one PADRE peptide is assigned per group of the subset.
Fritsch groups peptides (Figure 5) [464] [468], but Fritsch does not disclose assigning a subset of the groups no more than one PADRE peptide.
Stanford discloses methods for vaccine compositions in the treatment of cancer (abstract). A vaccine composition may contain a T-helper epitope (claim 1 (d)), which may be a PADRE peptide (claim 12) (col. 15, lines 14-17).
It would have been prima facie obvious to one of ordinary skill in the art to have modified the method of Fritsch for generating vaccine pools by including a PADRE peptide in a subset of the groups because Stanford states that T-helper epitopes play an important role in establishing and maximizing the capabilities of the immune system (col. 18, lines 61-67). One of ordinary skill in the art would have had a reasonable expectation of success because Stanford demonstrates that a PADRE peptide can be added to a vaccine composition that contains other peptides and neoantigens intended to treat cancer.
Response to Arguments under 35 USC 103
Applicant's arguments filed 11/11/2025 have been fully considered but they are not persuasive.
Applicant’s arguments regarding claims 3-4, 9, 11-12 and 19-20 are not persuasive because claims 1, 5 and 13 are still rejected under Fritsch (pg. 14 of Applicant’s remarks).
Conclusion
No claims are allowed.
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/N.A.A./Examiner, Art Unit 1687
/KAITLYN L MINCHELLA/Primary Examiner, Art Unit 1685