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 .
Applicant’s amendments and remarks, filed on 11/03/2025, are acknowledged. Applicant’s arguments have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application. Rejections and/or objections not reiterated from the previous office actions are hereby withdrawn.
Status of Claims
Claims 1-5, 7-20 are under examination. Claim 6 is withdrawn.
Priority
The instant application does not claim the benefit of priority under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) to any prior applications. Accordingly, the effective priority date for the instant application is the filing date of 02/25/2021.
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 1-5, 7-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The Supreme Court has established a two-step framework for this analysis, wherein a claim does not satisfy § 101 if (1) it is “directed to” a patent-ineligible concept, i.e., a law of nature, natural phenomenon, or abstract idea, and (2), if so, the particular elements of the claim, considered “both individually and ‘as an ordered combination,” do not add enough to “transform the nature of the claim into a patent-eligible application.” Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016) (quoting Alice, 134 S. Ct. at 2355).
Guidance: Step 1.
Under the broadest reasonable interpretation, the claimed invention (claims 1, 8, and 15 being representative) is directed to a method and system, and therefore fall within one of the four statutory categories.
A. Guidance Step 2A, Prong 1
The Revised Guidance instructs us first to determine whether any judicial exception to patent eligibility is recited in the claim. The Revised Guidance identifies three judicially-excepted groupings identified by the courts as abstract ideas: (1) mathematical concepts, (2) certain methods of organizing human behavior such as fundamental economic practices, and (3) mental processes. Regarding claim(s) 1, 8, and 15, the following steps encompass an abstract idea:
training, by one or more computer processors, a machine learning model using molecule representations and molecule attribute regressor functions, yielding an embedding of the molecule representations;
training, by the one or more computer processors using the machine learning model, a molecule attribute predictor function;
training, by the one or more computer processors, an augmented version of the machine learning model including the molecule attribute predictor function;
training, by one or more computer processors, a binding affinity model using a first database comprising protein sequence representations, the embedding of the molecule representations an embedding of a molecular database, and latent molecule features from the machine learning model and the augmented machine learning model, to predict on-target and off- target molecule-protein affinities;
generating, by the machine learning model, a molecule design according to utilizing the embedding of the molecule representations molecular database and the vector representation of the target protein sequence, a molecule design satisfying the target specificity value range, a drug likeliness attribute, and the target selectivity value range, using conditional latent space sampling;
determining, by the binding affinity model, a binding affinity between the molecule design the target protein sequence, and a binding affinity between the molecule design and a non-target protein sequence;
conducting, by the one or more computer processors, in silico target protein sequence docking screening;
Mathematical Concept
At least one training step uses molecular representations and regressor functions (i.e. mathematical equations). Accordingly, said training is associated with specific mathematical calculations. Similarly, the step for training a binding affinity model uses a sequence database and molecular features from the learning model (which requires mathematical calculations as set forth ab0ve). The specification also teaches that training may further include the use of mathematical functions and language models, e.g. GLOVE, WORD2VEC, etc. [0018, 0022]. Accordingly, when given their broadest reasonable interpretation in light of the background, the training as claimed includes mathematical calculations.
The step for generating a molecule design uses the learning model and a vector representation. In addition, the specification clearly teaches mathematical operations for conditional model design [0026]. Accordingly, when read in light of the specification, the above step amounts to generating a design using an algorithm that performs mathematical calculations (since vectors are well known mathematical concepts for representing data or performing calculations).
The step for determining a binding affinity uses a learning model. Accordingly, when read in light of the specification, this step also amounts to using an algorithm that performs a mathematical calculation for binding affinity. In addition, while the claims do recite a “learning model” and “binding affinity model”, it is important to note that the claims do not impose any specificity with regards to the nature or structure of the claimed “models”. As such, these limitations appear to be nothing more than a claim drafting strategy to circumvent the basic exceptions to § 101 using highly stylized language or hollow field-of-use limitations. Applicant is reminded that the Federal Circuit has cautioned against such overly formalistic approaches to subject-matter eligibility that invite manipulation by patent applicants. CLS Bank v. Alice Corp. (Fed. Cir. 2013) (en banc).
With regards to said conducting, this step requires in silico docking screening. A review of the specification [0014] teaches traditional in silico molecule design and screening methods rely on rational design methods that need physics-based simulations, heuristic search algorithms, and considerable domain knowledge. Accordingly, when given their broadest reasonable interpretation in light of the background, the training as claimed includes mathematical calculations. Therefore, when read in light of applicant’s own specification, the claims are directed to mathematical concepts. See MPEP 2106.04 and 2106.05(II). [Step 2A, Prong 1: YES].
Mental Processes
With regards to said training, the claim does not provide any details with regards to how the training is performed or how the trained model operates. Accordingly, the plain meaning of training encompasses mental observations or evaluations, e.g., a computer programmer merely inputting data into a model (i.e. an equation).
With regards to said conducting, the claim does not provide any details with regards to how the in silico protein sequence screening is performed or how screening is achieved. Accordingly, the plain meaning of screening encompasses mental observations or evaluations, e.g., a computer programmer merely observing data and making a decision. In addition, the specification describes processes for in silico screening that clearly use algorithms for performing the above functions [0014]. As such, the specification provides sufficient evidence that the claims are directed to an abstract idea since the specific descriptions provided for accomplishing these tasks include only data reception and analysis, which may be performed in the human mind via normal processes of observation and evaluation. For these reasons, but for the recitation of processors, the above step falls within the mental process groupings of abstract ideas. See MPEP 2106.04(a)(2), subsection III. [Step 2A, Prong 1: YES].
B. Guidance Step 2A, Prong 2
Having made that determination, under the 2019 Guidance, the examiner next determines whether there are additional elements beyond the recited abstract idea(s) that integrate them into a practical application.
In this case, the additional steps/elements that are not part of the abstract idea are as follows:
receiving, by the one or more computer processors, over a network, a vector representation of a target protein sequence, a target specificity value range, and a target selectivity value range;
providing, by the one or more processors, over the network, a molecule design selected for satisfying the target specificity value range ,drug likeliness, and the target selectivity value range.
With regards to the receiving step, this step is not limited to any particular techniques or devices and results in obtaining data for use by the abstract idea. Therefore, this step amounts to insignificant extra-solution activity and is not indicative of an integration into a practical application. See MPEP 2106.05(g).
With regards to said providing, this step is recited at a high level of generality and is not limited to any particular acts or operations. Accordingly, this limitation encompasses outputting a molecule design (i.e. outputting information) and therefore amounts to insignificant extra-solution activity. See MPEP 2106.05(g).
With regards to the claimed “processors”, “network”, and various “databases”, these limitations are recited at high level of generality and read on a computer and generic databases. Accordingly, they are merely being used as tools to perform generic computer functions or the abstract idea, as discussed above in Step 2A, Prong One, and therefore amount to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application. [Step 2A, Prong 2: NO].
C. Guidance Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amount to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As discussed above, the non-abstract steps/elements amount to nothing more than insignificant extra-solution activity. Moreover, Gupta et al. (Mol. Inf. 2018, 37, 1700111, pp.1-9) teaches using generative network models for de novo drug design that include receiving sequence data and providing molecule designs that meet specific design criteria [Section 3.1-3.4 and Figures 7, 8]. Therefore, even upon reconsideration, there is nothing unconventional with regards to the above non-abstract elements/steps. See MPEP 2106.05(d)(Part II). In addition, with regards to the claimed processor and databases, these are generically recited, routine and conventional elements, and the courts have explained that the use of generic computer elements do not alone transform an otherwise abstract idea into patent-eligible subject matter. See DDR Holdings (Fed. Cir. 2014). Thus, the independent claim(s) as a whole do not amount to significantly more than the exception itself. Therefore, the claim(s) is/are not patent eligible. [Step 2B: NO].
Dependent Claims
Dependent claims 2-5, 7, 9-20 have also been considered under the two-part analysis but do not include additional steps/elements appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception(s) for the following reasons. Regarding claim(s) 2, 3, 4, 7, 9, 10, 11, 14, 16, 17, 18, 20, these are all directed to limitations that further limit the specificity of the abstract idea set forth above and therefore are also encompass a mental processor and/or mathematical concepts for reasons discussed above in the Step 2A (prong 1) analysis. Regarding claim(s) 4, 5, 12, 13, 18, 19, these claims further limit the nature of the data being used by the abstract idea or additional functional limitations directed to acquiring data for use by the abstract idea. Accordingly, these claims amount to “insignificant extra-solution activity”, i.e. activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Therefore, the above steps do not integrate the judicial exception into a practical application. See MPEP 2106.05(g). Therefore, the claims as a whole are not patent eligible.
Response to Arguments
Applicant’s arguments, filed 11/03/2025, have been fully considered but are not persuasive for the following reasons.
Applicant argues that the claimed invention provides a technical solution and improvement to technology which lies in the “training”, “generating”, and “determining” steps. In response, this argument is not persuasive because these steps were interpreted as part of the abstract idea and analyzed under the Step 2A (prong 1) analysis. In other words, applicant is essentially arguing that the inventive concept is the abstract idea (which is used to identify successful drug candidates faster and with less cost). However, Applicant is reminded that “[i]t has been clear since Alice that a claimed invention’s use of the ineligible concept to which it is directed cannot supply the inventive concept that renders the invention ‘significantly more’ than that ineligible concept.” BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir. 2018). On this point, the courts have recently instructed that “[t]he different use of a mathematical calculation, even one that yields different or better results, does not render patent eligible subject matter.” Board Of Trustees Of Leland Stanford Junior University, 991 F.3d 1245, 1251 (Fed. Cir. 2021). In summary, while appellant’s particular algorithmic approach may be a particular way to achieve an alternative solution for generating drug candidates, the claimed invention is, nevertheless, directed to an improved algorithmic analysis. As such, the claims do not integrate the recited judicial exception into a practical application. For at least these reasons, the rejection is maintained
Applicant argues that the claimed invention integrates its features into a practical application of “providing” molecule drug designs satisfying user criteria. In response, the examiner has provided clear and sufficient reasons as to why the steps for receiving (data) and providing (data) amount to insignificant extra-solution activity and do not integrate the recited judicial exception into a practical application of the exception (Step 2A, prong 2 analysis). For these reasons, the examiner maintains that the claims as a whole do not integrate the abstract idea into a practical application. Similar to Recentive v. Fox, applicant is reminded that AI and machine learning claims need to demonstrate a genuine technological advancement beyond merely applying generic ML to a new use case or achieving increased speed and efficiency to be considered patent-eligible under Section 101. See MPEP 2106.04(d)(1). In summary, the claims result in providing a generic molecule design (i.e. information) and the claims do not delineate steps through which the machine learning technology achieves an improvement. Neither Applicant nor the specification provides any objective evidence of an improvement to the technology, nor does the specification explain the details of an unconventional technical solution expressed in the claim, or identify technical improvements realized by the claim over the prior art. See MPEP 2106.04(d)(1) and MPEP 2106.05(a). For these reasons, the examiner maintains that he has carefully applied the two-step analysis and the claims are not patent eligible.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), first paragraph:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same and shall set forth the best mode contemplated by the inventor of carrying out his invention.
The following rejection is modified in view of applicant’s amendments.
Claims 1-5, 7-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
The written description requirement is separate and distinct from the enablement requirement. The specification must: (1) describe the claimed invention in a manner understandable to a person of ordinary skill in the art, and (2) show that the inventor actually invented the claimed subject matter.
Regarding claim(s) 1, 8, and 15, the specification fails to provide written description support for the following steps:
training, by one or more computer processors, a machine learning model using molecule representations and molecule attribute regressor functions, yielding an embedding of the molecule representations;
training, by the one or more computer processors using the machine learning model, a molecule attribute predictor function;
training, by the one or more computer processors, an augmented version of the machine learning model including the molecule attribute predictor function;
training, by one or more computer processors, a binding affinity model using a first database comprising protein sequence representations, the embedding of the molecule representations an embedding of a molecular database, and latent molecule features from the machine learning model and the augmented machine learning model, to predict on-target and off- target molecule-protein affinities;
In this case, the training of a “machine learning model”, “molecular attribute predictor function”, “augmented” molecular attribute predictor function, and “binding affinity model” appear to be critical aspects of the claimed invention. However, the models are generically recited and the specification does not provide any significant structural or functional details with regards to the claimed models, e.g. how they were trained, validated, or other specific details with regards to how the models operate (specific model parameters). In other words, the claimed models are essentially a black box to achieve the claimed functions. At best, the specification teaches a limited example encompasses “a set of molecules described using simplified molecular line-entry system (SMILES) representations” [0018] and generically references “molecule attribute regressor functions in training the VAE” [0019]. However, these are not limiting definitions and it is improper to import narrowing limitations into the claims. See MPEP 2111.01. In addition, the claims are not limited to any particular disease/condition being treated by the claimed drug. Moreover, one of ordinary skill in the art would recognize that training models for drug design are not trivial. As supporting evidence on this point, applicant is directed to Chenthamarakshany et al. (2020, previously cited) which teaches a method for designing new drug-like small molecules for teaching COVID by training a molecular SMILES Variational Autoencoder (VAE) [See entire]. Unlike the instant disclosure, the reference is limited to training a well-defined model to design drugs for a particular condition (COVID). Additionally, Isayev et al. (WO/2019018780) teaches computational methods for de-novo drug discovery based on deep learning and reinforcement learning techniques. Unlike the instant claims, the reference teaches training well-defined neural network models (i.e. mathematically defined) using specific learning algorithms [see entire]. They also evaluate models with quantitative approaches and provide visualization and interpretation of internal representation vectors for both predictive and generative models. Notably, this reference also includes language that could be used to overcome some of the rejections under 35 USC 112(b) and improve the clarity of the instantly claimed invention (see, e.g. reference claims 1 and 11).
Therefore, neither the instant claims nor the specification provides sufficient written description for the breadth of models and diseases encompassed by the claims such that one of skill in the art would have been aware that applicants were actually in possession of models configured to perform the claimed. “[A] sufficient description of a genus . . . requires the disclosure of either a representative number* of species falling within the scope of the genus or structural features common to the members of the genus so that one of skill in the art can 'visualize or recognize' the members of the genus” (AbbVie, 759 F.3d at 1297, reiterating Eli Lilly, 119 F.3d at 1568-69)(emphasis added).
For the reasons discussed above, the specification does not satisfy the written description requirement with respect to the full scope of what is being claimed. For more information regarding the written description requirement, see MPEP §2161.01- §2163.07(b).
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 1-5, 7-20 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 pre-AIA the applicant regards as the invention. Claims that depend directly or indirectly from claim(s) 1, 8, 15 is/are also rejected due to said dependency.
Claims 1, 8, 15 recite “training, by one or more computer processors, a machine learning model using molecule representations and molecule attribute regressor functions, yielding an embedding of the molecule representations.” This phrase remains problematic for the following reasons. (1) It is unclear what is meant by “an embedding of the molecule representations”. A review of the specification does not provide any limiting definition or clarifying guidance such that the artisan would recognizes what structural or functional limitation is intended by the term “embedding”. (2) It remains unclear as to the metes and bounds of the claimed “training”, as this is merely achieved by “using molecule representations and molecule attribute regressor functions”. For example, the artisan would recognize that learning algorithms usually involve well-defined model parameters (learned from data) and hyperparameters (set beforehand to guide the algorithms). However, the claim does not set forth any steps involved in the method/process of use and a review of the specification does not provide any relationship (mathematical or otherwise) between the claimed model and the interaction dataset. Accordingly, it is unclear what actually steps and/or operations are encompassed by said “training”. A claim is indefinite where it merely recites a use without any active, positive steps delimiting how this use is actually practiced. See MPEP § 2173.05(q).
Applicant’s arguments have been fully considered but are not persuasive, as they do not include any illuminating arguments or clarifying amendments. Moreover, applicant is reminded that it is improper to import narrowing limitations from the specification into the claims. MPEP 2111.01. Accordingly, this rejection is maintained/modified in view of applicant’s amendments.
Claims 1, 8, 15 recite “training, by the one or more computer processors using the machine learning model, a molecule attribute predictor function.” It is unclear as to the metes and bounds of the claimed “molecular attribute predictor function”. For example, the artisan would recognize that learning algorithms usually involve well-defined model parameters (learned from data) and hyperparameters (set beforehand to guide the algorithms). However, the claim does not set forth any steps involved in the method/process of use and a review of the specification does not provide any relationship (mathematical or otherwise) between the claimed model and the interaction dataset, and a review of the specification does not provide any limiting that would serve to clarify what mathematical function is encompassed. Clarification is requested via amendment.
Claims 1, 8, 15 recite “training, by one or more computer processors, a binding affinity model using a first database comprising protein sequence representations, an embedding of a molecular database, and latent molecule features from the machine learning model.” This phrase is problematic for the following reasons. It is unclear as to the metes and bounds of the claimed “training”, as this is merely achieved by “using a first database comprising protein sequence representations, an embedding of a molecular database, and latent molecule features”. However, the claim does not set forth any steps involved in the method/process of use, i.e. this is a use type claim. Moreover, a review of the specification does not provide any relationship (mathematical or otherwise) between the claimed model and the interaction dataset. Accordingly, it is unclear what actually steps and/or operations are encompassed by said “training”. A claim is indefinite where it merely recites a use without any active, positive steps delimiting how this use is actually practiced. See MPEP § 2173.05(q). (3) It remains unclear as to the metes and bounds of the claimed “latent molecule features” such that artisan would recognize the type of data encompassed. A review of the specification does not provide any limiting definitions for these terms such that the artisan would know how to avoid infringement. The specification discloses “a set of molecules described using simplified molecular line-entry system (SMILES) representations” [0018] and generically references “molecule attribute regressor functions in training the VAE” [0019]. However, these are not limiting definitions and it is improper to import narrowing limitations into the claims. See MPEP 2111.01. Clarification is requested via amendment.
Applicant’s arguments have been fully considered but are not persuasive, as they do not include any illuminating arguments or clarifying amendments. Moreover, applicant is reminded that it is improper to import narrowing limitations from the specification into the claims. MPEP 2111.01. Accordingly, this rejection is maintained/modified in view of applicant’s amendments.
Double Patenting
The non-statutory 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. See 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); ln re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 C.F.R. 1.321 (c) may be used to overcome an actual or provisional rejection based on a non-statutory double patenting ground provided the conflicting application or patent is shown to be commonly owned with this application. See 37 C.F.R. 1.130(b). Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 C.F.R. 3.73(b). [See also MPEP 804.02].
The conclusion of obviousness-type double patenting is made in light of these factual determinations. Any obviousness-type double patenting rejection should make clear: (A) The differences between the inventions defined by the conflicting claims; and (B) The reasons why a person of ordinary skill in the art would conclude that the invention defined in the claim at issue is anticipated by, or would have been an obvious variation of the invention defined in a claim in the patent.
Claims 1-5, 7-20 are provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-17 of US application 17/185148. The differences between the inventions defined by the conflicting claims are as follows: Reference claim(s) 1 of the ‘148 application is a species of the genus recited in instant claim(s) 1, 8, 15 of the instant patent application, because the cited reference claim(s) teach all of the limitations of instant claim(s) 1, 8, 15, plus additional features and/or limitations. Therefore, instant claim(s) 1-5, 7-20 is/are anticipated by the narrower claims (i.e. species anticipates the genus). This is a provisional obviousness-type double patenting rejection because the conflicting claims have not in fact been patented.
Response to Arguments
Applicant’s arguments have not challenged the merits of these rejections and no terminal disclaimers in compliance with 37 C.F.R. 1.321 (c) have been filed to overcome these rejections, as required by 37 C.F.R. 1.130(b). Accordingly, the above rejections are maintained for reasons of record.
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PABLO S WHALEY whose telephone number is (571)272-4425. The examiner can normally be reached between 1pm-9pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Anita Coope can be reached at 571-270-3614. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PABLO S WHALEY/Primary Examiner, Art Unit 3619
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