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 .
DETAILED ACTION
This is a reply to the application filed on 4/2/2025, in which, claim(s) 1-13 are pending.
Priority
Acknowledgment is made of applicant's claim for foreign priority under 35 U.S.C. 119(a)-(d). Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/2/2025, has been reviewed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the examiner is considering the information disclosure statement.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Drawings
The drawings filed on 4/2/2025 is/are accepted by The Examiner.
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.
Claim(s) 1-13 is/are rejected under 35 U.S.C. 101 because the claimed is being directed to non-statutory subject matter.
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. Claim(s) 1-13 is/are directed to a method and system. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more. Based upon consideration of all of the relevant factors with respect to the claims as a whole, claims are held to claim an unpatentable abstract idea, and are therefore rejected as ineligible subject matter under 35 U.S.C. § 101.
Inventions for a “new and useful process, machine, manufacture, or composition of matter” generally constitute patent-eligible subject matter. 35 U.S.C. § 101. However, the U.S. Supreme Court has long interpreted 35 U.S.C. § 101 to include implicit exceptions: “[l]aws of nature, natural phenomena, and abstract ideas” are not patentable. Alice Corp. v. CLS Bank Int’1l, 573 U.S. 208,216 (2014).
The Supreme Court, in Alice, reiterated the two-step framework previously set forth in Mayo Collaborative Services v. Prometheus Laboratories, Inc., 566 U.S. 66 (2012), “for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent- eligible applications of those concepts.” Alice Corp., 573 U.S. at 217. The first step in that analysis is to “determine whether the claims at issue are directed to one of those patent-— ineligible concepts.” Id. If the claims are not directed to a patent-ineligible concept, e.g., an abstract idea, the inquiry ends. Otherwise, the inquiry proceeds to the second step where the elements of the claims are considered “individually and ‘as an ordered combination’” to determine whether there are additional elements that “‘transform the nature of the claim’ into a patent-eligible application.” Id. (quoting Mayo, 566 U.S. at 79, 78). This is “a search for an ‘inventive concept’ - i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself.’” Id. at 217-18 (alteration in original).
The USPTO published revised guidance on January 7, 2019, for use by USPTO personnel in evaluating subject matter eligibility under 35 U.S.C. § 101. 2019 REVISED PATENT SUBJECT MATTER ELIGIBILITY GUIDANCE, 84 Fed. Reg. 50 (Jan. 7, 2019) (the “2019 Revised Guidance”). That guidance revised the USPTO's examination procedure with respect to the first step of the Mayo/Alice framework by (1) “[p]roviding groupings of subject matter that [are] considered an abstract idea”; and (2) clarifying that a claim is not “directed to” a judicial exception if the judicial exception is integrated into a practical application of that exception. Id. at 50.1
The first step, as set forth in the 2019 Revised Guidance (i.e., Step 2A), is, thus, a two-prong test. In Step 2A, Prong One, we look to whether the claim recites a judicial exception, e.g., one of the following three groupings of abstract ideas: (1) mathematical concepts; (2) certain methods of organizing human activity, e.g., fundamental economic principles or practices, commercial or legal interactions; and (3) mental processes. See 2019 Revised Guidance, 84 Fed. Reg. at 54; MPEP §§ 2106.04(II) (A) (1), 2106.04(a). If so, we next determine, in Step 2A, Prong Two, whether the claim as a whole integrates the recited judicial exception into a practical application of that exception, i.e., whether the additional elements recited in the claim beyond the judicial exception, apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. See 2019 Revised Guidance, 84 Fed. Reg. at 54-55; MPEP §§ 2106.04 (IT) (A) (2), 2106.04(d). Only if the claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application do we conclude that the claim is “directed to” the judicial exception, e.g., an abstract idea. See 2019 Revised Guidance, 84 Fed. Reg. at 54-55; MPEP § 2106.04 (IT) (A) (2).
If the claim is determined to be directed to a judicial exception under Step 2A, we next evaluate the additional elements, individually and in combination, in Step 2B, to determine whether they provide an inventive concept, i.e., whether the additional elements or combination of elements amounts to significantly more than the judicial exception itself; only then, is the claim patent eligible. See 2019 Revised Guidance, 84 Fed. Reg. at 56; MPEP § 2106.05.
Step One of the Mayo/Alice Framework (2019 Revised Guidance, Step 2A)
2019 Revised Guidance, Step 2A, Prong 1
The abstract idea to which claims 1-13 are directed to is mental process such as concepts performed in the human mind (including an observation, evaluation, judgement, opinion) and mathematical relationships/calculations. In particular, the claims recite the following abstract concepts:
“obtaining by an obtaining unit input data from at least one section of the industrial plant, wherein the input data comprises environmental data and/or operational data of the at least one section” (i.e., abstract idea of receiving and collecting data/information as found abstract by the Courts in Internet Patents, Content Extraction, Digitech, CyberSource, Electric Power Group, Classen, FairWarning)
“determining by a processing unit a context factor score for the at least one section of the industrial plant based on at least one pre-determined context factor and the input data, wherein the at least one context factor comprises a relation between the input data and context data of the at least one section, wherein the context data comprises at least one context dependent property of the at least one section” (i.e., abstract idea of mental process of detecting, analyzing data, data recognition and storage as found abstract by the Courts in TLI Comms, Digitech, SmartGene, Bancorp Servs, Electric Power Group, Classen, FairWarning, Cybersource)
“determining by the processing unit the context threat score based on the at least one context factor score.” (i.e., abstract idea of mental process of detecting, analyzing data, data recognition and mathematic concepts as found abstract by the Courts in TLI Comms, Digitech, SmartGene, Bancorp Servs, Electric Power Group, Classen, FairWarning, Cybersource)
The Supreme Court and Federal Circuit have identified abstract ideas in patent claims by making comparisons to concepts found in past decisions to be judicial exceptions to eligibility. The 2019 IEG summarizes concepts the courts have considered to be abstract ideas by associating eligibility decisions with judicial descriptors (e.g., “an idea of itself,” “certain methods of organizing human activities”, “mathematical relationships and formulas”) based on common characteristics. These associations define the judicial descriptors in a manner that stays within the confines of the judicial precedent, with the understanding that these associations are not mutually exclusive, i.e., some concepts may be associated with more than one judicial descriptor.
The abstract functions of the claims in the case are claim(s) is/are directed to system and method of receiving and analyzing data, data recognition (i.e., abstract idea mental process) and determining a threat score as defined by the claimed steps above.
Looking at the steps of the claims, for each of the claims, data is simply being collecting, analyzing data, data recognition and manipulate using mathematic concepts, which was ruled abstract in:
a. Collecting and comparing known information (Classen);
b. Comparing information regarding a sample or test subject to a control or target data (Ambry/Myriad CAFC);
c. Collecting and analyzing information to detect misuse and notifying a user when misuse is detected (FairWarning);
d. Data recognition and storage (Content Extraction);
e. Obtaining and comparing intangible data (Cybersource);
f. Collecting, selecting, categorizing, analyzing, and displaying certain results of the collection and analysis (Electric Power Group);
g. Organizing and manipulating information through mathematical correlations (Digitech);
h. Virus Screening (int. Ventures v. Symantec ‘610 patent);
i. A mathematical formula for calculating parameters indicating an abnormal condition (Grams).
Furthermore, the invention is nothing more than data collecting, comparing and removing as described in the claims that can be performed mentally (or with a pen and piece of paper). The steps are similar to concepts and ideas that have been identified as abstract by the courts. For example, collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group); removing of particular data (Digitech) and obtaining and comparing intangible data (Cybersource). While the specific facts of the case differ from these cases, the claims are still directed to collecting, comparing, and removing information and providing known information.
2019 Revised Guidance, Step 2A, Prong 2
The 2019 Revised Guidance sets forth a non-exhaustive listing of considerations indicative that an additional element or combination of elements may have integrated a recited judicial exception into a practical application. See 2019 Revised Guidance, 84 Fed. Reg. at 55; MPEP § 2106.04(d). In particular, the Guidance describes that an additional element may have integrated the judicial exception into a practical application if, inter alia, the additional element reflects an improvement in the functioning of a computer or an improvement to other technology or a technical field. Id. At the same time, the Guidance makes clear that merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea; adding insignificant extra-solution activity to the judicial exception; or only generally linking the use of the judicial exception to a particular technological environment or field are not sufficient to integrate the judicial exception into a practical application. Id.
The abstract functions of the claims in the case are claim(s) is/are directed to system and method of collecting data, analyzing data, data recognition (i.e., abstract idea mental process) and generating threat scores (i.e., abstract idea mathematics concept) defined by the claimed steps. The claims do not require an arguably inventive set of components, methods, or algorithms. The abstract idea is implemented using generic computing elements (“computers, programs, medium”) and an off the shelf that do not integrate a practical application of the abstract idea in the claims (step 2A, prong 2). Accordingly, even in combination, these additional generic computing elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims recite a mental process, i.e., an abstract idea, and that the additional elements recited in the claim beyond the abstract idea are no more than generic computer components used as tools to perform the recited abstract idea and insignificant extra-solution activity. As such, they do not integrate the abstract idea into a practical application. See Alice Corp., 573 U.S. at 223-24 ("(Wholly generic computer implementation is not generally the sort of ‘additional feature[s] that provides any ‘practical assurance that the process is more than a drafting effort designed to monopolize the abstract idea itself.’” (quoting Mayo, 566 U.S. at 77)); 2019 Revised Guidance, 84 Fed. Reg. at 55 (identifying “an additional element adds insignificant extra-solution activity to the judicial exception” and “an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use” as examples in which a judicial exception has not been integrated into a practical application).
Step Two of the Mayo/Alice Framework (2019 Revised Guidance, Step 2B)
Step 2B: Considering Additional Elements
The considerations are whether the claim includes:
Improvements to another technology or technical field;
Improvements to the functioning of the computer itself;
Applying the judicial exception with, or by use of, a particular machine;
Effecting a transformation or reduction of a particular article to a different state or thing;
Adding a specific limitation other than what is well-understood, routine and conventional in the field, or adding unconventional steps that confine the claim to a particular useful application;
Other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment;
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer;
Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception;
Adding insignificant extra-solution activity to the judicial exception;
Generally linking the use of the judicial exception to a particular technological environment or field of use.
The relevant question under Step 2B is whether claim includes an additional element or combination of elements adds specific limitations beyond the judicial exception that are not “well-understood, routine, conventional activity” in the field or simply appends well-understood, routine, conventional activities previously known to the industry to the judicial exception. Here, the additional elements of claim beyond the abstract idea, namely, a “computer hardware”, “programs”, “machine learning model” is a conventional computing equipment and algorithm used in a well-understood, routine, and conventional manner. These additional elements do not provide an inventive concept; rather, they simply append well-understood, routine, conventional activities previously known to the industry to the judicial exception.
Applying the test to the claims in the application, the structural elements of the claims, which include a computer when taken in combination with the functional elements claim(s) is/are directed to system and method to collect data analyzing, detecting, and determine threat scores b anomaly detection system, together do not offer “significantly more” than the abstract idea itself because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of any computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment (a general purpose computer and/or environment of the user). When considered as an ordered combination, the Examiner does not find any combination of the additional elements that amounts to more than the sum of the parts. The Examiner finds that the individual elements of the claims are performing their intended roles and functions. In most cases, the additional elements are applied merely to carry out data processing, as discussed above, fall under well-understood, routine, and conventional functions of generic computers in our common day-to-day interactions. Therefore, the claimed interactions of the various generically recited methods/devices lacks an unconventional step that confines the claim to a particular useful application in the sense that the result is equivalent to purely mental activity and mathematic concept.
Dependent claims do not add an inventive step to the abstract idea of the independent claims and are therefore rejected based on the aforementioned rationale discussed in the rejection. Dependent claims 2-11, pertain to input factors and output scores without adding any inventive concept or using an unconventional computing element or improving the underlying computer technology.
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.
Claim(s) 1-8, 10-13 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Brunza et al. (US 20220342988 A1; hereinafter Brunza).
Regarding claims 1, 12, 13, Brunza discloses a computer-implemented method for determining a context threat score in an industrial plant [Brunza; Abstract], the method comprising:
obtaining by an obtaining unit input data from at least one section of the industrial plant, wherein the input data comprises environmental data and/or operational data of the at least one section (an industrial control system over a data communication network, cross-correlated behaviors of an information technology domain, an operational technology domain, and a physical access domain and associated threats. The method including receiving first sensor data from the information technology domain, second sensor data from the operational technology domain, and third sensor data from the physical access domain [Brunza; ¶7, 36-54; Figs. 1-3 and associated texts]);
determining by a processing unit a context factor score for the at least one section of the industrial plant based on at least one pre-determined context factor and the input data, wherein the at least one context factor comprises a relation between the input data and context data of the at least one section, wherein the context data comprises at least one context dependent property of the at least one section (fusing the sensor data of each of the domains to obtain fused sensor data; determining feature sets from the fused sensor data using behavior profiles; constructing behaviors as sets of the features over particular time periods; classifying the behaviors to determine a degree of anomaly, classifying anomalous behaviors to determine a threat probability [Brunza; ¶7, 36-54; Figs. 1-3 and associated texts]);
determining by the processing unit the context threat score based on the at least one context factor score (determined degree of anomaly and the determined threat probability, a Model Scoring circuitry 560, a best machine learning model may be selected and provided as a deployed machine learning model 566 in a deployed service 564. The deployed service 564 may be accessed by one or more client computer devices 562. Results of the deployed machine learning model 566 are provided to a scoring data store 570. Scoring data may include known evaluation parameters including one or more of accuracy, sensitivity, specificity [Brunza; ¶7, 36-54, 67; Figs. 1-3, 5c and associated texts]).
Regarding claim 2, Brunza discloses the method according to the claim 1, wherein the context data comprises time-based considerations, historical data patterns, user activities, system criticality, impact on operations and/or holistic contextual assessments (Sensor state data: Sensor state data can include timestamp aligned data, and real-time state data associated with a system sensor or group of sensors. Sensor state data can be either reported by a sensor in a single information domain, or reported by a group of sensors in a single information domain, or reported by a group of sensors across multiple information domains, or derived data created by the situation awareness system 102. Sensor state prediction data: Sensor state prediction data can include trend data, including data derived by curve-fitting to past sensor states and by extrapolation to sensor states in the future, associated with a sensor or groups of sensors. Sensor state prediction data can be either reported by a sensor in a single information domain, or reported by a group of sensors in a single information domain, or reported by a group of sensors across multiple information domains, or derived data created by the monitored system, or derived data created by the situation awareness system 102 [Brunza; ¶36-54, 67; Figs. 1-3, 5c and associated texts]).
Regarding claim 3, Brunza discloses the method according to claim 1, wherein the context factor score indicates a relevance of the input data (the situation awareness system 102 may utilize a continuous-valued score between 0 and 1, where the value signifies the likelihood that the data represents an attack (0 signifying absolutely normal traffic, 1 signifying certain attack). To achieve this, the situation awareness system 102 may deploy regression trees which ingest real-time data and generate operator and watchstander alerts with varying degrees of severity. Regression trees have an advantage over some ML techniques in that they can provide a human-readable ruleset indicating how the output value was derived based on the inputs [Brunza; ¶36-54, 67; Figs. 1-3, 5c and associated texts]).
Regarding claim 4, Brunza discloses the method according to claim 1, wherein each of the at least one context factors is associated with a predetermined context factor weight; and wherein determining the context threat score is based on the at least one context factor weight and the at least one context factor score [Brunza; ¶7-8, 36-54, 67; Figs. 1-3, 5c and associated texts].
Regarding claim 5, Brunza discloses the method according to claim 3, further comprising determining, by a machine learning model, the at least one context factor weight and the at least one context factor score (Classifiers: Normal behaviors 334 may be scored to reflect the degree of anomaly 338 determined with a machine learning binary classifier 336 and threat behaviors 342 may be scored to reflect the likelihood of a threat 346 with a machine learning binary classifier 344. ML algorithms for the machine learning binary classifiers 336, 344 might include random forest or recursive neural network [Brunza; ¶7-8, 36-54, 67; Figs. 1-3, 5c and associated texts].
Regarding claim 6, Brunza discloses the method according to claim 5, wherein the machine learning model comprises a regression model, a classification model, a decision tree model and/or a random forest model (the situation awareness system 102 may utilize a continuous-valued score between 0 and 1, where the value signifies the likelihood that the data represents an attack (0 signifying absolutely normal traffic, 1 signifying certain attack). To achieve this, the situation awareness system 102 may deploy regression trees which ingest real-time data and generate operator and watchstander alerts with varying degrees of severity. Regression trees have an advantage over some ML techniques in that they can provide a human-readable ruleset indicating how the output value was derived based on the inputs [Brunza; ¶36-54, 67; Figs. 1-3, 5c and associated texts]).
Regarding claim 7, Brunza discloses the method according to claim 1, further comprising providing by an outputting unit the context threat score of the at least one section to a user (The outputs of the behavior classifiers 338, 346 (scores and labels) are processed to provide human-interpretable input to the system human-machine interface (HMI 352) [Brunza; ¶36-54, 67; Figs. 1-3, 5c and associated texts]).
Regarding claim 8, Brunza discloses the method according to claim 1, further comprising: receiving an anomaly detection signal by the processing unit from an anomaly detection unit, wherein the anomaly detection signal indicates an anomaly in the at least one section; and evaluating the detected anomaly based on the determined context threat score of the at least one section (In addition to signature processing, the situation awareness system 102 may pursue an anomaly-based detection process 334, 336, 338. The normal historical traffic are characterized with behaviors by processing the outputs of the binary classifier 336 with neural networks. In one embodiment, the neural networks are recurrent neural networks, which are adept at handling streaming data. In determining anomaly scores 338, incoming traffic may be compared with this streaming data using a distance metric; in 338, data traffic that varies from an established baseline may generate an anomaly score proportional to its difference from the baseline (i.e., wide variance from the baseline may produce a high anomaly score). An example distance metric is the difference between the average value of some network quantity like packet length for incoming and normal traffic [Brunza; ¶36-54, 56, 67; Figs. 1-3, 5c and associated texts]).
Regarding claim 10, Brunza discloses the method according to claim 1, wherein the method is performed in real-time (ingest real-time data [Brunza; ¶36-54, 56, 67; Figs. 1-3, 5c and associated texts]).
Regarding claim 11, Brunza discloses the method according to claim 1, wherein the at least one section relates to a special area of the industrial plant or a functional section of the industrial plant (the Joint Directors of Laboratories (JDL) model may be used as the fusion model. JDL supports the alignment, normalization, and timestamping of all ingested data on a consistent set of space-time coordinates. The JDL model may also be used to support data aggregation over time (e.g., of data packets into data windows) and development of state information (behavioral primitives) through extraction of features and behaviors from the fused data (ingest real-time data [Brunza; ¶35-54, 56, 67; Figs. 1-3, 5c and associated texts]).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brunza et al. (US 20220342988 A1; hereinafter Brunza) in view of Michan (US 20220163947 A1).
Regarding claim 9, Brunza does not explicitly discloses the method according to claim 8, wherein evaluating the detected anomaly comprises a false positive anomaly detection; however, in a related and analogous art, Michan teaches this feature.
In particular, Michan teaches true/false anomaly detection [Michan; ¶5, 12, 35]. It would have been obvious before the effective filing date of the claimed invention to modify Brunza in view of Michan with the motivation to prevent over-sensitivity of the threshold and oscillating/noisy industrial IoT data [Michan; ¶12].
Internet Communications
Applicant is encouraged to submit a written authorization for Internet communications (PTO/SB/439, http:ljwww.uspto.gov/sites/default/files/documents/sb0439.pdf) in the instant patent application to authorize the examiner to communicate with the applicant via email. The authorization will allow the examiner to better practice compact prosecution. The written authorization can be submitted via one of the following methods only: (1) Central Fax which can be found in the Conclusion section of this Office action; (2) regular postal mail; (3) EFS WEB; or (4) the service window on the Alexandria campus. EFS web is the recommended way to submit the form since this allows the form to be entered into the file wrapper within the same day (system dependent). Written authorization submitted via other methods, such as direct fax to the examiner or email, will not be accepted. See MPEP § 502.03.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAO Q HO whose telephone number is (571)270-5998. The examiner can normally be reached on 7:00am - 5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey Nickerson can be reached on (469) 295-9235. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DAO Q HO/Primary Examiner, Art Unit 2432
1 The MANUAL OF PATENT EXAMINING PROCEDURE (“MPEP”) incorporates the revised guidance and subsequent updates at § 2106 (9th ed. Rev. 10.2019, rev. June 2020).
Prosecution Insights