DETAILED ACTION
1. This is a Final Office Action Correspondence in response to arguments/amendments filed for U.S. Application No. 18/500664 on January 28, 2026.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
3. The Information Disclosure Statements filed on November 05, 2025 was reviewed and accepted by the Examiner.
Applicant
4. Applicant is encouraged to contact the Examiner in hopes of reaching a resolution in light of compact prosecution.
Response to Arguments
5. Applicant’s arguments have been considered but are not fully persuasive.
On Pg. 10 of remarks in regards to 35 U.S.C. 103, relating to claim 1, Applicant states “The Office Action cites McNair as teaching the interaction data object because "McNair discloses content that contains historical data, clinical data, lab results, test results, clinical trials, or behaviour patterns." Office Action, p. 4 (citing McNair, col. 25, 11. 15-15). The Office Action explains that the "test results are seen as assessment codes" and "clinical trials are seen as intervention codes." Office Action, p. 4. However, neither the test results nor the clinical trials are alpha-numerical codes. Therefore, neither teach or suggest an intervention alpha-numerical code or an assessment alpha-numerical code. None of the content cited by the Office Action is reflected in the form of alpha-numerical codes. While McNair may reference some codes, such as clinical concept codes, none of the referenced codes include an intervention alpha-numerical code and an assessment alpha-numerical code within a single interaction data object. McNair, therefore, fails to teach or suggest "receiving . . . a plurality of interaction data objects, wherein an interaction data object of the plurality of interaction data objects comprises a historical record of one or more of a plurality of assessment alpha-numerical codes and one or more of a plurality of alpha- numerical intervention codes" as recited by the independent claims.”
Examiner replies that McNair does teach this concept. In addition to the cited sections Col. 8 Lines 5-11 McNair discloses text are a part of the documents. Col. 8 Lines 10-15 McNair discloses time stamps are included within the document. Text is seen as containing both letters and numbers.
Claim Rejections - 35 USC § 103
7. 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.
8. 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.
9. Claim(s) 1-8, 10-19 and 20-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over McNair U.S. Patent No. 11,527,326 (herein as ‘McNair’) and further in view of Tomkins et al. U.S. Patent Application Publication No. 2021/0295822 (herein as ‘Tomkins’).
As to claim 1 McNair teaches a computer-implemented method, the computer-implemented method comprising:
receiving, by one or more processors, a plurality of interaction data objects wherein an interaction data object of the plurality of interaction data objects comprises a historical record of one or more of a plurality of assessment alpha-numerical codes and a plurality of intervention alpha-numerical codes (Col. 25 Lines 15-25 McNair discloses content that contains historical data, clinical data, lab results, test results, clinical trials, or behavior patterns. The test results are seen as the assessment alpha-numerical codes. The clinical trials are seen as intervention alpha-numerical codes. The data sources that contain content are seen as interaction data object);
McNair does not teach but Tomkins teaches generating, by the one or more processors, a frequency distribution comprising a plurality of code pairs based on a plurality of cooccurrences of the plurality of assessment alpha-numerical codes and the plurality of intervention alpha-numerical codes within the plurality of interaction data objects (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects);
generating, by the one or more processors and using the frequency distribution, a cross-code dataset comprising one or more mapped code pairs from the plurality of code pairs based on a threshold cooccurrence value, wherein one of the one or more mapped code pairs includes one of the plurality of intervention alpha-numerical codes mapped with one of the plurality of assessment alpha-numerical codes (Par. 0137 and Par. 0168 Tomkins discloses in response to request data vertices are generated and associated with actions. The vertices of text are seen as the assessment alpha-numerical codes. The performed actions are seen as the intervention alpha-numerical codes. Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic);
receiving, by the one or more processors, data indicative of an electronic search query provided by a user device to an electronic search engine (Col. 17 Lines 24-28 Tomkins discloses receiving a query from a patient of target conditions of interest);
McNair and Tomkins are analogous art because they are in the same field of endeavor, processing health care data. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the patient diagnosis of McNair to include the frequency distribution of Tomkins, to identify relevant sets of data or patient treatment (Par. 0003 Tomkins).
McNair teaches and performing, by the one or more processors and based on the cross-code dataset, a query resolution operation for the electronic search query the query resolution operation comprising: identifying an intermediate search resolution for the electronic search query based on a comparison between one or more query terms of the electronic search query and the cross-code dataset (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution);
wherein the intermediate search resolution comprises (i) a first intervention code, of the plurality of intervention alpha-numerical codes, that corresponds to a first assessment code, of the plurality of assessment alpha-numerical codes, associated with the one or more query terms or (ii) a second assessment code, of the plurality of assessment alpha-numerical codes, that corresponds to a second intervention code, of the plurality of intervention alpha-numerical codes, associated with the one or more query terms (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. Such solvers identify unprocessed patient information to input missing or delayed values by comparing patterns or sequences of clinical events to find similar patients with similar clinical conditions or similar clinical variables. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution. The similar clinical variables are seen as the assessment alpha-numerical code. The similar clinical conditions are seen as the intervention code)
and providing, to the electronic search engine, data indicative of the intermediate search resolution. ((Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. This information can be used for other solvers).
As to claim 2 McNair in combination with Tomkins teaches each and every limitation of claim 1.
In addition Tomkins teaches wherein the cross-code dataset comprises a plurality of mapped code pairs and each of the plurality of mapped code pairs comprises a respective assessment code of the plurality of assessment alpha-numerical codes and a respective intervention code of the plurality of intervention alpha-numerical codes (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects).
As to claim 3 McNair in combination with Tomkins teaches each and every limitation of claim 2.
In addition Tomkins teaches wherein a mapped code pair of the plurality of mapped code pairs comprises a textual description of the respective assessment code mapped to a textual description of the respective intervention code (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects).
As to claim 4 McNair in combination with Tomkins teaches each and every limitation of claim 1.
In addition Tomkins teaches wherein generating the cross-code dataset comprises: identifying a set of intervention alpha-numerical codes of the plurality of intervention alpha-numerical codes that correspond to each of the plurality of assessment alpha-numerical codes based on the frequency distribution, wherein a number of the one or more intervention alpha-numerical codes is based on the threshold cooccurrence value (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects. Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic).
As to claim 5 McNair in combination with Tomkins teaches each and every limitation of claim 1.
In addition Tomkins teaches wherein the one or more mapped code pairs comprise a respective mapped code pair for each assessment code of the plurality of assessment alpha-numerical codes (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents).
As to claim 6 McNair in combination with Tomkins teaches each and every limitation of claim 1.
In addition McNair teaches wherein the plurality of interaction data objects is associated with a time interval (Col. 8 Lines 9-15 McNair discloses that time is associated with the conditions).
As to claim 7 McNair in combination with Tomkins teaches each and every limitation of claim 6.
In addition Tomkins teaches wherein the time interval is based on a refresh rate that defines one or more of one or more historical refresh times or one or more future refresh times for the plurality of interaction data objects (Par. 0351 Tomkins discloses over time updating the associations between the concepts).
As to claim 8 McNair in combination with Tomkins teaches each and every limitation of claim 1.
In addition Tomkins teaches wherein the one or more assessment alpha-numerical codes of the interaction data object comprises a primary assessment code within a subset of the plurality of assessment alpha-numerical codes listed in the interaction data object and the one or more intervention alpha-numerical codes of the interaction data object comprises a primary intervention code within a subset of the plurality of intervention alpha-numerical codes listed in the interaction data object (Par. 0142 Tomkins discloses prioritizing terms or words to identify results that are of higher relevance).
As to claim 10 McNair teaches a system comprising memory and one or more processors communicatively coupled to the memory, the one or more processors configured to:
receive a plurality of interaction data objects wherein an interaction data object of the plurality of interaction data objects comprises a historical record of one or more of a plurality of assessment alpha-numerical codes and one or more of a plurality of intervention alpha-numerical codes (Col. 25 Lines 15-25 McNair discloses content that contains historical data, clinical data, lab results, test results, clinical trials, or behavior patterns. The test results are seen as the assessment alpha-numerical codes. The clinical trials are seen as intervention alpha-numerical codes. The data sources that contain content are seen as interaction data object);
McNair does not teach but Tomkins teaches generate a frequency distribution comprising a plurality of code pairs based on a plurality of cooccurrences of the plurality of assessment alpha-numerical codes and the plurality of intervention alpha-numerical codes within the plurality of interaction data objects (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects);
generate, using the frequency distribution, a cross-code dataset comprising one or more mapped code pairs from the plurality of code pairs based on a threshold cooccurrence value (Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic);
wherein one of the one or more mapped code pairs includes one of the plurality of intervention alpha-numerical codes mapped with one of the plurality of assessment alpha-numerical codes (Par. 0137 and Par. 0168 Tomkins discloses in response to request data vertices are generated and associated with actions. The vertices of text are seen as the assessment alpha-numerical codes. The performed actions are seen as the intervention alpha-numerical codes. Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic);
receive data indicative of an electronic search query provided by a user device to an electronic search engine (Col. 17 Lines 24-28 Tomkins discloses receiving a query from a patient of target conditions of interest);
McNair and Tomkins are analogous art because they are in the same field of endeavor, processing health care data. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the patient diagnosis of McNair to include the frequency distribution of Tomkins, to identify relevant sets of data or patient treatment (Par. 0003 Tomkins).
McNair teaches and perform, based on the cross-code dataset a query resolution operation for the electronic search query, the query resolution operation comprising: identifying an intermedia search resolution for the electronic search query based on a comparison between one or more query terms of the electronic search query and the cross-code dataset; wherein the intermediate search resolution comprises (i) a first intervention code, of the plurality of intervention alpha-numerical codes, that corresponds to a first assessment code, of the plurality of assessment alpha-numerical codes, associated with the one or more query terms or (ii) a second assessment code, of the plurality of assessment alpha-numerical codes, that corresponds to a second intervention code, of the plurality of intervention alpha-numerical codes, associated with the one or more query terms (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. Such solvers identify unprocessed patient information to input missing or delayed values by comparing patterns or sequences of clinical events to find similar patients with similar clinical conditions or similar clinical variables. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution. The similar clinical variables are seen as the assessment code. The similar clinical conditions are seen as the intervention code);
and providing, to the electronic search engine, data indicative of the intermediate search resolution (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. This information can be used for other solvers).
As to claim 11 McNair in combination with Tomkins teaches each and every limitation of claim 10.
In addition Tomkins teaches wherein the cross-code dataset comprises a plurality of mapped code pairs and each of the plurality of mapped code pairs comprises a respective assessment code of the plurality of assessment alpha-numerical codes and a respective intervention code of the plurality of intervention alpha-numerical codes (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects).
As to claim 12 McNair in combination with Tomkins teaches each and every limitation of claim 11.
In addition Tomkins teaches wherein a mapped code pair comprises a first textual description of the respective assessment code mapped to a second textual description of the respective intervention code (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects).
As to claim 13 McNair in combination with Tomkins teaches each and every limitation of claim 10.
In addition Tomkins teaches wherein the one or more processors are further configured to: identify a set of intervention alpha-numerical codes of the plurality of intervention alpha-numerical codes that correspond to each of the plurality of assessment alpha-numerical codes based on the frequency distribution, wherein a number of the set of intervention alpha-numerical codes is based on the threshold cooccurrence value (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects. Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic).
As to claim 14 McNair in combination with Tomkins teaches each and every limitation of claim 10.
In addition Tomkins teaches wherein the one or more mapped code pairs comprise a respective mapped code pair for each assessment code of the plurality of assessment alpha-numerical codes (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents).
As to claim 15 McNair in combination with Tomkins teaches each and every limitation of claim 10.
In addition McNair teaches wherein the plurality of interaction data objects is associated with a time interval (Col. 8 Lines 9-15 McNair discloses that time is associated with the conditions).
As to claim 16 McNair in combination with Tomkins teaches each and every limitation of claim 15.
In addition Tomkins teaches wherein the time interval is based on a refresh rate that defines one or more of one or more historical refresh times or one or more future refresh times for the plurality of interaction data objects (Par. 0351 Tomkins discloses over time updating the associations between the concepts).
As to claim 17 McNair in combination with Tomkins teaches each and every limitation of claim 10.
In addition Tomkins teaches wherein the plurality of assessment alpha-numerical codes and the plurality of intervention alpha-numerical codes are based on one or more primary assessment alpha-numerical codes and one or more primary intervention alpha-numerical codes identified within each of the plurality of interaction data objects (Par. 0142 Tomkins discloses prioritizing terms or words to identify results that are of higher relevance).
As to claim 18 McNair teaches one or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, cause the one or more processors to:
receive a plurality of interaction data wherein an interaction data object of the plurality of interaction data objects comprises a historical record of one or more of a plurality of assessment alpha-numerical codes and one or more of a plurality of intervention alpha-numerical codes (Col. 3 Lines 13-17 McNair discloses the structure topic modeling (STM), which contains diagnostics and therapeutic plans for patient care. The diagnostic are seen as the assessment alpha-numerical codes. The therapeutic plans are seen as intervention alpha-numerical codes. The STM are seen as interaction data object. Fig. 2 and Col. 17 lines 35-55 McNair discloses receiving the STM models);
McNair does not teach but Tomkins teaches generate a frequency distribution comprising a plurality of code pairs based on a plurality of cooccurrences of the plurality of assessment alpha-numerical codes and the plurality of intervention alpha-numerical codes within the plurality of interaction data objects (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects);
generate, using the frequency distribution, a cross-code dataset comprising one or more mapped code pairs from the plurality of code pairs based on a threshold cooccurrence value , wherein one of the one or more mapped code pairs includes one of the plurality of intervention alpha-numerical codes mapped with one of the plurality of assessment alpha-numerical codes (Par. 0137 and Par. 0168 Tomkins discloses in response to request data vertices are generated and associated with actions. The vertices of text are seen as the assessment alpha-numerical codes. The performed actions are seen as the intervention alpha-numerical codes. Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic);
receive data indicative of an electronic search query provided by a user device to an electronic search engine; and perform, based on the cross-code dataset (Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic);
McNair and Tomkins are analogous art because they are in the same field of endeavor, processing health care data. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the patient diagnosis of McNair to include the frequency distribution of Tomkins, to identify relevant sets of data or patient treatment (Par. 0003 Tomkins).
McNair teaches and a query resolution operation for the electronic search query, the query resolution operation comprising: (Col. 17 Lines 63-69 McNair discloses providing the patient with conditions to help the patient prevail over the diagnosis);
identifying an intermediate a search resolution for the electronic search query based on a comparison between one or more query terms of the electronic search query and the cross-code dataset (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution);
wherein the intermediate search resolution comprises (i) a first intervention code, of the plurality of intervention alpha-numerical codes, that corresponds to a first assessment code, of the plurality of assessment alpha-numerical codes, associated with the one or more query terms or (ii) a second assessment code, of the plurality of assessment alpha-numerical codes, that corresponds to a second intervention code, of the plurality of intervention alpha-numerical codes, associated with the one or more query terms (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. Such solvers identify unprocessed patient information to input missing or delayed values by comparing patterns or sequences of clinical events to find similar patients with similar clinical conditions or similar clinical variables. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution. The similar clinical variables are seen as the assessment code. The similar clinical conditions are seen as the intervention code);
and providing, to the electronic search engine, data indicative of the search resolution (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. This information can be used for other solvers).
As to claim 19 McNair in combination with Tomkins teaches each and every limitation of claim 18.
In addition Tomkins teaches wherein the one or more processors are further caused to: identify a set of intervention alpha-numerical codes of the plurality of intervention alpha-numerical codes that correspond to each of the plurality of assessment alpha-numerical codes based on the frequency distribution, wherein a number of the set of intervention alpha-numerical codes is based on the threshold cooccurrence value (Par. 0205 Tomkins discloses generating a distribution based upon the sets of words appearing in the documents. The sets of words are seen as assessment alpha-numerical codes and interaction codes. The documents that contain the sets of words are seen as interaction data objects. Par. 0205 Tomkins discloses generating a neural network based upon the frequency distribution by using the sets of text that satisfy a relevance threshold associated with a query topic).
As to claim 21 McNair in combination with Tomkins teaches each and every limitation of claim 8.
In addition McNair teaches wherein the primary assessment code comprises a first listed assessment code within the subset of the plurality of assessment alpha-numerical codes listed in the interaction data object and the primary intervention code comprises a first listed intervention code within the subset of the plurality of intervention alpha-numerical codes listed in the interaction data object (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. Such solvers identify unprocessed patient information to input missing or delayed values by comparing patterns or sequences of clinical events to find similar patients with similar clinical conditions or similar clinical variables. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution. The similar clinical variables are seen as the assessment code. The similar clinical conditions are seen as the intervention code).
As to claim 22 McNair in combination with Tomkins teaches each and every limitation of claim 1.
In addition McNair teaches wherein the query resolution operation further comprises: identifying a search resolution for the electronic search query based on a comparison between the intermediate search resolution and the plurality of interaction data objects (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. Col 18 Lines 6-16 and Col. 19 Lines 10-20 McNair discloses using conditions detection to identify new or improved solvers to address the needs of the data. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution);
and the data indicative of the intermediate search resolution comprises data indicative of the search resolution (Col. 17 Lines 5-26 McNair discloses solver library’s which are used to determine one or more conditions or recommended treatments for a patient. Such solvers identify unprocessed patient information to input missing or delayed values by comparing patterns or sequences of clinical events to find similar patients with similar clinical conditions or similar clinical variables. The determine one or more conditions or recommended treatments for a patient is seen as the intermediate search resolution).
As to claim 23 McNair in combination with Tomkins teaches each and every limitation of claim 1.
In addition McNair teaches wherein the plurality of assessment alpha-numerical codes comprises one or more clinical diagnosis codes, and the plurality of intervention alpha-numerical codes comprises one or more clinical procedural codes (Col. 3 Lines 13-17 McNair discloses the structure topic modeling (STM), which contains diagnostics and therapeutic plans for patient care. The diagnostic are seen as the assessment alpha-numerical codes. The therapeutic plans are seen as intervention alpha-numerical codes with clinical procedure).
Conclusion
10. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JERMAINE A MINCEY whose telephone number is (571)270-5010. The examiner can normally be reached 8am EST until 5pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ann J Lo can be reached on (571) 272-9767. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.A.M/ February 12, 2026
Examiner, Art Unit 2159
/ANN J LO/ Supervisory Patent Examiner, Art Unit 2159