Prosecution Insights
Last updated: April 19, 2026
Application No. 19/200,871

USER INTERFACE DATA SAMPLE TRANSFORMER

Non-Final OA §102§103§DP
Filed
May 07, 2025
Examiner
OBERLY, VAN HONG
Art Unit
2166
Tech Center
2100 — Computer Architecture & Software
Assignee
Palantir Technologies Inc.
OA Round
1 (Non-Final)
75%
Grant Probability
Favorable
1-2
OA Rounds
3y 2m
To Grant
90%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allow Rate
456 granted / 608 resolved
+20.0% vs TC avg
Strong +16% interview lift
Without
With
+15.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
11 currently pending
Career history
619
Total Applications
across all art units

Statute-Specific Performance

§101
7.9%
-32.1% vs TC avg
§103
58.6%
+18.6% vs TC avg
§102
21.9%
-18.1% vs TC avg
§112
3.7%
-36.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 608 resolved cases

Office Action

§102 §103 §DP
DETAILED ACTION The Action is responsive to Applicant’s Application filed July 9, 2025. Please note claims 21-40 are pending. Priority Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged. Drawings The drawings, filed May 5, 2024 are considered in compliance with 37 CFR 1.81 and accepted. 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 . Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 21-22, 24-25, 27-34, 36, 38-40 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-5, 7-8, 10-11, 13, 19 of U.S. Patent No. 12,332,909. Although the claims at issue are not identical, they are not patentably distinct from each other because: Instant Application 19/200,871 US Patent No. 12,332,909 21. A method comprising: selecting a subset of an input dataset; executing a set of data transformations on the subset of the input dataset to generate a transformed subset using a first executable code; updating a set of data transformations based on an input associated with the transformed subset; generating a second executable code corresponding to the updated set of data transformations based on the first executable code, wherein the second executable code is different from the first executable code; and converting the input dataset to a validated format by applying the second executable code corresponding to the updated set of data transformations to the input dataset; wherein the method is performed using one or more processors. 1. A method comprising: receiving an indication of an input dataset; selecting a subset of the input dataset based on a first input; executing a set of data transformations on the subset of the input dataset to generate a transformed subset; causing presentation of an indication of the transformed subset via a software application on a user interface; receiving a second input associated with the transformed subset from the user interface; updating the set of data transformations based on the second input associated with the transformed subset; generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code; and converting the input dataset to a validated format by applying the database-executable code corresponding to the updated set of data transformations to the input dataset; wherein the method is performed using one or more processors. 22. The method of claim 21, wherein the first executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code. 1.…generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code 24. The method of claim 21, wherein the second executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code. 1.…generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code 25. The method of claim 24, wherein the database-executable code includes a functional programming code. 1.…generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code 27. The method of claim 21, wherein the validated format is a data format that can be parsed by a data visualization application. 2. The method of claim 1, wherein the validated format is a data format that can be parsed by a data visualization application. 28. The method of claim 27, wherein the input dataset is in a non-validated format that cannot be parsed by the data visualization application. 3. The method of claim 2, wherein the input dataset is in a non-validated format that cannot be parsed by the data visualization application. 29.The method of claim 21, wherein the executing a set of data transformations includes executing the set of data transformations on the subset of the input dataset yielding one or more errors; wherein the updating the set of data transformation includes further updating the set of data transformations based on the one or more errors. 4. The method of claim 1, wherein the executing a set of data transformations includes executing the set of data transformations on the subset of the input dataset yielding one or more errors; wherein the updating the set of data transformation includes further updating the set of data transformations based on the one or more errors. 30. The method of claim 29, wherein the updating the set of data transformations based on the one or more errors includes: generating one or more second data transformations based on the one or more errors; and updating the set of data transformations by adding the one or more second data transformations. 5. The method of claim 4, wherein the updating the set of data transformations based on the one or more errors includes: generating one or more second data transformations based on the one or more errors; and updating the set of data transformations by adding the one or more second data transformations. 31. The method of claim 21, further comprising: receiving a filter associated with the validated format; wherein the converting the input dataset to a validated format includes: generating a first filtered dataset extracted from the input dataset based on the filter; and applying the updated set of data transformations to the first filtered dataset. 7. The method of claim 1, further comprising: receiving a filter associated with the validated format; wherein the converting the input dataset to a validated format includes: generating a first filtered dataset extracted from the input dataset based on the filter; and applying the updated set of data transformations to the first filtered dataset. 32. The method of claim 31, wherein the input dataset is a first input dataset; wherein the method further comprises: receiving an indication of a second input dataset; generating a second filtered dataset extracted from the second input dataset based on the filter; and applying the updated set of data transformations to the second filtered dataset. 8. The method of claim 7, wherein the input dataset is a first input dataset; wherein the method further comprises: receiving an indication of a second input dataset; generating a second filtered dataset extracted from the second input dataset based on the filter; and applying the updated set of data transformations to the second filtered dataset. 33. A system comprising: one or more memories comprising instructions stored thereon; and one or more processors configured to execute the instructions and perform a set of operations comprising: selecting a subset of an input dataset; executing a set of data transformations on the subset of the input dataset to generate a transformed subset using a first executable code; updating a set of data transformations based on an input associated with the transformed subset; generating a second executable code corresponding to the updated set of data transformations based on the first executable code, wherein the second executable code is different from the first executable code; and converting the input dataset to a validated format by applying the second executable code corresponding to the updated set of data transformations to the input dataset. 10. A system comprising: one or more memories comprising instructions stored thereon; and one or more processors configured to execute the instructions and perform operations comprising: receiving an indication of an input dataset; selecting a subset of the input dataset based on a first input; executing a set of data transformations on the subset of the input dataset to generate a transformed subset; causing presentation of an indication of the transformed subset via a software application on a user interface; receiving a second input associated with the transformed subset from the user interface; updating the set of data transformations based on the second input associated with the transformed subset; generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code; and converting the input dataset to a validated format by applying the database- executable code corresponding to the updated set of data transformations to the input dataset 34. The system of claim 33, wherein the first executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code. 10… generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code 36. The system of claim 33, wherein the second executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code. 10 …generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code 38. The system of claim 33, wherein the validated format is a data format that can be parsed by a data visualization application. 11. The system of claim 10, wherein the validated format is a data format that can be parsed by a data visualization application. 39. The system of claim 33, wherein the executing a set of data transformations includes executing the set of data transformations on the subset of the input dataset yielding one or more errors; wherein the updating the set of data transformation includes further updating the set of data transformations based on the one or more errors. 13. The system of claim 10, wherein the executing a set of data transformations includes executing the set of data transformations on the subset of the input dataset yielding one or more errors; wherein the updating the set of data transformation includes further updating the set of data transformations based on the one or more errors. 40. A non-transitory computer-readable storage medium having instructions that, when executed by one or more processors, cause the one or more processors to perform a set of operations comprising: selecting a subset of an input dataset; executing a set of data transformations on the subset of the input dataset to generate a transformed subset using a first executable code; updating a set of data transformations based on an input associated with the transformed subset; generating a second executable code corresponding to the updated set of data transformations based on the first executable code, wherein the second executable code is different from the first executable code; and converting the input dataset to a validated format by applying the second executable code corresponding to the updated set of data transformations to the input dataset. 19. A method comprising: receiving an indication of an input dataset; selecting a subset of the input dataset based on a first input; executing a set of data transformations on the subset of the input dataset to generate a transformed subset; causing presentation of an indication of the transformed subset via a software application on a user interface; receiving a second input associated with the transformed subset from the user interface; updating the set of data transformations based on the second input associated with the transformed subset; generating database-executable code corresponding to the updated set of data transformations based on an application-executable code associated with the software application, wherein the application-executable code is in a code language applied to the subset of the input dataset, wherein the application-executable code is different from the database-executable code; and converting the input dataset to a validated format by applying the database-executable code corresponding to the updated set of data transformations to the input dataset, the validated format being a data format that can be parsed by a data visualization application; wherein the method is using one or more processors; wherein the executing a set of data transformations includes executing the set of data transformations on the subset of the input dataset yielding one or more errors; wherein the updating the set of data transformation includes further updating the set of data transformations based on the one or more errors. 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) 21-22, 24, 29-30, 33-34, 36, 39-40 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hiatt et al. (US Pub. No. 2015/0019476) Regarding claim 21, Hiatt teaches a method comprising: ‘selecting a subset of an input dataset’ as an input adapter to pull a set of data from a legacy system into a database (¶0031-32) ‘executing a set of data transformations on the subset of the input dataset to generate a transformed subset using a first executable code’ as conversion components to transform the data (¶0033-42) ‘updating a set of data transformations based on an input associated with the transformed subset’ (¶0033-42) ‘generating a second executable code corresponding to the updated set of data transformations based on the first executable code, wherein the second executable code is different from the first executable code’ as consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (¶0065-72) ‘converting the input dataset to a validated format by applying the second executable code corresponding to the updated set of data transformations to the input dataset’ as applying the changes from the reconciliation component (¶0065-72) ‘wherein the method is performed using one or more processors’ (¶0029) Regarding claim 22, Hiatt fails teaches ‘wherein the first executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code’ as instructions to be executed via application programming interfaces, databases functions, etc. (¶0043-44) Regarding claim 24, Hiatt teaches ‘wherein the second executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code’ as instructions to be executed via application programming interfaces, databases functions, etc. (¶0043-44) Regarding claim 29, Hiatt teaches: ‘wherein the executing a set of data transformations includes executing the set of data transformations on the subset of the input dataset yielding one or more errors’ as conversion components to transform the data (Hiatt ¶0033-42) and collecting errors (Hiatt ¶0066) and consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (Hiatt ¶0065-72) ‘wherein the updating the set of data transformation includes further updating the set of data transformations based on the one or more errors’ as consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (Hiatt ¶0065-72) Regarding claim 30, Hiatt teaches wherein the updating the set of data transformations based on the one or more errors includes: ‘generating one or more second data transformations based on the one or more errors; and updating the set of data transformations by adding the one or more second data transformations’ as consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format based on errors (¶0065-72) Regarding claim 33, Hiatt teaches a system comprising: ‘one or more memories comprising instructions stored thereon’ (¶0029) ‘one or more processors configured to execute the instructions and perform a set of operations (¶0029) comprising: selecting a subset of an input dataset’ as an input adapter to pull a set of data from a legacy system into a database (¶0031-32) ‘executing a set of data transformations on the subset of the input dataset to generate a transformed subset using a first executable code’ as conversion components to transform the data (¶0033-42) ‘updating a set of data transformations based on an input associated with the transformed subset’ (¶0033-42) ‘generating a second executable code corresponding to the updated set of data transformations based on the first executable code, wherein the second executable code is different from the first executable code’ as consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (¶0065-72) ‘converting the input dataset to a validated format by applying the second executable code corresponding to the updated set of data transformations to the input dataset’ as consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (¶0065-72) Regarding claim 34, Hiatt teaches ‘wherein the first executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code’ as instructions to be executed via application programming interfaces, databases functions, etc. (¶0043-44) . Regarding claim 36, Hiatt teaches ‘wherein the second executable code includes at least one selected from a group consisting of an application-executable code, a browser-executable code, and a database-executable code’ as instructions to be executed via application programming interfaces, databases functions, etc. (¶0043-44) Regarding claim 39, Hiatt teaches: ‘wherein the executing a set of data transformations includes executing the set of data transformations on the subset of the input dataset yielding one or more errors’ as conversion components to transform the data (Hiatt ¶0033-42) and collecting errors (Hiatt ¶0066) and consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (Hiatt ¶0065-72) ‘wherein the updating the set of data transformation includes further updating the set of data transformations based on the one or more errors’ as consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (Hiatt ¶0065-72) Regarding claim 40, Hiatt teaches a non-transitory computer-readable storage medium having instructions that, when executed by one or more processors, cause the one or more processors to perform a set of operations comprising: ‘selecting a subset of an input dataset’ as an input adapter to pull a set of data from a legacy system into a database (¶0031-32) ‘executing a set of data transformations on the subset of the input dataset to generate a transformed subset using a first executable code’ as conversion components to transform the data (¶0033-42) ‘updating a set of data transformations based on an input associated with the transformed subset’ (¶0033-42) ‘generating a second executable code corresponding to the updated set of data transformations based on the first executable code, wherein the second executable code is different from the first executable code’ as consulting with a reconciliation component with a reconciliation table to identify further operations to further transform the data into the target format (¶0065-72) ‘converting the input dataset to a validated format by applying the second executable code corresponding to the updated set of data transformations to the input dataset’ as applying the changes from the reconciliation component (¶0065-72) 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. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claim(s) 23, 25-26, 35, 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hiatt et al. (US Pub. No. 2015/0019476) further in view of Sundaresan (US Pat. No. 6,487,566) Regarding claim 23, Hiatt fails to explicitly teach ‘wherein the browser-executable code includes a programming script.’ Sundaresan teaches ‘wherein the browser-executable code includes a programming script’ as a web-browser including scripts (Col. 5, Lines 37-40) It would have been obvious to one of ordinary skill in the art at the time that the present invention was effectively filed to modify the teachings of the cited references because Sundaresan’s would have allowed Hiatt’s to improve the transformation of structured data (Col. 3, Lines 44-49) Regarding claim 25, Sundaresan teaches ‘wherein the database-executable code includes a functional programming code’ as programming code (Col. 10, Lines 55-56) Regarding claim 26, Sundaresan teaches ‘wherein the database-executable code is configured to be executed across a distributed data storage system’ as a distributed computer system (Col. 5, Lines 25-28) Regarding claim 35, Sundaresan teaches ‘wherein the browser-executable code includes a programming script’ as a web-browser including scripts (Col. 5, Lines 37-40) Regarding claim 37, Sundaresan teaches ‘wherein the database-executable code is configured to be executed across a distributed data storage system’ as a distributed computer system (Col. 5, Lines 25-28) Claim(s) 27-28, 38 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hiatt et al. (US Pub. No. 2015/0019476) further in view of Callahan (US Pub. No. 2014/0129556) Regarding claim 27, Hiatt fails to explicitly teach ‘wherein the validated format is a data format that can be parsed by a data visualization application’ Callahan teaches ‘wherein the validated format is a data format that can be parsed by a data visualization application’ (¶0066) It would have been obvious to one of ordinary skill in the art at the time that the present invention was effectively filed to modify the teachings of the cited references because Callahan’s would have allowed Hiatt’s to maintain records in various formats (¶0003) Regarding claim 28, Callahan teaches ‘wherein the input dataset is in a non-validated format that cannot be parsed by the data visualization application’ (¶0142) Regarding claim 38, Hiatt fails to explicitly teach ‘wherein the validated format is a data format that can be parsed by a data visualization application’ Callahan teaches ‘wherein the validated format is a data format that can be parsed by a data visualization application’ (¶0066) It would have been obvious to one of ordinary skill in the art at the time that the present invention was effectively filed to modify the teachings of the cited references because Callahan’s would have allowed Hiatt’s to maintain records in various formats (¶0003). Claim(s) 31-32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hiatt et al. (US Pub. No. 2015/0019476) further in view of Figura et al. (US Pub. No. 2013/0182700) Regarding claim 31, Hiatt fails to explicitly teach ‘further comprising: receiving a filter associated with the validated form; wherein the converting the input dataset to a validated format includes: generating a first filtered dataset extracted from the input dataset based on the filter; and applying the updated set of data transformations to the first filtered dataset’ Figura teaches ‘further comprising: receiving a filter associated with the validated form; wherein the converting the input dataset to a validated format includes: generating a first filtered dataset extracted from the input dataset based on the filter; and applying the updated set of data transformations to the first filtered dataset’ as data filtering allowing a specified subset of incoming data to be processed, and transforming data from different sources to a standardized format (¶0141) It would have been obvious to one of ordinary skill in the art at the time that the present invention was effectively filed to modify the teachings of the cited references because Figura’s would have allowed Hiatt’s to provide flexibility among various data formats (¶0004) Regarding claim 32, Figura teaches ‘wherein the input dataset is a first input dataset; wherein the method further comprises: receiving an indication of second input dataset; generating a second filtered dataset extracted from the second input dataset based on the filter; and applying the updated set of data transformations to the second filtered dataset’ as the process repeating and data filtering allowing a specified subset of incoming data to be processed, and transforming data from different sources to a standardized format (¶0109) Examiner’s Note Examiner has cited particular columns/paragraphs and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. In the case of amending the claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. This will assist in expediting compact prosecution. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121(b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.131(b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as “Applicants believe no new matter has been introduced” may be deemed insufficient. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to VAN OBERLY whose telephone number is (571)272-7025. The examiner can normally be reached Monday - Friday, 7:30am-4pm MT. 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, Sanjiv Shah can be reached at (571) 272-4098. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /VAN H OBERLY/Primary Examiner, Art Unit 2166
Read full office action

Prosecution Timeline

May 07, 2025
Application Filed
Mar 06, 2026
Non-Final Rejection — §102, §103, §DP (current)

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Prosecution Projections

1-2
Expected OA Rounds
75%
Grant Probability
90%
With Interview (+15.5%)
3y 2m
Median Time to Grant
Low
PTA Risk
Based on 608 resolved cases by this examiner. Grant probability derived from career allow rate.

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