Prosecution Insights
Last updated: July 17, 2026
Application No. 18/017,123

METHOD FOR GENERATING TRAINED MODEL, METHOD FOR DETERMINING BASE SEQUENCE OF BIOMOLECULE, AND BIOMOLECULE MEASUREMENT DEVICE

Non-Final OA §101§103§112
Filed
Jan 20, 2023
Priority
Jul 31, 2020 — nonprovisional of PCTJP2020029565
Examiner
HILL, GRACELYN MARKHAM
Art Unit
Tech Center
Assignee
Hitachi Ltd.
OA Round
1 (Non-Final)
100%
Grant Probability
Favorable
1-2
OA Rounds
1y 5m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 100% — above average
100%
Career Allowance Rate
1 granted / 1 resolved
+40.0% vs TC avg
Minimal +0% lift
Without
With
+0.0%
Interview Lift
resolved cases with interview
Typical timeline
4y 11m
Avg Prosecution
22 currently pending
Career history
16
Total Applications
across all art units

Statute-Specific Performance

§101
6.4%
-33.6% vs TC avg
§103
80.9%
+40.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1 resolved cases

Office Action

§101 §103 §112
DETAILED ACTION Claim Status Claims 1-14 are rejected. 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 . Priority This application claims Domestic Benefit to application # PCT/JP2020/029565, filed 07/31/2020. Domestic Benefit is acknowledged. Therefore, the effective filing date of claim(s) is 07/31/2020. This application is a 371 of the PCT application listed above. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Information Disclosure Statement The Information Disclosure Statement(s) filed on 01/20/2023 are in compliance with the provisions of 37 CFR 1.97 and have been considered in full. A signed copy of list of references cited from each IDS is included with this Office Action. Drawings The drawings filed on 01/20/2023 are accepted. Claim Interpretation The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “an extraction device” “a base caller” “accuracy acquisition device” “teacher data generation device” All of which are in claim 8. The following was found in the specification to describe these devices: Paragraph [0080] mentions the extraction device and that it is being performed by a computer Paragraph [0080] mentions the method for identifying the plurality of blocking events can be designed by a person skilled in the art and they could use a known technique Paragraph [0095] mentions the accuracy acquisition device and that it is being performed by a computer Paragraph [0039] mentions the teacher data generation device and that it is being performed by a computer This disclosure does not provide sufficient structure because it is merely a bare statement that known techniques can be used (see MPEP 2181.II.A). They are being interpreted as separate “stations” where the equivalent method step would be performed, either by computer or human means. Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Claim Rejections - 35 USC § 112 The following is a quotation of the first paragraph of 35 U.S.C. 112(a): (a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention. The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112: The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention. Claims 8-14 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claims contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claim 8 recites limitations for “devices” and a “base caller” that has been interpreted to invoke 35 U.S.C. 112(f)/35 U.S.C. 112, sixth paragraph. However, as discussed in the Claim Interpretation section above, the instant specification does not describe the algorithms associated with the “devices”. MPEP § 2181.IV sets forth that mere restatement of function in the specification without description of the means to accomplish the function fails to provide adequate written description under 35 U.S.C. 112(a). Therefore, the “devices” do not meet the written description requirement for means-plus-function limitations. Claims 9-14 inherit this issue without resolving it and are thus additionally rejected. The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1-14 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The terms “good data” and “bad data” in claims 1 and 8 are relative terms which renders the claim indefinite. The terms “good” and “bad” are not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The concepts of good and bad are too nebulous, without being further defined, for the metes and bounds of the claims to be clearly identified. Claims 2-7 and 9-14 inherit the issues of claims 1 and 8 without resolving them, and are thus also rejected. Claim limitations for “devices” and a “base caller” in claim 8 invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Claims 9-14 inherit this issue without resolving it and are thus also rejected. Applicant may: (a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph; (b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or (c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)). If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either: (a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or (b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea/law of nature/natural phenomenon without significantly more. In accordance with MPEP § 2106, claims found to recite statutory subject matter ( Step 1 : YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea/law of nature/natural phenomenon: 1. generating a first trained model by executing machine learning of a training model using first teacher data, 1. the first trained model is configured to classify the blocking event data into good data or bad data. 2. classifying the blocking event data into good data or bad data by the first trained model; 2. determining a base sequence of a biomolecule based on the blocking event data classified as good data. 5. the second trained model is generated by executing machine learning of a training model using second teacher data, 5. the base sequence is determined based on the blocking event data by using a second trained model 6. acquiring accuracy for the determined base sequence 6. generating the teacher blocking event data related to the good data based on the blocking event data related to the base sequence if the accuracy satisfies a predetermined criterion. 8. the first trained model according to claim 1 that classifies the blocking event data into good data or bad data; 8. base caller that determines a base sequence of a biomolecule based on the blocking event data classified as the good data 12. the second trained model is generated by executing machine learning of a training model using second teacher data 13. an accuracy acquisition device that acquires accuracy for the determined base sequence 13. a teacher data generation device that generates the teacher blocking event data related to the good data based on the blocking event data related to the base sequence if the accuracy satisfies a predetermined criterion. The limitations for “generating,” “classifying,” “determining,” and “acquiring” are all steps that can be practically performed by a human being with access to a pen and paper. A human being can compute a simple machine learning model, such as a decision tree, classify data as good or bad, determine a sequence based on data, and compute accuracy. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. As such, claims 1-14 recite an abstract idea ( Step 2A, Prong 1 : YES). Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). This judicial exception is not integrated into a practical application because the claims do not recite an additional element that reflects an improvement to technology or applies or uses the recited judicial exception to effect a particular treatment for a condition. Rather, the instant claims recite additional elements that amount to mere instructions to implement the abstract idea in a generic computing environment or mere instructions to apply the recited judicial exception via a generic treatment. Specifically, the claims recite the following additional elements: 1. A method for generating a trained model for classifying blocking event data representing a nanopore blocking event in a biomolecule measurement device 1. the first teacher data includes teacher blocking event data and a teacher label, and the teacher label indicates whether the teacher blocking event data is classified as good data or bad data, 2. A method for determining a base sequence of a biomolecule, the method comprising: inputting blocking event data representing a blocking event of a nanopore in a biomolecule measurement device to a first trained model generated using the method according to claim 1; 3. The method according to claim 1, wherein the blocking event data and the teacher blocking event data are data representing a feature of the blocking event. 4. The method according to claim 2, wherein the blocking event data and the teacher blocking event data represent respective current values, and the current values can take respective ones of a plurality of discretized values, and each of the plurality of discretized values corresponds to one of the bases of the biomolecule. 5. the second teacher data includes teacher blocking event data and a teacher base sequence. 7. The method according to claim 1, wherein the training model includes a neural network. 8. A biomolecule measurement device comprising: a first liquid tank; a second liquid tank; a thin film on which nanopores are formed, the thin film being disposed between the first liquid tank and the second liquid tank; a first electrode provided in the first liquid tank; a second electrode provided in the second liquid tank; an ammeter that measures a current value flowing between the first electrode and the second electrode; an extraction device that extracts blocking event data based on the current value measured by the ammeter; a storage device that stores the blocking event data; 9. The biomolecule measurement device according to claim 8, wherein the thin film is formed of a solid material, and the nanopore is a pore penetrating the solid material. 10. The biomolecule measurement device according to claim 8, wherein the blocking event data and the teacher blocking event data are data representing a feature of the blocking event. 11. The biomolecule measurement device according to claim 8, wherein the current value can take one of a plurality of discretized values, and each of the plurality of discretized values corresponds to one of the bases of the biomolecule. 12. the base caller includes a second trained model 12. the second teacher data includes teacher blocking event data and a teacher base sequence. 14. The biomolecule measurement device according to claim 8, wherein the training model includes a neural network. All of these limitations simply further limit the data types and machines to be used in the method or system. Only the limitations for claim 2 about inputting blocking event data recites an active step. This step is considered “mere data gathering”, similar to presenting offers to potential customers and gathering statistics generated based on the testing about how potential customers responded to the offers; the statistics are then used to calculate an optimized price, OIP Technologies, 788 F.3d at 1363, 115 USPQ2d at 1092-93. There are no limitations that indicate that the claimed “neural network” of claims 7 and 14 or the formats of the provided data require anything other than generic computing systems. As such, these limitations equate to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. As such, claims 1-14 are directed to an abstract idea. ( Step 2A, Prong 2 : NO). Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment. The instant claims recite additional elements enumerated above, in the section on step 2A. The additional elements of claims 1-5, 8-12 are describing the functions and embodiment of a nanopore sequencing workflow. Nanopore sequencing is a well-understood, routine and conventional technique in the bioinformatics art, as evidenced by figure 1, box 1 and description of Deamer et al. (Nature Biotechnology volume 34, pages518–524 (2016)), which shows two liquid tanks with electrodes and a film disposed between, an anmeter, and the output of a base caller. Models to classify the accuracy of the data are also discussed (pg 522 right col ¶ 4-5). Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; has been found to be a well-understood, routine, conventional activity. The remaining additional elements set forth limitations about neural networks, which are also well-understood, routine and conventional, as evidenced by Abiodun et al. (IEEE Access, VOLUME 7, 2019). As discussed above, there are no additional limitations to indicate that the claimed neural network requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself ( Step 2B : No). As such, claims 1-14 are not patent eligible. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 1-3 and 5-14 are rejected under 35 U.S.C. 103 as being unpatentable over Washio et al. (JPWO2018207524A1, IDS reference), Nishida et al. (JPWO2018181458A1, IDS reference) and Ryosuke et al. (WO2019026359, IDS reference). Washio describes a method for generating a learned model (classifier) for classifying a tunnel current pulse by a nanogap electrode in a biomolecule measuring device (classification analysis device), wherein the learned model is generated by a PU method which is a kind of semi-supervised learning algorithm, and the learned model classifies the tunnel current pulse into good data or bad data (noise pulse) (in particular, Claims 1-2, ¶ [0031] - [0039], [0088], [0091] - [0100], and Figs. 1-4 and 15). In addition, it is deemed that Washio also describes that this method can be applied not only to the detection waveform by the nanogap electrode but also to the detection waveform by the measurement system of the through hole corresponding to the sample object (¶ [0088]), and also describes that the nanopore blockage event data is classified by the trained model. Then, when the invention according to Claim 1 is compared with the invention described in Washio, the invention according to Claim 1 includes generating a first trained model by executing machine learning of a learning model using first teacher data, the first teacher data includes teacher blockage event data and a teacher label, and the teacher label represents whether the teacher blockage event data is classified as good data or bad data, whereas The invention described in Washio is different in that a trained model is generated by the PU method, which is a kind of semi-supervised learning algorithm. However, using a supervised learning algorithm as a machine learning method is well known as can be seen in Nishida (in particular, ¶ [0130]) and Ryosuke (in particular, ¶ [0020]), and a person skilled in the art could have appropriately used a supervised learning algorithm instead of the PU method, which is a kind of semi-supervised learning algorithm, when generating a trained model in the invention described in Washio. Regarding claims 2-3, Washio describes that the base sequence of the biomolecule is determined (¶ [0031]), and that classification is performed using data representing the feature amount of the tunnel current pulse. Regarding claims 5 and 7, Washio describes that a base sequence is determined using a trained model (Claim 2). A neural network is taught as a learning model (Washio specification ¶ [0258]). Regarding claim 6, Washio (¶ [0260]) teaches the use of an accuracy test to test their classifier models, and notes the classifier which performed best, providing a suggestion to use data related to a model only if that model has a high enough accuracy. Regarding claims 8 and 9, As described above, it is deemed that Washio describes that nanopore blockage event data is classified by a trained model, and taught that a biomolecule measuring device for acquiring nanopore blockage event data is composed of a first liquid tank, a second liquid tank, a thin film (a solid material) on which nanopores (which are pores) are formed and arranged between the first liquid tank and the second liquid tank, a first electrode provided in the first liquid tank, a second electrode provided in the second liquid tank, and an ammeter for measuring a current value flowing between the first electrode and the second electrode, as seen in paragraphs [0091] - [0100] and Fig. 15 of Washio. For claims 10-14, which are restatements of previous dependent claims, please refer to the examination of Claims 1-7. Regarding claims 1-3 and 5-14, An invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention if some teaching, suggestion, or motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. There is a teaching to use supervised learning in the text of Nishida and Ryosuke, to improve the classification accuracy (Nishida ¶ [0130], Ryosuke ¶ [0020]). There would be a reasonable expectation of success in making this combination to a person of ordinary skill in the art, as there is nothing blocking the artisan from trying to use a different learning method for this use case. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the method of Washio by using supervised learning models, in order to improve the accuracy of the method. Claims 4 is rejected under 35 U.S.C. 103 as being unpatentable over Washio, Nishida and Ryosuke as applied to claims 1-3 and 5-14 above, and further in view of Shibahara et al(WO2019026359A1, IDS reference). Washio, Nishida, and Ryosuke teach the limitations these claims are dependent upon. Regarding claim 4, Shibahara describes that the current value of the blockage event data is a plurality of discretized values corresponding to any of the bases of the biomolecule (in particular, Figs. 1-2). Regarding claim 4 , An invention would have been prima facie obvious to one of ordinary skill in the art at the time of the effective filing date of the invention if some teaching, suggestion, or motivation in the prior art would have led that person to combine the prior art teachings to arrive at the claimed invention. There is a teaching to use blockage event data in the text of Shibahara, in order to reduce the impact of vibrations on sequence decoding (abstract). There would be a reasonable expectation of success in making this combination to a person of ordinary skill in the art, as there is nothing stopping this kind of data from being used in Washio. Therefore, it would have been prima facie obvious to one of ordinary skill in the art at the time to modify the method of Washio by adding the data considerations of Shibahara, in order to reduce the impact of vibrations on sequencing. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to GRACELYN M HILL whose telephone number is (571)272-9871. The examiner can normally be reached Monday-Friday 8:30-5pm. 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, Olivia M. Wise can be reached at 571-272-2249. 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. /G.M.H./Examiner, Art Unit 1685 /OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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Prosecution Timeline

Jan 20, 2023
Application Filed
Jun 10, 2026
Non-Final Rejection mailed — §101, §103, §112 (current)

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ADAPTIVE BRAIN TRAINING COMPUTER SYSTEM AND METHOD
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Expected OA Rounds
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Grant Probability
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4y 11m (~1y 5m remaining)
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