DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This communication is in response to the Remarks filed on 12/16/2025.
Claims 1-21 are pending. New claim 21 is added.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/16/2023 and 9/18/2025 has been considered by the examiner.
Response to Arguments
Applicant’s arguments, filed under Remarks on pages 8-9 on 12/16/2025, with respect to claims 1-20, have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Objections
Claim 21 is objected to because of the following informalities: claim 21 recites acronym BCVA. Please define the acronym in its full form within the claim. Appropriate correction is required.
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 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., abstract idea – mental process) without significantly more. Claim 1 is used as an example. Claims 8 and 15 recite a system and non-transitory machine-readable medium, respectively, having a memory and a processor. The two-part test to identify claims that are directed to a judicial exception (Step 2A) and to then evaluate if additional elements of the claim provide an inventive concept (Step 2B) are:
(1) Are the claims directed to a process, machine, manufacture or composition of matter;
(2A) Prong One: Are the claims directed to a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea;
Prong Two: If the claims are directed to a judicial exception under Prong One, then is the judicial exception integrated into a practical application;
(2B) If the claims are directed to a judicial exception and do not integrate the judicial exception, do the claims provide an inventive concept.
Claim 1. A method for predicting a visual acuity response, the method comprising: (a) receiving a first input that includes two-dimensional imaging data associated with a subject undergoing a treatment; (b) receiving a second input that includes three-dimensional imaging data associated with the subject undergoing the treatment; and (c) predicting, via a neural network system, a visual acuity response (VAR) output using the first input and the second input, the VAR output comprising a predicted change in visual acuity of the subject undergoing the treatment. [emphasis added].
With regard to (1), the instant claims recite an apparatus and a method, therefore the answer is "yes".
With regard to (2A), Prong One: Yes. Claim 1 recites an abstract idea of mental processes “receiving” and “predicting.” Regarding the limitations (a) “receiving a first input…” and (b) “receiving a second input…”, these steps of “collecting information” are recited at a high level of generality such that they could practically be performed in the human mind, with or without using a computer, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). See MPEP 2106.04(a)(2)(III)(A). Support for this interpretation is provided in the instant specification as described in paragraphs [0040, 0045-0047].
Regarding the limitation (c) “predicting…a visual acuity response (VAR) output using the first input and the second input…”, the step is recited at a high level of generality such that this step could be practically performed in the human mind, with or without using a computer. An ophthalmologist, for example, can predict or estimate the change in a future visual acuity of a patient, based on knowledge, fact, and/or reasoning. This concept, under the broadest reasonable interpretation, covers performance of the limitation in the mind as observations, evaluations, judgements, and/or opinions but for generic computer components. See MPEP 2106.04(a)(2)(III)(A). The instant specification provides support for this interpretation at paragraphs [0049, 0051, 0053, 0040]. Thus, these limitations are a mental process.
With regard to (2A), Prong Two: No. The instant claims do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, and therefore does not integrate the judicial exception into a practical application.
Claim 1 recites the additional elements of “two-dimensional imaging data associated with a subject undergoing a treatment” and “three-dimensional imaging data associated with the subject undergoing the treatment”, “a predicted change in visual acuity of the subject undergoing the treatment” and “a neural network system.”
Regarding the particular type of information (“two-dimensional imaging data associated with a subject undergoing a treatment” and “three-dimensional imaging data associated with the subject undergoing the treatment”, “a predicted change in visual acuity of the subject undergoing the treatment”), these limitations simply link the use of the abstract idea to the environment of “techniques for predicting visual acuity response in patients undergoing treatment.” As such, the additional elements do not integrate the abstract idea into a practical application. See MPEP section 2106.04(d).
Regarding the limitation “a neural network system”, this limitation provides nothing more than mere instructions to implement an abstract idea on a generic computer. The neural network system is used to generally apply the abstract idea without limiting how the neural network system functions. The instant specification provides support for this interpretation. As described in paragraphs [0037], [0038], [0040] and [0042], employing a neural network is generic in the context of the disclosure because it refers to generic neural networks. The claim invokes the neural network system merely as a tool to perform an existing process of “predicting.” According to the MPEP section 2106.05(f), claim limitations that do not amount to more than a recitation of mere instructions to implement an abstract idea on a computer do not integrate the abstract idea into a practical application.
Moreover, the claim does not appear to reflect an improvement to another technology or technical field. Regarding the discussion of “a need for systems and methods that can predict how well a subject having nAMD is likely to respond to treatment with an anti-VEGF drug” and “such predictions may improve clinical trial screening, prescreening, or both by enabling the exclusion of those subjects predicted to not respond well to treatment” presented in the specification (paragraphs [0003], [0016]), the claim does not appear to cover a particular solution to the problem or a particular way to achieve a desired outcome. It simply recites the idea of a solution or outcome (“predicting, via a neural network system, a visual acuity response (VAR) output using the first input and the second input, the VAR output comprising a predicted change in visual acuity of the subject undergoing the treatment”). As for the discussion pertaining to the reduction in the processing power and size of the portion of the neural network system by converting the OCT images into tabular form, the claim does not include the components or steps of the invention that provide the improvement described in the specification. In sum, the usage of the neural network system and the combination of the types of imaging data, as claimed, does not provide any improvements to the existing technology. See MPEP sections 2106.04(d) and 2106.05(a).
For at least the above reasons, the additional elements do not integrate the abstract idea into a practical application. See MPEP 2106.04(d).
With regard to (2B), as discussed with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here. Claim 1 recites the additional elements of “two-dimensional imaging data associated with a subject undergoing a treatment” and “three-dimensional imaging data associated with the subject undergoing the treatment”, “a predicted change in visual acuity of the subject undergoing the treatment” and “a neural network system.”
Regarding the particular type of information (“two-dimensional imaging data associated with a subject undergoing a treatment” and “three-dimensional imaging data associated with the subject undergoing the treatment”, “a predicted change in visual acuity of the subject undergoing the treatment”), these limitations simply link the use of the abstract idea to the environment of “techniques for predicting visual acuity response in patients undergoing treatment.” See MPEP section 2106.05(h).
Regarding the limitation “a neural network system”, this limitation provides nothing more than mere instructions to implement an abstract idea on a generic computer. The neural network system is used to generally apply the abstract idea without limiting how the neural network system functions. The instant specification provides support for this interpretation. As described in paragraphs [0037], [0038], [0040] and [0042], employing a neural network is generic in the context of the disclosure because it refers to generic neural networks. The claim invokes the neural network system merely as a tool to perform an existing process of “predicting.” See MPEP section 2106.05(f).
Moreover, the claim does not appear to reflect an improvement to another technology or technical field. Regarding the discussion of “a need for systems and methods that can predict how well a subject having nAMD is likely to respond to treatment with an anti-VEGF drug” and “such predictions may improve clinical trial screening, prescreening, or both by enabling the exclusion of those subjects predicted to not respond well to treatment” presented in the specification (paragraphs [0003], [0016]), the claim does not appear to cover a particular solution to the problem or a particular way to achieve a desired outcome. It simply recites the idea of a solution or outcome (“predicting, via a neural network system, a visual acuity response (VAR) output using the first input and the second input, the VAR output comprising a predicted change in visual acuity of the subject undergoing the treatment”). As for the discussion pertaining to the reduction in the processing power and size of the portion of the neural network system by converting the OCT images into tabular form, the claim does not include the components or steps of the invention that provide the improvement described in the specification. See MPEP sections 2106.04(d) and 2106.05(a). In other words, the usage of the neural network system and the combination of the types of imaging data, as claimed, does not provide any improvements to the existing technology.
In summary, the additional elements, taken individually and in an ordered combination, do not result in the claim as a whole amounting to significantly more than the above-identified judicial exception (the abstract idea). See MPEP section 2106.05.
For at least the above reasons, claims 1, 8 and 15 are rejected under 35 USC 101 as being directed to an abstract idea without reciting significantly more.
With regard to dependent claims 2-7, 9-14, and 16-21 similar analysis is applied and therefore does not integrate the judicial exception into a practical application – does not provide significant more than the judicial exception. Several dependent claims describe several subsystems and routine neural-network elements - Input layers, dense hidden layers, a trained image-recognition model, combining the outputs, and applying a trained model. These are generic components and standard workflow steps. These claims are similarly rejected for the same reasons discussed in view of steps recited in claims 1, 8 and 15, and not repeated herewith.
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-4, 7-11, 14-18, and 21 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 2022/0230300 to Kawczynski et al. (hereafter, “Kawczynski”).
With regard to claim 1, Kawczynski discloses a method for predicting a visual acuity response, the method comprising: receiving a first input that includes two-dimensional imaging data associated with a subject undergoing a treatment (“multiple A-scans can be processed to generate one or more B-scans”, paragraphs [0046, 0051], B-scans; paragraphs [0088, 0094-0105] for different treatment; paragraph [0123]); receiving a second input that includes three-dimensional imaging data associated with the subject undergoing the treatment (“C-scan (e.g., which may capture some three-dimensional information, such as depth) can be generated using multiple B-scans”, paragraphs [0044, 0052], C-scans; paragraphs [0088, 0094-0105]] for different treatment; paragraph [0123]); and predicting, via a neural network system, a visual acuity response (VAR) output using the first input and the second input, the VAR output comprising a predicted change in visual acuity of the subject undergoing the treatment (paragraphs [0061, 0072, 0082-0096, 0104-0105]).
With regard to claim 2, Kawczynski discloses wherein the three-dimensional imaging data comprises optical coherence tomography (OCT) imaging data associated with the subject undergoing the treatment and wherein the two-dimensional imaging data comprises color fundus imaging data associated with the subject undergoing the treatment (OCT images, paragraphs [0041, 0043-0046, 0089, 0097]; color fundus imaging, paragraphs [0047-0049, 0051, 0089, 0097]).
With regard to claim 3, Kawczynski discloses wherein the second input further includes a visual acuity measurement associated with the subject undergoing the treatment and demographic data associated with the subject undergoing the treatment (see, age-related macular degeneration throughout the reference, paragraphs [0033, 0035, 0037, 0097, 0107, 0115]).
With regard to claim 4, Kawczynski discloses wherein the predicting, via the neural network system, the VAR output comprises: generating a first output using the two-dimensional imaging data associated with the subject undergoing the treatment; generating a second output using the three-dimensional imaging data associated with the subject undergoing the treatment; and generating the VAR output via fusion of the first output and the second output (see claim 1 where it is shown that 2D image data and 3D image data is received/generated. Further, the B-scans are generated from combining the depth scans at the lateral positions; A three-dimensional image may be constructed to include multiple B-scans, paragraphs [0044]; paragraphs [0095, 0104, 0106]).
With regard to claim 7, Kawczynski discloses training the neural network system using two-dimensional imaging data associated with a first plurality of subjects who have previously undergone the treatment and using three-dimensional imaging data associated with a second plurality of subjects who have previously undergone the treatment (paragraphs [0113-0118, 0217-0222]).
With regard to claims 8 and 15, claims 8 and 15 are rejected same as claim 1 and the arguments similar to that presented above for claim 1 are equally applicable to claims 8 and 15, Kawczynski discloses a system with a memory and a processor at paragraphs [0188-0195] where computing system are discussed, and all of the other limitations similar to claim 1 are not repeated herein, but incorporated by reference.
With regard to claim 9, claim 9 is rejected same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to claim 9, and all of the other limitations similar to claim 2 are not repeated herein, but incorporated by reference.
With regard to claim 10, claim 10 is rejected same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to claim 10, and all of the other limitations similar to claim 3 are not repeated herein, but incorporated by reference.
With regard to claim 11, claim 11 is rejected same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to claim 11, and all of the other limitations similar to claim 4 are not repeated herein, but incorporated by reference.
With regard to claim 14, claim 14 is rejected same as claim 7 and the arguments similar to that presented above for claim 7 are equally applicable to claim 14, and all of the other limitations similar to claim 7 are not repeated herein, but incorporated by reference.
With regard to claim 16, claim 16 is rejected same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to claim 16, and all of the other limitations similar to claim 2 are not repeated herein, but incorporated by reference.
With regard to claim 17, claim 17 is rejected same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to claim 17, and all of the other limitations similar to claim 3 are not repeated herein, but incorporated by reference.
With regard to claim 18, claim 18 is rejected same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to claim 18, and all of the other limitations similar to claim 4 are not repeated herein, but incorporated by reference.
With regard to claim 21 Kawczynski discloses wherein the VAR output comprises a predicted numeric change in BCVA or one of a plurality of different classes of BCVA change (this is disclosed throughout the reference, especially at paragraphs [0112, 0120-0177]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHEFALI D. GORADIA whose telephone number is (571)272-8958. The examiner can normally be reached Monday-Thursday 8AM-6PM, Friday 8AM-12PM.
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, Henok Shiferaw can be reached at 571-272-4637. 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.
SHEFALI D. GORADIA
Primary Patent Examiner
Art Unit 2676
/SHEFALI D GORADIA/Primary Patent Examiner, Art Unit 2676