Prosecution Insights
Last updated: July 17, 2026
Application No. 18/766,090

SYSTEM AND METHOD FOR GENERATING A COGNITIVE DISORDER NOURISHMENT PROGRAM

Final Rejection §101
Filed
Jul 08, 2024
Priority
Mar 01, 2021 — CIP of 11/694,787 +1 more
Examiner
SIOZOPOULOS, CONSTANTINE B
Art Unit
3686
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
KPN Innovations LLC
OA Round
2 (Final)
58%
Grant Probability
Moderate
3-4
OA Rounds
12m
Est. Remaining
97%
With Interview

Examiner Intelligence

Grants 58% of resolved cases
58%
Career Allowance Rate
100 granted / 171 resolved
+6.5% vs TC avg
Strong +38% interview lift
Without
With
+38.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
33 currently pending
Career history
206
Total Applications
across all art units

Statute-Specific Performance

§101
39.5%
-0.5% vs TC avg
§103
33.5%
-6.5% vs TC avg
§102
23.7%
-16.3% vs TC avg
§112
2.1%
-37.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 171 resolved cases

Office Action

§101
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 Arguments Regarding the arguments against the rejection of claims under 35 USC 101, the Examiner respectfully disagrees. Applicant argues that the claims do not recite a mental process. In response to the current amendments, the abstract idea under Step 2 A Prong 1 has been re-analyzed as being certain methods of organizing human activity and updated as noted below. Further, the use of the machine learning models and training steps with training data sets for the abstract steps are not abstract, however they are analyzed under Step 2A Prong 2 as being insignificant additional elements as noted below. Additionally, the use of the biological sampling device to obtain samples recites insignificant pre solution activity as noted, not a part of the abstract idea. The “output” as noted in the Step 2A Prong 1 analysis recites as part of the abstract idea as noted below. Applicant further argues that the claims recite a practical application, as the claims are analogous to Example 47 as the claims recite specific, computer implemented machine learning pipeline to generate a cognitive disorder nourishment program. Examiner asserts that Example 47 recites a specific technology improvement related to IT networks using the ANN. The instant application however recites generic additional elements that recite mere computer implementation when viewed individually and in combination. The use of the generic computing components to merely automate the abstract process and improve accuracy, consistency, and scalability of the abstract idea does not recite a technology improvement, see MPEP 2106.05(f), specifically” "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).” Applicant further argues that the claims are analogous to Example 48 in that the claims recite AI operations that are expressly tied to generating a specific, technical meaningful output through a concrete sequence of data retrieval and model executed transformations, rather than just applying AI. Examiner further asserts that Example 48 recites a specific technology improvement related to signal processing, however the instant application does not recite such specific technology improvement. The output of the nourishment program recites an abstract idea where the additional elements of the ML models and use of the directory recites mere computer implementation and accessing information in a generic manner for the data gathering step as noted in the rejection below. Applicant further argues that the claims recites significantly more than the judicial exception under Step 2B. Examiner further asserts that under the Berkheimer analysis, the additional elements are recited at a generic level as noted in the Applicant’s Specification, and further the recitation of relevant court cases that demonstrate the retrieval of information from memory and the transmission of data to a computer from another device recites well understood, routine, and conventional activity. As noted, the use of these elements to improve the consistency, relatability, and selection of nourishments programs for a user recites an improvement to the abstract idea and does not recite a practical application, nor do the elements provide an inventive concept under Step 2B. See MPEP 2106.05(a)II, particularly “Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.” Regarding the arguments against the rejection of claims under 35 USC 102, Examiner agrees and therefore this rejection is withdrawn. 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 1-20 are rejected under 35 USC 101 because the claimed invention is directed to an abstract idea without significantly more. It is appropriate for the Examiner to determine whether a claim satisfies the criteria for subject matter eligibility by evaluating the claim in accordance to the Subject Matter Eligibility Test as recited in the following Steps: 1, 2A, and 2B, see MPEP 2106(III.). Patent Subject Matter Eligibility Test: Step 1: First, the Examiner is to establish whether the claim falls within any statutory category including a process, a machine, manufacture, or composition of matter, see MPEP 2106.03(II.) and MPEP 2106.03(I). Claims 1-10 are related to a system, and claims 11-20 are also related to a method (i.e., a process). Accordingly, these claims are all within at least one of the four statutory categories. Patent Subject Matter Eligibility Test: Step 2A- Prong One: Step 2A of the Subject Matter Eligibility Test demonstrates whether a clam is directed to a judicial exception, see MPEP 2106.04(I.). Step 2A is a two-prong inquiry, where Prong One establishes the judicial exception. Regarding Prong One of Step 2A, the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation, they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes, see MPEP 2106.04(II.)(A.)(1.) and 2106.04(a)(2). Representative independent claim 1 includes limitations that recite at least one abstract idea as underlined in the following limitations. Specifically, independent claim 1 recites: A system for generating a cognitive disorder nourishment program, the system comprising: a processor; and a memory communicatively connected to the processor, wherein the memory contains instructions configuring the processor to: obtain at least a cognitive indicator element comprising at least a biomarker and at least a user preference, wherein obtaining the at least a cognitive indicator element comprises obtaining a biological sample using a biological sampling device; determine an edible as a function of the at least a cognitive indicator element, wherein determining the edible further comprises: producing a cognitive appraisal as a function of the cognitive indicator element and a cognitive function using a cognitive machine-learning model, wherein the cognitive machine-learning model is trained using a cognitive training set correlating cognitive functions and cognitive indicator elements to cognitive appraisals; retrieving, from an edible directory, nourishment compositions for a plurality of candidate edibles; and identifying the edible using an edible machine-learning model configured to receive the cognitive appraisal and the nourishment compositions and output the edible; and generate a nourishment program as a function of the edible, wherein generating the nourishment program further comprises generating the nourishment program as a function of an intended outcome using a nourishment machine-learning model configured to output the nourishment program as a function of the edible and the intended outcome. The Examiner submits that the foregoing underlined limitations constitute “certain methods of organizing human activity”, more specifically managing interactions between people as the following abstract limitations recite generating and outputting a cognitive disorder nourishment program for a user: “determine” an edible as a function of the at least a cognitive indicator element, which is an abstract limitation of an evaluation of the cognitive indicator element to make a determination of edible, determining the edible further comprises “producing” a cognitive appraisal as a function of the cognitive indicator element and a cognitive function, which recites abstract limitations of analysis of the cognitive indicator elements and function for producing an appraisal, “correlating” cognitive functions and cognitive indicator elements to cognitive appraisals, which recites an analysis of the cognitive functions and cognitive indicator elements to cognitive appraisals, “identifying” the edible and to receive the cognitive appraisal and the nourishment compositions and “output” the edible, which are abstract limitations of analysis of the edible and an interaction to receive the appraisal and the compositions, and further an interaction to present the edible, “generate” a nourishment program as a function of the edible, which is an abstract limitation of a judgment of a nourishment program after consideration of the edible, generating the nourishment program further comprises “generating” the nourishment program as a function of an intended outcome, which recites an abstract limitation of analysis and determination of the program to be given to the user, “output” the nourishment program as a function of the edible and the intended outcome, which is an abstract limitation of an interaction to present the nourishment program that was generated. The claim limitations as a whole recite steps for generating and outputting a cognitive disorder nourishment program for a user, which recites social activity steps for the management of the nourishment plan of the user and therefore recite managing interactions between people and is a certain method of organizing human activity. The abstract idea recited in claim 11 similar to that of claim 1. Any limitations not identified above as part of the abstract idea are deemed “additional elements” (i.e., processor) and will be discussed in further detail below. Accordingly, the claim as a whole recites at least one abstract idea. Furthermore, dependent claims further define the at least one abstract idea, and thus fails to make the abstract idea any less abstract as noted below: Claims 2 and 12 recite further abstract limitation of “determining” the edible by determining the edible as a function of a digestive analysis, further describing the abstract idea. Claims 3 and 13 recite further abstract limitations describing the determination of the edible as “identifying” a nourishment demand and further describing the generating of the nourishment program as a function of the identified demand, further describing the abstract idea. Claims 6 and 16 recite further abstract limitations describing the generation of the nourishment program as comprising “identifying” at least a dietary source, further describing the abstract idea. Claims 7 and 17 recite further abstract limitations describing the generation of the nourishment program by “identifying” a threshold amount of consumption for a user and further generating the program as a function of the threshold amount of consumption, further describing the abstract idea. Claims 10 and 20 recite further abstract limitations of “updating” the nourishment program as a function of user feedback, further describing the abstract idea. Patent Subject Matter Eligibility Test: Step 2A- Prong Two: Regarding Prong Two of Step 2A, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. It must be determined whether any additional elements in the claim beyond the abstract idea integrates the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exceptions into a “practical application,” see MPEP 2106.04(II.)(A.)(2.) and 2106.04(d)(I.). In the present case, the additional limitations beyond the above-noted at least one abstract idea are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”): A system for generating a cognitive disorder nourishment program, the system comprising: a processor; and a memory communicatively connected to the processor, wherein the memory contains instructions configuring the processor to (amounts to nothing more than an instruction to apply the abstract idea using a generic computer as noted below, see MPEP 2106.05(f)): obtain at least a cognitive indicator element comprising at least a biomarker and at least a user preference, wherein obtaining the at least a cognitive indicator element comprises obtaining a biological sample using a biological sampling device (merely data gathering steps as noted below, see MPEP 2106.05(g) and Versata Dev. Group, Inc. v. SAP Am., Inc.); determine an edible as a function of the at least a cognitive indicator element, wherein determining the edible further comprises: producing a cognitive appraisal as a function of the cognitive indicator element and a cognitive function using a cognitive machine-learning model, wherein the cognitive machine-learning model is trained using a cognitive training set (amounts to nothing more than an instruction to apply the abstract idea using a generic computer as noted below, see MPEP 2106.05(f)) correlating cognitive functions and cognitive indicator elements to cognitive appraisals; retrieving, from an edible directory, nourishment compositions for a plurality of candidate edibles; and (merely data gathering steps as noted below, see MPEP 2106.05(g) and Versata Dev. Group, Inc. v. SAP Am., Inc.) identifying the edible using an edible machine-learning model configured to (amounts to nothing more than an instruction to apply the abstract idea using a generic computer as noted below, see MPEP 2106.05(f)) receive the cognitive appraisal and the nourishment compositions and output the edible; and generate a nourishment program as a function of the edible, wherein generating the nourishment program further comprises generating the nourishment program as a function of an intended outcome using a nourishment machine-learning model configured to (amounts to nothing more than an instruction to apply the abstract idea using a generic computer as noted below, see MPEP 2106.05(f)) output the nourishment program as a function of the edible and the intended outcome. For the following reasons, the Examiner submits that the above identified additional limitations do not integrate the above-noted at least one abstract idea into a practical application. Regarding the additional limitations of the overall computing system comprising a processor and memory, use of a cognitive machine-learning model, wherein the cognitive machine-learning model is trained using a cognitive training set, use of an edible machine-learning model, and use of a nourishment machine-learning model, the Examiner submits that these limitations amount to nothing more than an instruction to apply the abstract idea using a generic computer and generic computing components (see MPEP § 2106.05(f)). [0009] of the Applicant’s Specification recites the overall generic computing system with the use of generic processors and memory. [0017, 0018, 0019] recites the generic training using the training set and construction of the cognitive ML model. [0030] recites the generically constructed edible ML model. [0040] recites the generically constructed nourishment ML model. The additional elements recite the use of generic computing components with a non-specific implementation to carry out steps of the abstract idea without showing an improvement to technology, computers or other technical fields, and thus recites mere instructions to implement the abstract idea on a computer. Claim 11 recites similar additional elements and are analyzed in a similar manner. Regarding the additional limitations of obtain at least a cognitive indicator element comprising at least a biomarker and at least a user preference, wherein obtaining the at least a cognitive indicator element comprises obtaining a biological sample using a biological sampling device and retrieving, from an edible directory, nourishment compositions for a plurality of candidate edibles, these are merely pre-solution activities. The Examiner submits that this additional limitation merely adds insignificant extra-solution activity of collecting data to the at least one abstract idea in a manner that does not meaningfully limit the at least one abstract idea (see MPEP § 2106.05(g)). [0011, 0044] of the Applicant’s Specification recites the action of obtaining or gathering the biomarker and user preferences. [0011] recites the use of the biological sampling device for the action of gathering biological sample. [0027, 0047] recites the retrieval of information from storage in the edible directory. The data transmission from the sampling device and retrieval of information from the directory are used to perform actions for the system including data gathering for the abstract idea, and thus recites insignificant pre-solution activities. Claim 11 recites similar additional elements and are analyzed in a similar manner. Taken alone, the additional elements do not integrate the at least one abstract idea into a practical application. Looking at the additional limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to generate and output a cognitive disorder nourishment program for a user, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception, see MPEP 2106.04(d), 2106.05(a), 2106.05(b). The remaining dependent claim limitations not addressed above fail to integrate the abstract idea into a practical application as set below: Claims 4 and 14 recites limitations further describing the obtained cognitive indicator element, however this still recites insignificant pre-solution activity. Claims 5 and 15 recites further limitations of the obtained biomarker and further the obtained behavior as being intercorrelated, however this still recites insignificant pre-solution activity. Claims 8 and 18 recite further detail of the obtained user behavior, however this still recites insignificant pre-solution activity. Claims 9 and 19 recite further limitations of how the cognitive indicator elements are obtained, however this still recites insignificant pre-solution activity. Claims 10 and 20 recite further additional elements of “receiving” user feedback as a function of implementing the nourishment program, however this recites insignificant pre-solution activity. Thus, taken alone and in ordered combination, the additional elements do not integrate the at least one abstract idea into a practical application. Patent Subject Matter Eligibility Test: Step 2B: Regarding Step 2B of the Subject Matter Eligibility Test, the independent claims do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application, see MPEP 2106.05(II.). Further, it may need to be established, when determining whether a claim recites significantly more than a judicial exception, that the additional elements recite well understood, routine, and conventional activities, see MPEP 2106.05(d). Regarding the additional limitations of the overall computing system comprising a processor and memory, use of a cognitive machine-learning model, wherein the cognitive machine-learning model is trained using a cognitive training set, use of an edible machine-learning model, and use of a nourishment machine-learning model, the Examiner submits that these limitations amount to nothing more than an instruction to apply the abstract idea using a generic computer and generic computing components (see MPEP § 2106.05(f)). [0009] of the Applicant’s Specification recites the overall generic computing system with the use of generic processors and memory. [0017, 0018, 0019] recites the generic training using the training set and construction of the cognitive ML model. [0030] recites the generically constructed edible ML model. [0040] recites the generically constructed nourishment ML model. The additional elements recite the use of generic computing components with a non-specific implementation to carry out steps of the abstract idea without showing an improvement to technology, computers or other technical fields, and thus recites mere instructions to implement the abstract idea on a computer and does not recite significantly more than the judicial exception. Claim 11 recites similar additional elements and are analyzed in a similar manner. Regarding the additional limitations of obtain at least a cognitive indicator element comprising at least a biomarker and at least a user preference, wherein obtaining the at least a cognitive indicator element comprises obtaining a biological sample using a biological sampling device and retrieving, from an edible directory, nourishment compositions for a plurality of candidate edibles, these are merely pre-solution activities. The Examiner submits that this additional limitation merely adds insignificant extra-solution activity of collecting data to the at least one abstract idea in a manner that does not meaningfully limit the at least one abstract idea (see MPEP § 2106.05(g) and MPEP § 2106.05(d)(II), specifically “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” and “buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)”). [0011, 0044] of the Applicant’s Specification recites the action of obtaining or gathering the biomarker and user preferences. [0011] recites the use of the biological sampling device for the action of gathering biological sample. [0027, 0047] recites the retrieval of information from storage in the edible directory. The data transmission from the sampling device and retrieval of information from the directory are used to perform actions for the system including data gathering for the abstract idea, and thus recites insignificant pre-solution activities and does not recite more than the judicial exception. The retrieval these indicator elements as recited in [0011] of the Applicant’s Specification can be interpreted as a retrieval of information from memory or merely transmitting data from the cognitive indicator element to the computing device, and thus recites well understood, routine, and conventional activities. Use of the sampling device as the cognitive indicator element to gather data and transmit it to the computing device also recites well understood, routine, and conventional activity. Further, the retrieval of the compositions from the storage of the edible directory recites well understood, routine, and conventional activity. Claim 11 recites similar additional elements and are analyzed in a similar manner. The dependent claims do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exceptions for the same reasons to those discussed above with respect to determining that the dependent claims do not integrate the at least one abstract idea into a practical application. For the reasons stated, the claims fail the Subject Matter Eligibility Test and therefore claims 1-20 are rejected under 35 USC 101 as being directed to non-statutory subject matter. The following references have been considered as relevant, however have not been used in the above rejections and do not teach the current invention separately nor in combination: US 20180308389 A1 to Moser et al. teaches of improving cognitive help by generating a nutritional plan for a user using components such as an automated health advisor and adjusting nutrition plans. WO-2024226343-A1 to Rosenberg et al. teaches of generating a dietary treatment plan by analyzing patient characteristics. NPL “Automated and personalized meal plan generation and relevance scoring using a multi-factor adaptation of the transportation problem” to Salloum et al. teaches of an automated meal plan generator. These references do not teach aspects of the current invention including but not limited to: “ wherein determining the edible further comprises: producing a cognitive appraisal as a function of the cognitive indicator element and a cognitive function using a cognitive machine-learning model, wherein the cognitive machine-learning model is trained using a cognitive training set correlating cognitive functions and cognitive indicator elements to cognitive appraisals; retrieving, from an edible directory, nourishment compositions for a plurality of candidate edibles; and identifying the edible using an edible machine-learning model configured to receive the cognitive appraisal and the nourishment compositions and output the edible” Conclusion THIS ACTION IS MADE FINAL. 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 CONSTANTINE SIOZOPOULOS whose telephone number is (571)272-6719. The examiner can normally be reached Monday-Friday, 8AM-5PM EST. 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, Jason B Dunham can be reached at (571) 272-8109. 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. /CONSTANTINE SIOZOPOULOS/ Examiner Art Unit 3686
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Prosecution Timeline

Jul 08, 2024
Application Filed
Oct 17, 2025
Non-Final Rejection mailed — §101
Mar 03, 2026
Interview Requested
Mar 17, 2026
Applicant Interview (Telephonic)
Mar 21, 2026
Examiner Interview Summary
Apr 17, 2026
Response Filed
Jun 26, 2026
Final Rejection mailed — §101 (current)

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Expected OA Rounds
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Grant Probability
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