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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant’s submission filed on December 23, 2025 has been entered.
Response to Amendment
The following Office action in response to communications received December 23, 2025. Claims 1 and 11 have been amended. Therefore, claims 1-20 are pending and addressed below.
Applicant’s amendments to the claims are sufficient to overcome the 35 USC § 112, rejections set forth in the previous office action dated July 23, 2025.
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 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Based upon consideration of all of the relevant factors with respect to the claims as a whole, the claims are directed to non-statutory subject matter which do not include additional elements that are sufficient to amount to significantly more than the judicial exception because of the following analysis:
Independent Claim(s) 1 and 11 are directed to a system for nutritional recommendation using analysis of immune impacts to designed and configured to receive test results detecting an effect of at least an aliment on at least a biomarker and determine an immune system impact of the at least an aliment as a function of the at least a biomarker. The claim(s) recite(s) “receiving, a behavioral datum of a user; receiving, a test result detecting an effect of at least the behavioral datum on at least a biomarker; receiving a first training set, wherein the first training set correlates biomarker levels to immune system function; and determining, an immune system impact of the behavioral datum as a function of the at least a biomarker; generating, a nutritional recommendation using the determined immune system impact of the behavioral datum as a function of the at least a biomarker; map, the immune system impact to one or more nutritional categories, wherein each nutritional category is associated with a descriptor in a standardized format, and the immune system impact is associated with the nutritional category by one or more tokens; modeling the one or more tokens as a chain; estimating, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category; generate a nutritional recommendation using based on the mapped nutritional category, wherein the nutritional recommendation is derived as a function of the determined immune system impact and the one or more tokens linking the immune system impact to the nutritional category; and display, the nutritional recommendation to the user, wherein displaying the nutritional recommendation comprises: filtering, aliments of the nutritional recommendation using one or more elements of user data; and modifying, using an interactive feature, the nutritional recommendation based on user input.”
The limitations of “receiving, a behavioral datum of a user; receiving, a test result detecting an effect of at least the behavioral datum on at least a biomarker; receiving a first training set, wherein the first training set correlates biomarker levels to immune system function; and determining, an immune system impact of the behavioral datum as a function of the at least a biomarker; generating, a nutritional recommendation using the determined immune system impact of the behavioral datum as a function of the at least a biomarker; map, the immune system impact to one or more nutritional categories, wherein each nutritional category is associated with a descriptor in a standardized format, and the immune system impact is associated with the nutritional category by one or more tokens; modeling the one or more tokens as a chain; estimating, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category; generate a nutritional recommendation using based on the mapped nutritional category, wherein the nutritional recommendation is derived as a function of the determined immune system impact and the one or more tokens linking the immune system impact to the nutritional category; and display, the nutritional recommendation to the user, wherein displaying the nutritional recommendation comprises: filtering, aliments of the nutritional recommendation using one or more elements of user data; and modifying, using an interactive feature, the nutritional recommendation based on user input,” as drafted, under its broadest reasonable interpretation, covers the performance of a Mental Process concepts performed in the human mind (including an observation, evaluation, judgment, opinion), but for the recitation of generic computer components. That is, other than reciting “memory, computing device, machine-learning model, display device, statistical model, and inference algorithm” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “memory, computing device” language, “receiving” in the context of this claim encompasses the user manually retrieving patient behavioral datum. Similarly, the receiving, a test result detecting an effect of at least the behavioral datum on at least a biomarker, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of using a “memory, computing device, machine-learning model, display device, statistical model, and inference algorithm” to perform all of the “receiving, generating, determining, mapping, modeling, estimating, displaying, filtering and modifying” steps. The “memory, computing device, machine-learning model, display device, statistical model, and inference algorithm” are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of executing computer-executable instructions for implementing the specified logical function(s) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Claim 1 has the following additional elements (i.e., memory, computing device, machine-learning model, display device, statistical model, and inference algorithm). Claim 11 has the following additional elements (i.e., computing device, machine-learning model, display device, statistical model, and inference algorithm). Looking to the specification, these components are described at a high level of generality (¶ 8 and 86-87; System includes a computing device104. Computing device104 may include any computing device104 as described in this disclosure, including without limitation a microcontroller, microprocessor, digital signal processor (DSP) and/or system on a chip (SoC) as described in this disclosure. Computing device104 may include, be included in, and/or communicate with a mobile device such as a mobile telephone or smartphone. Computing device104 may include a single computing device104 operating independently, or may include two or more computing device104 operating in concert, in parallel, sequentially or the like; two or more computing device104 may be included together in a single computing device104 or in two or more computing device104. Computing device104 may interface or communicate with one or more additional devices as described below in further detail via a network interface device). The use of a general-purpose computer, taken alone, does not impose any meaningful limitation on the computer implementation of the abstract idea, so it does not amount to significantly more than the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology and their collective functions merely provide a conventional computer implementation of the abstract idea. Furthermore, the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generally linking the abstract idea to a particular technological environment or field of use, as the courts have found in Parker v. Flook. Therefore, there are no limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception.
Dependent claims 2-10 and 12-20 include all the limitations of the parent claims and are directed to the same abstract idea as discussed above and incorporated herein. Although the dependent claims add additional limitations, they only serve to further limit the abstract idea by reciting limitations on what the information is and how it is received and used. These information characteristics do not change the fundamental analogy to the abstract idea grouping of “Mental Process,” and, when viewed individually or as a whole, they do not add anything substantial beyond the abstract idea. Furthermore, the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology. Therefore, the claims when taken as a whole are ineligible for the same reasons as the independent claims.
Claims 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Response to Arguments
Applicant’s arguments filed December 23, 2025 have been fully considered but they are not persuasive. In the remarks applicant argues:
(1) Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Applicant respectfully traverses.
Under the January 2019 Guidance, now incorporated in the June 2020 revision of Manual of Patent Examining Procedure ("MPEP"), the first step of the Alice Corp. Pty. Ltd/Mayo Collaborative Services test was revised. MPEP 2106.04 [incorporating 2019 Revised Patent Subject Matter Eligibility Guidance, 84, Fed. Reg. 50, 52 (January 7, 2019)]. Revised Step 2A now focuses on (1) Whether the claim recites a judicial exception and (2) whether a recited judicial exception is integrated into a practical application. Id. Only if a claim recites a judicial exception and fails to integrate the exception into a practical application, further analysis pursuant to the second step (2B) in the Alice Corp. Pty. Ltd Mayo Collaborative Services test is needed. Id.
Additionally, the July 2024 Subject Matter Eligibility Examples should be used in
conjunction with the USPTO guidance on subject matter eligibility, which is incorporated into MPEP 2106. These examples are discussed in the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence. The update includes examples 47-49, which provide insights into the application of the guidance, particularly for emerging technologies like artificial intelligence.
Solely in the interest of advancing prosecution and while not acquiescing to the Examiner's position, Applicant has amended claim 1 to recite:
1. A system for nutritional recommendation using artificial intelligence analysis of
immune impacts, the system comprising at least a computing device, wherein the
computing device comprises:
a memory; and
at least a processor communicatively connected to the memory, wherein the memory contains instructions configuring the at least a processor to: receive a behavioral datum of a user; receive a test result detecting an effect of at least the behavioral datum on at least a biomarker;
generate a machine-learning model, wherein generating the machine- learning model comprises:
receiving a first training set, wherein the first training set correlates biomarker levels to immune system function; and
training a machine-learning process as a function of the first training set to generate the machine-learning model; determine an immune system impact of the behavioral datum as a function of the at least a biomarker using the machine-learning model;
map, using the at least a processor, the immune system impact to one or more nutritional categories, wherein each nutritional category is associated with a descriptor in a standardized format, and the immune system impact is associated with the nutritional category by one or more tokens in modified training data;
model the one or more tokens as a chain such that the one or more tokens are configured to be used by a statistical model; estimate, using an inference algorithm associated with the statistical model, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category; generate a nutritional recommendation based on the mapped nutritional category and using the machine-learning model, wherein the nutritional recommendation is derived as a function of the determined immune system impact and the one or more tokens linking the immune system impact to the nutritional category; and
display, using a display device, the nutritional recommendation to the user, wherein displaying the nutritional recommendation comprises:
filtering, using the at least a processor, aliments of the nutritional recommendation using one or more elements of user data; and
modifying, using an interactive feature, the nutritional recommendation based on user input. Applicant submits that, according to MPEP 2106.04, independent claims 1 and 11, and
their dependent claims, are allowable under Step 2A and/or 2B of the eligibility analysis, as discussed further below in this paper. Step 2A, Prong one
Under Step 2A, Prong One, the Examiner states "in response to argument (1), Examiner respectfully disagrees. Examiner maintains that as drafted, under its broadest reasonable interpretation, covers the performance of a Mental Process concepts performed in the human mind. For example, all of the data receiving limitations can be retrieved manually (e.g. retrieve/receive... behavioral datum, test results, training sets, etc.). In addition, determining an immune system impact, generating, modifying, filtering and displaying a recommendation, mapping data points and displaying results are all method able to be done without computer implementation." Office Action, p. 12. Applicant respectfully disagrees. Mental Processes
For Mental Processes, the MPEP states that the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.
Applicant respectfully submits that some limitations of currently amended claim 1 of "model the one or more tokens as a chain such that the one or more tokens are configured to be used by a statistical model; estimate, using an inference algorithm associated with the statistical model, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category" do not fall within the "mental process" groupings of abstract ideas.
For example, such limitations cannot be performed mentally or with pen and paper. Further, at least such limitations do not recite mental processes because they cannot be practically performed in the human mind. See MPEP 2106.04(a)(2), subsection III.A (discussing SRI Int'l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1303 (Fed. Cir. 2019)). Applicant respectfully submits that at least those limitations of amended claim 1 detailed above should be considered "additional elements" to the alleged abstract idea. Therefore, Applicant respectfully rebuts the assertion that at least some elements of claim 1 recite abstract ideas. Method for Training
Further, examples of claims that do not recite an abstract idea issued with or after the 2019 PEG are found at least in Example 39 (Method for Training a Neural Network for Facial Detection)." October Update, p. 7.
Specifically, Example 39 illustrates a patent eligible claim that recites: (Subject Matter Eligibility Examples: Abstract Ideas, pgs. 8-9)
A computer-implemented method of training a neural network for facial detection
comprising:
collecting a set of digital facial images from a database;
applying one or more transformations to each digital facial image including
mirroring, rotating, smoothing, or contrast reduction to create a modified set of
digital facial images;
creating a first training set comprising the collected set of digital facial images, the modified set of digital facial images, and a set of digital non-facial images;
training the neural network in a first stage using the first training set;
creating a second training set for a second stage of training comprising the first training set and digital non-facial images that are incorrectly detected as facial
images after the first stage of training;
and training the neural network in a second stage using the second training set. The Explanation in the Guidance states:
The claim does not recite any of the judicial exceptions enumerated in the 2019 PEG. For instance, the claim does not recite any mathematical relationships, formulas, or calculations. While some of the limitations may be based on mathematical concepts, the mathematical concepts are not recited in the claims.
Further, the claim does not recite a mental process because the steps are not practically performed in the human mind. Finally, the claim does not recite any method of organizing human activity such as a fundamental economic concept or managing interactions between people. Thus, the claim is eligible because it does not recite a judicial exception._(Id. at pg. 9, Emphasis Added.).
Further, the USPTO recently clarified the difference between claims that "recite" an abstract idea and claims that just "involve" an abstract idea in a Memorandum to Technology Center 3600. USPTO, Memorandum to Tech. Centers 2100, 2600, and 3600 (August 4, 2025).
Applicant respectfully submits that some of the limitations of claim 1 detailed above are substantially analogous to those of Example 39 because, like Example 39 that utilizes a first training data set and a second training data set based on the first one to iteratively training a neural network, the steps recited in amended claim 1 disclose "receiving a first training set, wherein the first training set correlates biomarker levels to immune system function; and training a machine-learning process as a function of the first training set to generate the machine-learning model." Further, analogous to Example 39, claim 1 does not recite any mathematical relationships, formulas, or calculations.
Applicant respectfully submits that at least those limitations of amended claim 1 detailed above should be considered "additional elements" to the alleged abstract idea. Therefore, Applicant respectfully rebuts the assertion that at least some elements of claim 1 recite abstract ideas.
Step 2A, Prong two
The Office asserts that "the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology and their collective functions merely provide a conventional computer implementation of the abstract idea. Furthermore, the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generally linking the abstract idea to a particular technological environment or field of use, as the courts have found in Parker v. Flook. Therefore, there are no limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception." Office Action p 13.
Applicant respectfully submits that, at least as amended, representative claim 1 incorporates the alleged abstract idea into a practical application.
First, and as noted above, Applicant respectfully submits that some limitations of
currently amended claim 1 of "model the one or more tokens as a chain such that the one or more tokens are configured to be used by a statistical model; estimate, using an inference algorithm associated with the statistical model, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category" and "receiving a first training set, wherein the first training set correlates biomarker levels to immune system function; and training a machine-learning process as a function of the first training set to generate the machine-learning model" do not fall within the "mental process" groupings of abstract ideas.
Second, Applicant respectfully submits, that the claims have to be considered "as a whole" for Step 2A, Prong Two as noted in the Memorandum to Technology Center 3600. USPTO, Memorandum to Tech. Centers 2100, 2600, and 3600 (August 4, 2025).
Thirdly, a claim reciting an abstract idea is not directed to that abstract idea if incorporates the abstract idea in a practical application. MPEP 2106.04(d) "A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception." Id."In determining the eligibility of respondents' claimed process for patent protection under § 101, their claims must be considered as a whole." Diamond v. Diehr, 450 U.S. 175, 188 (1981). Therefore, the question is whether the claims as a whole "focus on a specific means or method that improves the relevant technology or are instead directed to a result or effect that itself is the abstract idea and merely invoke generic processes and machinery". McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314 (Fed. Cir. 2016).
The July 2024 Guidelines teach that integration of a judicial exception into a practical application may be achieved when "[(1)] the specification . .. set[s] forth an improvement in the technology[;] and[, (2)] the claim ... reflect[s] the disclosed improvement" (July 2024 Subject Matter Eligibility Guidelines, p. 12). The July 2024 Guidelines show that Example 47 claim 3 integrates the judicial exception into a practical application because (1) the specification teaches an improvement to network security "by acting in real time to proactively prevent network intrusions"; and (2) "[t]he claimed invention reflects this improvement in the field of network intrusion detection". (July 2024 Subject Matter Eligibility Guidelines, p. 12).
Specific examples of claims that are eligible under 35 U.S.C. § 101 are found in at least Example 47 (Artificial Neural Network for Anomaly Detection - claim 1 and 3) presented with the July 2024 Subject Matter Eligibility Update. Example 47 illustrates the application of the eligibility analysis to claims that recite limitations specific to artificial intelligence, particularly the use of an artificial neural network to identify or detect anomalies.
With reference to Example 47 and claim 3, the July 2024 Subject Matter Eligibility Update states with respect to (1) above: "according to the background section, existing systems use various detection techniques for detecting potentially malicious network packets and can alert a network administrator to potential problems. The disclosed system detects network intrusions and takes real-time remedial actions, including dropping suspicious packets and blocking traffic from suspicious source addresses. The background section further explains that the disclosed system enhances security by acting in real time to proactively prevent network intrusions". (July 2024 Subject Matter Eligibility Guidelines, p. 12).
Here, analogously to Example 47, at least the limitations of currently amended claim
1 integrate the judicial exception into a practical application because (1) the specification teaches a technological improvement.
The technical problem addressed by the disclosed system is how to provide for more accurate and efficient data analysis.
The disclosed system applies any alleged abstract idea in a concrete and practical way to make improvements in the field of optimizing data analysis in heterogenous environments with large volumes of complex data and interactions:"...complexity and variability of the subject matter. A vast multiplicity of factors to be measured is further complicated by a complex web of subtle but crucial interactions." See paragraph [0002].
For example, in the disclosed system "in an alternative or additional approach, sequential tokens may be modeled as chains, serving as the observations in a Hidden Markov Model (HMM). HMMs as used herein are statistical models with inference algorithms that that may be applied to the models. In such models, a hidden state to be estimated may include an association between an extracted word category of physiological data, a given relationship of such categories to prognostic labels, and/or a given category of prognostic labels. There may be a finite number of category of physiological data, a given relationship of such categories to prognostic labels, and/or a given category of prognostic labels to which an extracted word may pertain; an HNIM inference algorithm, such as the forward backward algorithm or the Viterbi algorithm, may be used to estimate the most likely discrete state given a word or sequence of words." See paragraph [0019].
These technical operations reflect an accurate and performance-driven system that would not be practically achievable by human effort alone.
The claimed system models one or more tokens as a chain such that the one or more tokens are configured to be used by a statistical model. Further, the claimed system uses an inference algorithm to estimate a discrete state associated with the one or more token in accordance with a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category. The system is adaptable particularly in environments where input data is e.g., heterogenous, dynamic and complex in nature (e.g., size) and where associations are typically not directly observable (hidden). The system further allows for optimized accuracy of input into subsequent operations, such as, the generation and display of a nutritional recommendation. Disclosed is a data-driven system that allows for actions to be performed more accurately and in order to maximize outcomes associated with the system.
Applicant respectfully submits that at least the limitations of currently amended claim 1 integrate the judicial exception into a practical application because the specification teaches a number of technological improvements as detailed above.
Analogously to Example 47, at least the limitations of currently amended claim 1 integrate the judicial exception into a practical application because (2) the claimed invention reflects the improvements described above in the field of optimizing data analysis in heterogenous environments with large volumes of complex data and interactions.
At least the following limitations of currently amended claim 1 reflect the technical
improvements detailed above in the technical field of optimizing data analysis in heterogenous environments with large volumes of complex data and interactions: "model the one or more tokens as a chain such that the one or more tokens are configured to be used by a statistical model; estimate, using an inference algorithm associated with the statistical model, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category."
At least the limitations of currently amended claim 1 provide for a robust system that allows for more accurate and more efficient data analysis in order to optimize subsequent processing and decision-making operations.
Further, at least the limitations of currently amended claim 1 detailed above reflect the technological improvements to the technical problems described in the background (how to increase accuracy and efficiency of data analysis techniques in environments where the data (and subject matter) is complex, variable and there is a multiplicity of factors to be measured) and when considered in combination, integrate the abstract idea into a practical application because the claim improves the functioning of a computer or technical field. See MPEP 2106.04(d)(1) and 2106.05(a). The claimed invention reflects this improvement in the technical field of optimizing data analysis in heterogenous environments with large volumes of complex data and interactions.
Thus, applicant respectfully submits that the claim as a whole integrates the judicial exception into a practical application (Step 2A, Prong Two: YES), such that the claim is not directed to the judicial exception. (Step 2A: NO).
In light of this, Applicant submits claim 1, as amended, integrates any alleged abstract
idea into a practical application and is thus patentable. Claim 11 has been similarly amended and is patentable for at least the reasons discussed above for claim 1.
Sten 2B
In view of the above arguments presented with respect to Step 2A, the Step 2B analysis of the Examiner stands moot. Applicant submits that representative claim 1, as amended, amounts to significantly more than the judicial exception under step 2B and the Office Action has not shown otherwise.
The Office asserts that under Step 2B "the claims lack limitations that are indicative of an inventive concept (aka "significantly more"). The claimed limitations must include one or more of an improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a); applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b); effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c); applying or using 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 more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo; and/or adding a specific limitation other than what is well-understood, routine, conventional activity in the field - see MPEP 2106.05(d)." Office Action p. 13.
Applicant respectfully disagrees and submits that at least the limitations of claim 1 as amended, which the Office has not yet considered: “model the one or more tokens as a chain such that the one or more tokens are configured to be used by a statistical model; estimate, using an inference algorithm associated with the statistical model, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category" recite additional elements that amount to significantly more than the judicial exception (i.e., inventive concept).
Firstly, at least the limitations of claim 1 as amended recite meaningful limits on
practicing the abstract idea. Further, this can be evidenced at least by the "practical application" analysis presented above in connection with Prong 2 of Step 2A.
Applicant further respectfully asserts that at least the limitations of claim 1 as amended amount to an inventive concept, and thus "significantly more" than any alleged abstract idea recited therein. "The second step of the Alice test is satisfied when the claim limitations "involve more than performance of 'well-understood, routine, [and] conventional activities previously known to the industry."' Berkheimer v. HP, Inc., 881 F.3d 1360, 1367 (Fed. Cir. 2018) (citation omitted). Here, at least the limitations of claim 1 as amended recite the use of technical features associated with a system for more accurate and efficient data analysis in order to optimize subsequent processing and decision-making operations.
The above recited limitations, including at least the limitations claim 1 as amended, are not generic and instead recite a novel approach comprising "model the one or more tokens as a chain such that the one or more tokens are configured to be used by a statistical model; estimate, using an inference algorithm associated with the statistical model, a discrete state associated with the one or more tokens given a sequence associated with the chain in order to determine a most likely association of the immune system impact and the nutritional category."
Applicant respectfully submits that no court cases, literature, or references are of record indicating that the above-described limitations are "well-understood, routine, [and] conventional," and furthermore asserts that neither the instant application nor the prosecution history in this matter contains any admission thereof.
Further, claim 1 has features that amount to significantly more than the abstract idea,
because such features provide a technical contribution to the field of optimizing data analysis in heterogenous environments with large volumes of complex data and interactions, which differs from conventional systems that do not achieve the desired level of robustness, accuracy and speed in environments that are complex in nature and which process large volumes of heterogeneous data (see paragraph [0002]).
Accordingly, Applicant respectfully submits that at least the limitations of claim 1 as
amended are not "well-understood, routine, [and] conventional," and thus amount to an inventive concept.
Additionally, Applicant respectfully submits that claim 11 recites an inventive concept, at least because amended claim 11 contains limitations amounting to a non-conventional and non- generic arrangement of process steps. See BASCOM Glob. Internet Servs., Inc. v. AT&T Mobility, LLC, 827 F.3d 1341, 1350 (Fed. Cir. 2016). "Examiners should keep in mind that the courts have held computer-implemented processes to be significantly more than an abstract idea (and thus eligible), where generic computer components are able in combination to perform functions that are not merely generic." May 4th USPTO Memorandum at p. 4; see also DDR Holdings, 773 F.3d at 1257. Moreover, "an inventive concept may be found in the non-conventional and non-generic arrangement" even of generic computer operations on a generic computing device. Bascom, 827 F.3d at 1350. Without conceding that any limitation of claim 11 is generic or conventional, Applicant respectfully asserts that, taken as a whole, limitations to claims 11 amount to a non-conventional and non-generic arrangement of computer and functions and other technical limitations, because the instant Application does not contain any information to suggest that the elements and/or the combination thereof are conventional. There is no evidence to indicate that at least the limitations of amended claim 11 is conventional, and Applicant does not admit that the elements and/or their combination are conventional. Applicant therefore respectfully submits that claim 11 as amended recites limitations amounting to an inventive concept, and thus to significantly more than the abstract idea to which claim 11 is allegedly drawn. At least for these additional reasons, Applicant respectfully submits claim 11 recites patent eligible subject matter.
Claims 2-10 and 12-20 depend, directly or indirectly, on claims 1 or 11 and thus recite all the same elements as claim 1 or claim 11. Applicant therefore submits claims 2-10 and 12-20 overcome these rejections for at least the same reasons as discussed above with reference to amended claims 1 and 11.
In response to argument (1), Examiner has considered Applicant’s arguments in view of the presently amended system and method claims, but respectfully maintains that the claims still do not overcome the rejection under 35 U.S.C. § 101. While the amendments add further algorithmic detail, including token chaining and statistical inference, the claims as a whole remain directed to a judicial exception and do not integrate that exception into a practical application, nor do they recite an inventive concept.
Under Step 2A, Prong One, Examiner maintains that both the system and method claims are directed to an abstract idea, specifically mental processes and mathematical concepts implemented on a generic computer. The claims focus on receiving user behavioral data and biomarker test results, analyzing correlations between those inputs, classifying immune impacts into nutritional categories, and generating and presenting a nutritional recommendation. This is fundamentally an information-processing and advisory workflow that mirrors human reasoning performed by a nutrition or health professional (i.e., reviewing test results, assessing immune impact, categorizing dietary needs, and recommending nutrition). The additional recitations of machine-learning models, token chains, statistical models, and inference algorithms describe mathematical and probabilistic techniques for performing those evaluations. As such, these limitations fall within the abstract idea groupings identified in MPEP § 2106.04(a), including mental processes and mathematical concepts, even though they are implemented at scale on a computer.
Applicant’s emphasis on the limitations involving “modeling the one or more tokens as a chain” and “estimating a discrete state using an inference algorithm” is not persuasive. These steps are still directed to abstract mathematical reasoning (i.e., probabilistic modeling, classification, and inference) and are used here solely to automate the underlying abstract task of mapping health data to recommendations. The Federal Circuit has consistently held that claims do not escape abstraction merely because they recite sophisticated algorithms or techniques that are impractical to perform mentally; rather, the inquiry concerns whether the claim is directed to abstract reasoning itself. Here, the statistical modeling and inference are in service of an abstract evaluative goal and therefore do not remove the claim from the abstract idea category.
Turning to Step 2A, Prong Two, Examiner is not persuaded that the amended claims integrate the judicial exception into a practical application. Although the claims now recite more detailed analytical steps, they do not reflect a specific technological improvement to computer functionality, machine-learning technology, or data-processing techniques. The claims do not recite how the machine-learning model is improved, how inference accuracy is increased, how computational efficiency is enhanced, or how the claimed techniques solve a technical problem in computer science itself. Instead, the claims apply known machine-learning and statistical techniques to a particular field of use (i.e., nutritional and immune health) to achieve the abstract result of a personalized recommendation. Under MPEP § 2106.05(f), this constitutes merely using machine learning as a tool to implement an abstract idea, rather than integrating the abstract idea into a practical application that meaningfully limits the exception.
The Examiner further notes that the recited output (i.e., filtering aliments, modifying recommendations based on user input, and displaying results) constitutes post-solution activity that does not impose a meaningful limitation on the abstract idea. These steps simply present the outcome of the abstract analysis to the user and allow routine interaction, which courts have consistently found insufficient to confer eligibility. Unlike the claims in USPTO Example 47, which were eligible due to reciting concrete, real-time actions that altered network operation and improved network security, the present claims do not affect any comparable technical action or improvement. The claims end with informational output rather than a technological transformation.
Proceeding to Step 2B, the Examiner maintains that the claims lack an inventive concept. The computing device, processor, memory, machine-learning model, statistical model, and inference algorithm are all recited at a high level of generality and perform their conventional functions of data storage, processing, analysis, and display. The ordered combination of these elements does not reflect a non-conventional or non-generic arrangement comparable to those found eligible in cases such as BASCOM. Applicant has not provided evidence that the claimed use of token chains and inference algorithms in this context is anything other than well-understood, routine, and conventional in the fields of data analytics and machine learning. The mere inclusion of additional algorithmic detail does not, by itself, establish an inventive concept absent a claimed improvement to the technology itself.
In summary, even when considered in light of the amended system and method claims, the Examiner finds that the claims remain directed to the abstract idea of analyzing health-related data to generate a nutritional recommendation. The recited artificial intelligence and statistical modeling features are used in a conventional manner to carry out that abstract idea and do not integrate it into a practical application or provide significantly more. Accordingly, the rejection under 35 U.S.C. § 101 is maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to EDWARD B WINSTON III whose telephone number is (571)270-7780. The examiner can normally be reached M-F 1030 to 1830.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/E.B.W/ Examiner, Art Unit 3683
/ROBERT W MORGAN/ Supervisory Patent Examiner, Art Unit 3683