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 .
Status of the Claims
Claims 1-4, 6-16, and 18-20 are currently pending. Claims 5 and 17 are canceled in the Claims filed on November 5, 2025.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 November 5, 2025 has been entered.
Claim Objections
Claim 7 is objected to due to the following informalities: Claim 7 is indicated as “previously presented” despite including amended language. This appears to be a typographical error, and in the interest of compact prosecution, Examiner will interpret Claim 7 as “currently amended.”
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-4, 6-16, and 18-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claims 1, 10, and 20, Claims 1, 10, and 20 recite “the one or more digital phenotypes comprising features computed from wearable sensor signals and features computed from the live video raw data.” It is unclear if the aforementioned “wearable sensor signals” refer to different data than the second plurality of data comprising “one or more physiological inputs from the first user when the at least one wearable electronic device is worn by the first user,” which is recited earlier in Claims 1, 10, and 20. Additionally, it is unclear if the “wearable sensor” refers to a different device than the “wearable electronic device,” which is recited earlier in Claims 1, 10, and 20 as the device used to obtain the second plurality of data. In the interest of compact prosecution, Examiner will interpret the “wearable sensor signals” as the second plurality of data obtained from the at least one wearable electronic device. Appropriate correction is required.
Dependent Claims 2-4, 6-9, 11-16, and 18-19 are also rejected under 35 U.S.C. 112(b) due to their dependence from independent Claims 1, 10, and 20.
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 1-4, 6-16, and 18-20 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.
Step 1
Claims 1-4, 6-16, and 18-20 are within the four statutory categories. Claims 1-4 and 6-9 are drawn to a method for clinical recommendations, which is within the four statutory categories (i.e. process). Claims 10-16 and 18-19 are drawn to a system for clinical recommendations, which is within the four statutory categories (i.e. machine). Claim 20 is drawn to a non-transitory medium for clinical recommendations, which is within the four statutory categories (i.e. manufacture).
Prong 1 of Step 2A
Claim 1, which is representative of the inventive concept, recites: A method comprising:
providing, with at least one application server, a first instance of an end user application to a mobile electronic device associated with a first user, wherein the first instance of the end user application comprises a first graphical user interface configured for the first user, the first graphical user interface comprising one or more interface elements associated with evaluation or management of an autoimmune condition of the first user;
providing, with the at least one application server, a second instance of the end user application to a client device associated with a second user, wherein the second instance of the end user application comprises a second graphical user interface configured for the second user, the second graphical user interface comprising one or more interface elements associated with the evaluation or management of the autoimmune condition of the first user;
receiving, via an input device of the mobile electronic device, a first plurality of data comprising one or more user-generated inputs from the first user corresponding to the autoimmune condition of the first user;
receiving, with at least one wearable electronic device communicably engaged with the mobile electronic device, a second plurality of data comprising at least one physiological measurement from the first user, wherein the at least one wearable electronic device comprises at least one physiological sensor configured to measure one or more physiological inputs from the first user when the at least one wearable electronic device is worn by the first user;
receiving, via the first instance of the end user application or the second instance of the end user application, a third plurality of data via a live video feed between the first user and the second user;
wherein the first instance of the end user application or the second instance of the end user application is configured to automatically convert data from the live video feed to a raw data format to comprise the third plurality of data;
receiving, with the at least one application server via at least one communications network, the first plurality of data, the second plurality of data, and the third plurality of data;
receiving, with the at least one application server, a fourth plurality of data comprising at least one of electronic medical record (EMR) data, laboratory information management system (LIMS) data, or conversational data between the first user and a health coach;
for each record of the first, second, third, and fourth pluralities of data, associating the record with a patient specific identifier and time of capture metadata and storing the associated record in a data store;
synchronizing the stored records based on the time of capture metadata to create a time indexed analytical record spanning a first time period;
deriving one or more digital phenotypes from at least the second and the third pluralities of data, the one or more digital phenotypes comprising features computed from wearable sensor signals and features computed from the live video raw data;
analyzing, with a processor of the at least one application server, the time indexed analytical record using at least one machine learning model comprising one or more artificial neural networks configured to jointly process the first, second, third, and fourth pluralities of data to compute a flare prediction index corresponding to a current or future state of the autoimmune condition of the first user,
generating, with the processor of the at least one application server, an output comprising the flare prediction index as at least one diagnostic measure of the current or future state of the autoimmune condition of the first user;
generating, with the processor of the at least one application server, at least one activity recommendation in response to the flare prediction index, wherein the at least one activity recommendation corresponds to at least one patient outcome associated with the current or future state of the autoimmune condition of the first user;
providing, with the at least one application server via the at least one communications network, the at least one activity recommendation to the first user via the first instance of the end user application; and
providing, with the at least one application server via the at least one communications network, the flare prediction index and the at least one activity recommendation to the second user via the second instance of the end user application.
The underlined limitations as shown above, given the broadest reasonable interpretation, recite the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and/or following rules or instructions – in this case, the receiving of the first, second, third, and fourth data, the conversion of the raw data to the third data, associating the first, second, third, and fourth data with a patient identifier and timing, the creation of the time indexed analytical record, deriving the one or more digital phenotypes, analyzing the time indexed analytical record, computing the flare prediction index, generating and outputting the flare prediction index as a diagnostic measure, generating the activity recommendation in response to the flare prediction index, providing of the activity recommendation to a first user, and the providing of the flare prediction index to a second user recite following rules or instructions in order to manage diagnosing and treating a patient), e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea are deemed “additional elements,” and will be discussed in further detail below.
Furthermore, the abstract idea for Claims 10 and 20 is identical as the abstract idea for Claim 1, because the only difference between Claims 1, 10, and 20 is that Claim 1 recites a method, whereas Claim 10 recites a system, and Claim 20 recites a non-transitory computer readable medium.
Dependent Claims 2-4, 6-9 and 11-16, and 18-19 include other limitations, for example Claim 2 recites receiving an input comprising a clinical recommendation from the second user, Claims 3 and 15 recite that the clinical recommendation comprises a dosage and timing of various types of medication, Claims 4 and 16 recite types of activity recommendations, Claims 5 and 17 recite types of diagnostic measures of the current or future state of the autoimmune condition, Claims 6-7 and 12-13 recite receiving conversational data between the patient and a health coach and utilizing the conversational data to generate the diagnostic measure, Claims 8-9 and 18-19 recite utilizing the first, second, and third data to determine the efficacy of the activity or clinical recommendation and communicating the efficacy to the provider, Claim 11 recites types of users, and Claim 14 recites receiving patient reported outcomes in response to activity recommendations, but these only serve to further narrow the abstract idea, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, e.g. see MPEP 2106.04, and/or do not further narrow the abstract idea and instead only recite additional elements, which will be further addressed below. Hence dependent Claims 2-4, 6-9 and 11-16, and 18-19 nonetheless recite the same abstract idea as independent Claims 1 and 10.
Hence Claims 1-4, 6-16, and 18-20 recite the aforementioned abstract idea.
Prong 2 of Step 2A
Claims 1, 10, and 20 are not integrated into a practical application because the additional elements (i.e. the non-underlined limitations above – in this case, the hardware elements including the server, the data store, the mobile electronic device, the wearable electronic device, and the communications network, the machine learning model, the steps of providing of the first and second end user applications, and the live video feed) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of the aforementioned hardware elements, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see pg. 26, line 13 through pg. 27, line 6, and pg. 28, lines 5-12 of the present Specification, see MPEP 2106.05(f);
generally link the abstract idea to a particular technological environment or field of use – for example, the claim language reciting that the interface elements are associated with evaluation or management of an autoimmune condition, and the limitations of the machine learning model, which amounts to limiting the abstract idea to the field of healthcare and machine learning, see MPEP 2106.05(h); and/or
add insignificant extra-solution activity to the abstract idea – for example, providing interface elements to a user via the first and second instances of the end user application, which amounts to mere data gathering and/or an insignificant application, and the recitation of receiving the third plurality of data via a live video feed between the first and second users, which amounts to mere data gathering, see MPEP 2106.05(g).
Additionally, dependent Claims 2-4, 6-9 and 11-16, and 18-19 include other limitations, but these limitations also amount to no more than generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data being processed recited in dependent Claims 2-4, 6-9, 11-16, and 18-19), and/or do not include any additional elements beyond those already recited in independent Claims 1 and 10, and hence also do not integrate the aforementioned abstract idea into a practical application.
Hence Claims 1-4, 6-16, and 18-20 do not include additional elements that integrate the judicial exception into a practical application.
Step 2B
Claims 1, 10, and 20 do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. the non-underlined limitations above – in this case, the hardware elements including the server, the data store, the mobile electronic device, the wearable electronic device, and the communications network, the machine learning model, the steps of providing of the first and second end user applications, and the live video feed), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, generally link the abstract idea to a particular technological environment or field of use, and/or add insignificant extra-solution activity to the abstract idea, wherein the additional elements comprise limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The present Specification expressly disclosing that the structural additional elements are well-understood, routine, and conventional in nature:
Pg. 26, line 13 through pg. 27, line 6, and pg. 28, lines 5-12 of the Specification discloses that the additional elements (i.e. the aforementioned hardware elements) comprise a plurality of different types of generic computing systems;
Relevant court decisions: The functional limitations interpreted as additional elements are analogized to the following examples of court decisions demonstrating well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II):
Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec – similarly, the current invention receives first and second data from the mobile electronic device and the wearable electronic device, and transmits the first and second data to the server over a network, for example the Internet, e.g. see pg. 26, lines 6-12 of the present Specification;
Electronic recordkeeping, e.g. see Alice Corp v. CLS Bank – similarly, the current invention merely recites the storing of patient data at various locations, for example at least temporarily (such that it may be transmitted) on the wearable electronic device, the mobile electronic device, on the server, and/or on the data store;
Storing and retrieving information in memory, e.g. see Versata Dev. Group, Inc. v. SAP Am., Inc. – similarly, the current invention recites storing the various patient data in on the various structural elements, receiving and storing the data on the server, and retrieving the various patient data from storage of the server in order to generate the activity recommendation and the diagnostic measure;
Dependent Claims 2-4, 6-9 and 11-16, and 18-19 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because the additional elements recited in the aforementioned dependent claims similarly amount to generally linking the abstract idea to a particular technological environment or field of use (e.g. the types of data being processed recited in dependent Claims 2-4, 6-9, 11-16, and 18-19), and/or the limitations recited by the dependent claims do not recite any additional elements not already recited in independent Claims 1 and 10, and hence do not amount to “significantly more” than the abstract idea.
Hence, Claims 1-4, 6-16, and 18-20 do not include any additional elements that amount to “significantly more” than the judicial exception.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, Claims 1-4, 6-16, and 18-20 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Subject Matter Free From Prior Art
Claims 1-4, 6-16, and 18-20 are not presently rejected under 35 U.S.C. 102 or 103, and hence would be in condition for allowance if amended to overcome the rejections presented under 35 U.S.C. 101. The following represents Examiner' s characterization of the most relevant prior art references and the differences between the present claim language and the prior art references in view of 35 U.S.C. 102 and/or 103:
With regards to 35 U.S.C. 102 and/or 103, the following represents the closest prior art to the claimed invention, as well as the differences between the prior art and the limitations of the presently claimed invention.
Op Den Buijs (US 2014/0129247) teaches a clinical interface system in communication with a clinical decision support system, wherein the clinical interface system includes a plurality of devices and enables a user to input patient data and display data to a clinical specialist. Additionally, Op Den Buijs teaches obtaining patient data from wearable sensors, and the patient data is used to determine one or more suggested treatment options/orders. Furthermore, Op Den Buijs teaches utilizing a neural network risk model engine to generate patient prediction probabilities. However, Op Den Buijs does not teach that the patient data includes a patient autoimmune condition, a particular time period for the patient data, and/or synchronizing the stored records based on the time of capture to create a time indexed analytical record utilizing the gathered types of patient data. Additionally, Op Den Buijs does not teach using the neural network risk model to generate a flare prediction index for the autoimmune condition.
Spurlock (US 2019/0108912) teaches a system that predicts patient health states and a future diagnosis for a specific disease including an autoimmune disease. However, Spurlock does not teach any of the structural limitations regarding the devices/interfaces used by patients and providers, obtaining patient data from wearable sensors, and/or generating a recommended activity based on test data. Additionally, Spurlock does not teach that the patient data includes video data.
Nguyen (US 2014/0276552) teaches receiving patient video data for a videoconference, patient responses to a questionnaire, and data from medical sensors, wherein the aforementioned data is analyzed to produce a patient report including a recommended course of treatment. However, Nguyen does not teach that the patient condition includes an autoimmune disease and/or using a machine learning model to perform any of the analysis.
Biswas (US) teaches analyzing video data obtained from a video conference to determine a patient’s mental state utilizing an artificial neural network. However, Biswas does not teach the configuration of the structural limitations regarding the devices/interfaces used by patients and providers, obtaining patient data from wearable sensors, evaluating patients for autoimmune diseases, and/or producing a flare up prediction index. Additionally, Biswas does not teach synchronizing the stored records to create a time indexed analytical record.
Hyde (US 2020/0121215) teaches determining an average value over time for a patient metric. However, Hyde does not teach the configuration of the structural limitations regarding the devices/interfaces used by patients and providers, evaluating patients for autoimmune diseases, and/or producing a flare up prediction index. Additionally Hyde does not teach synchronizing the stored records to create a time indexed analytical record.
Van Der Zaag (US 2013/0226621) teaches a system including an interface enabling a clinician to choose options for diagnostic testing for a patient, and utilizing various machine learning techniques to classify patient data. However, Van Der Zaag does not teach the configuration of the structural limitations regarding the devices/interfaces used by patients and providers, or that a patient condition includes an autoimmune condition. Furthermore, Van Der Zaag does not teach synchronizing the stored records to create a time indexed analytical record.
The aforementioned references are understood to be the closest prior art. Various aspects of the present invention are known individually, but for the reasons disclosed above, the particular manner in which the elements of the present invention are claimed, when considered as an ordered combination, distinguishes from the aforementioned references and hence the invention recited in Claims 1-4, 8-10, 12, 14, and 16-22 is not considered to be disclosed by and/or obvious in view of the inventions of the closest prior art references.
Response to Arguments
Applicant’s arguments, see Remarks, filed November 5, 2025, with respect to the rejection of Claim 2 under 35 U.S.C. 112(b) have been fully considered and, in combination with the amendments, are persuasive. The previous grounds of rejection of Claim 2 under 35 U.S.C. 112(b) has been withdrawn. However, as shown above, Claims 1-4, 6-16, and 18-20 are nonetheless rejected under 35 U.S.C. 112(b) due to the newly amended claim limitations.
Applicant’s arguments, see Remarks, filed November 5, 2025, with respect to the rejections of Claims 1-4, 6-16, and 18-20 under 35 U.S.C. 101 have been fully considered but are not persuasive.
Applicants first allege that the claimed invention is patent eligible because it is not directed towards the abstract idea of certain methods of organizing human activities, specifically because it recites a concrete, technology-centric pipeline that ingests heterogeneous data, converts them into a machine-processable format, and processes them through a neural network to determine a flare prediction index, e.g. see pg. 15 of Remarks – Examiner disagrees.
Regarding the specificity of the claimed limitations, Examiner notes that the Claims being narrowly claimed is not dispositive in determining the eligibility of the Claims. The Court has held that a claim may not preempt abstract ideas, laws of nature, or natural phenomena, even if the judicial exception is narrow, e.g. see MPEP 2106.04. That is, a claim reciting a narrow abstract idea nonetheless recites an abstract idea, and must be evaluated under the remainder of the requirements under 35 U.S.C. 101.
Applicants further allege that the claimed invention is patent eligible because it integrates any abstract idea into a practical application, specifically because it recites limitations that represent a particular machine environment and because the computation of the flare prediction index solves a computer-data problem and defines a machine-learning implementation that cannot be performed as a mental process, e.g. see pgs. 15-16 of Remarks – Examiner disagrees.
Regarding the application of the abstract idea by a particular machine, the present claim language does not provide any particularity with regards to the machine itself. For example, the language of independent Claims 1, 10, and 20 recite an “application server,” a “mobile electronic device,” an “input device of the mobile electronic device,” a “wearable electronic device” a “data store,” and a “communication network.” None of the aforementioned machine/hardware structural limitations are recited with any particularity and/or any details beyond the functions they execute. That is, an abstract idea is not integrated into a practical application merely because it recites a plurality of machine/structural limitations at a high level of generality to execute the functions of the abstract idea.
Additionally, regarding the machine-learning aspect of the claim language, as shown above, this is not characterized as part of the abstract idea. However, the recited machine-learning limitations (i.e. the “at least one machine learning model comprising one or more artificial neural networks”) that compute the flare prediction index merely recite the inputs (i.e. the first, second, third, and fourth pluralities of data) and the outputs (i.e. the flare prediction index), without providing specific details regarding the machine learning model itself beyond it comprising an artificial neural network. For example, there is no recitation of any limitations that define the artificial neural network in a way that achieves any particular technological improvement. Moreover, the additional element of the machine learning model comprising an artificial neural network may result in “determining the most optimal treatment faster, improving outcomes and reducing organ damage in patients,” e.g. see lines 18-19 of the as-filed Specification, but these improvements are improvements to the abstract idea of a certain method of organizing human activities and an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology, e.g. see MPEP 2106.05(a)(II).
Applicants further allege that the claimed invention is patent eligible because it recites significantly more than the abstract idea, specifically because the cited prior art references are distinguished from the claimed limitations and hence the claimed limitations are not well-understood, routine, or conventional, e.g. see pgs. 16-18 of Remarks – Examiner disagrees.
Examiner initially notes that the Claims are no longer rejected under 35 U.S.C. 102 and/or 103 for the reasons disclosed above. However, the “novelty of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the 101 categories of possibly patentable subject matter,” and specifically, lack of novelty under 35 U.S.C. 102 or obviousness under 35 U.S.C. 103 of a claimed invention does not necessarily indicate that additional elements are well-understood, routine, conventional elements. Because they are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101, e.g. see MPEP 2106.05I(I). Hence, the claimed limitations are not properly interpreted as “significantly more” than the abstract idea merely because they are distinguished from the previously cited prior art references.
For the aforementioned reasons, Claims 1-4, 6-16, and 18-20 are rejected under 35 U.S.C. 101.
Applicant’s arguments, see Remarks, filed November 5, 2025, regarding the rejections of Claims 1-4, 6-16, and 18-20 under 35 U.S.C. 103 have been considered and, in combination with the amendments, are persuasive for the reasons disclosed above. The previous rejections of Claims 1-4, 6-16, and 18-20 under 35 U.S.C. 103 are withdrawn.
Conclusion
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/JOHN P GO/Examiner, Art Unit 3681