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 .
Status of Claims
This action is in reply to Applicant’s communication filed on October 10, 2025.
Claims 1, 11 and 20 have been amended and are hereby entered.
Claims 1-20 are currently pending and have been examined.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 October 10, 2025 has been entered.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites the limitation “detecting one of the anticipated user states during execution of the recommended treatment plan”. Applicant’s specification does not provide sufficient support regarding what the different user states may or may not be, and further how the user states are detected or determined. Examiner notes that paragraph 62 of Applicant’s specification describes providing use instructions based on an assumption that the user will potentially experience higher pain than normal, an extra stressful situation, etc. However, Applicant’s specification does not show sufficient support for what the “anticipated user states” entail, nor how they are detected by the claimed system.
Claims 11 and 20 recite substantially similar limitations to those in claim 1 and are rejected on the same basis as stated above. Claims 2-10 and 12-19 are further rejected as being dependent on a rejected base claim.
Claim Rejections - 35 USC § 112(b)
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 1-20 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.
Claim 1 recites the limitation “generating a set of state-contingent product-use instruction variants for anticipated user states including at least increased pain and increased stress and, responsive to detecting one of the anticipated user states during execution of the recommended treatment plan, automatically updating product-use instructions in real time using a corresponding pre-generated variant;”. It is unclear to the Examiner as to what “a corresponding pre-generated variant” entails. For example, is the pre-generated variant corresponding to the recommended treatment plan, or the product-use instructions? Examiner interprets the limitation “automatically updating product-use instructions in real time using a corresponding pre-generated variant”, using broadest reasonable interpretation, to mean that the pre-generated variant is associated with/referring to the appropriate product-use instructions for the detected anticipated user state (see also Applicant’s specification para 62 for support). Examiner suggests amending the claim in such a way that clearly ties the corresponding pre-generated variant back to the detected anticipated user state. For example, for better clarity, the claim may be amended to recite “automatically updating product-use instructions in real time using a corresponding pre-generated variant associated with the detected anticipated user state”. Appropriate clarification and/or correction are required.
Further, Claim 1 recites the limitation “detecting one of the anticipated user states during execution of the recommended treatment plan”. Examiner poses the following questions regarding the clarity of the identified limitation: (1) what are the different anticipated user states? and (2) how is the system detecting different anticipated user states during the execution of the recommended treatment plan? As discussed above in the 112(a) rejection to claim 1, the Applicant’s specification lacks sufficient support for this limitation. Examiner suggests amending the claim in such a way that addressees these questions posed by the Examiner. Appropriate clarification and/or correction are required.
Further, Claim 1 recites the limitation "the regime recommendation model" on page 3, line 4. There is insufficient antecedent basis for this limitation in the claim. Appropriate correction is required.
Claims 11 and 20 recite substantially similar limitations to those in claim 1 and are rejected on the same basis as stated above. Claims 2-10 and 12-19 are further rejected as being dependent on a rejected base claim.
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 an abstract idea without significantly more.
Step 1 analysis:
Claims 1, 11 and 20 are each directed to a method, a system, and a manufacture respectively and therefore all fall into one of the four statutory categories. (Step 1: Yes, the claims fall into one of the four statutory categories).
Step 2A analysis - Prong one:
The substantially similar independent method, system, and computer readable media claims, taking claim 1 as exemplary, recite the following: A method comprising: generating a machine learning platform coupled to a communication network by creating connections between a first machine learning model and a second machine learning model, wherein the first machine learning model comprises a first group of probability weightings and the second machine learning model comprises a second group of probability weightings; obtaining a user profile dataset comprising voice notes associated with a user; providing the user profile dataset to the first machine learning model, wherein the first machine learning model is trained to diagnose users by generating probabilistic values for maladies based on user profiles of the users; generating, based on the first machine learning model and the user profile dataset of the user, a plurality of probabilistic values respectively associated with a plurality of maladies of the user, each probability value indicating a probability the user has the malady, wherein generating the plurality of probabilistic values comprises: analyzing the voice notes to determine a tone of the user; determining, based on the tone, a current stress level of the user, and determining changes in stress level of the user based on a comparison of the current stress level and a plurality of historical levels of the user that are associated with a plurality of historical treatment plans; selecting, based on the plurality of probabilistic values, the second machine learning model from a set of machine learning models respectively trained to predict cannabis treatment responses for a particular malady of the plurality of maladies; selecting one or more cannabis products by an inventory model that: (a) selects a dispensary nearest to the user that matches a medical-card status of the user; (b) filters out products containing allergens listed in the user profile dataset and products belonging to forms that the regimen recommendation model assigned a zero probability; and (c) converts each candidate product dose from a first format to a second format corresponding to discrete product portions; generating, by a processing device, a recommended treatment plan for using the one or more cannabis products to treat the particular malady of the user based on the user profile dataset and the second machine learning model by matching the cannabis treatment responses to physician recommendations; generating a set of state-contingent product-use instruction variants for anticipated user states including at least increased pain and increased stress and, responsive to detecting one of the anticipated user states during execution of the recommended treatment plan, automatically updating product-use instructions in real time using a corresponding pre-generated variant; transmitting the recommended treatment plan to a client device to cause the client device to display the recommended treatment plan; and improving an accuracy of the machine learning platform by updating the connections between the first machine learning model and the second machine learning model, the first group of probability weightings, and the second group of probability weightings based on the changes in stress level of the user; performing parameter estimation to update the first group of probability weightings and the second group of probability weightings based on a patient-success node that aggregates user well-being and activities-of-daily-living metrics; and performing parameter updating to modify internal connections within the first machine learning model and the second machine learning model based on the patient- success node.
The examiner is interpreting the above bolded limitations as additional elements as further discussed below. The remaining un-bolded limitations above, as drafted, is a process that, under the broadest reasonable interpretation, covers performance of the limitation in the mind but for recitation of generic computer components. That is, other than reciting a method implemented by a processor and the use of machine learning models, nothing in the claim precludes the step from practically being performed in the mind. For example, but for the method implemented by the processor, this claim encompasses a person listening to a patient’s voice to determine their pain and stress levels, recognizing conceptual connections between patient data, recommending a treatment plan and adjusting the evaluation based on changes in the patients pain and stress level in the manner described in the identified abstract idea, supra. 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.
Examiner notes that the “connections” are being interpreted, using broadest reasonable interpretation, as logical or conceptual connections.
The limitations above, as drafted, is a process that, under the broadest reasonable interpretation, covers certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions) but for recitation of generic computer components. That is, other than reciting a method implemented by a processing device (computer), the claimed invention amounts to managing personal behavior or interaction between people. For example, but for the identified/bolded limitations above, this claim encompasses a person interviewing a patient, determining possible maladies and stress level of the patient, determining and then recommending a treatment plan for the patient and updating the treatment plan as new data becomes available in the manner described in the identified abstract idea, supra. The Examiner notes that certain “method[s] of organizing human activity” includes a person’s interaction with a computer (see MPEP 2106.04(a)(2)(II)). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The types of identified abstract ideas are considered together as a single abstract idea for analysis purposes. (Step 2A – Prong 1: Yes, the claims are abstract).
Step 2A analysis - Prong two:
Claims 1, 11 and 20 recite additional elements beyond the abstract idea. Claims 1, 11 and 20 recite a machine learning platform, a first and a second trained machine learning model, a set of trained machine learning models, a processing device, a client device, an inventory model, a regime recommendation model and a communication network. Claim 11 further recites a memory. Claim 20 further recites non-transitory computer-readable storage medium, instructions and a host system. The instructions appear to be software.
This judicial exception is not integrated into a practical application. In particular, the claims recite a processing device, a client device, an inventory model, a regime recommendation model, a communication network, a memory, non-transitory computer-readable storage medium, instructions and a host system which are recited at a high-level of generality (i.e., as a generic processor performing generic computer functions) such that it amounts to no more than mere instructions to apply the exceptions using a generic computer component. For example, Applicant’s specification explains that the processing device receives inputs, executes instructions, analyzes data, transmits results, causes information to be displayed, etc. (see Applicant’s specification pages 10 and 37-40). The claim further recites the additional elements of using a machine learning platform made up of a first and second trained machine learning models and a set of trained machine learning models to diagnose users and to predict cannabis treatment responses for a particular malady. This represents mere instructions to implement the abstract idea on a generic computer. Implementing an abstract idea using a generic computer or components thereof does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Alternatively, or in addition, the implementation of the trained machine learning models to diagnose users and to predict cannabis treatment responses for a particular malady merely confines the use of the abstract idea (i.e., the trained model) to a particular technological environment or field of use and thus fails to add an inventive concept to the claims. The identified additional elements equate to saying “apply it.” MPEP 2106.04(d)(I) indicates that merely saying “apply it” or equivalent to the abstract idea cannot provide a practical application.
Further, the additional elements of (1) transmitting the recommended treatment plan to a client device is being interpreted as insignificant extra-solution activity. Limitation (1) is recited at a high level of generality (i.e., as a general means of transmitting data) such that it amounts to the mere transmission of data, which is a form of extra-solution activity, and thus cannot provide a practical application or significantly more. MPEP 2106.04(d)(I) indicates that extra-solution data gathering activity cannot provide a practical application. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Therefore, Claims 1, 11, and 20 are directed to an abstract idea without practical application. (Step 2A – Prong 2: No, the additional claimed elements are not integrated into a practical application).
Step 2B analysis:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a machine learning platform, a first and a second trained machine learning model, a set of trained machine learning models, a processing device, a client device, an inventory model, a regime recommendation model, a communication network, a memory, non-transitory computer-readable storage medium, instructions and a host system to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. The collective functions appear to be implemented using conventional computer systemization. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”).
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of (1) ttransmitting the recommended treatment plan to a client device were considered extra-solution activity. This has been re-evaluated under the “significantly more” analysis and determined to be well-understood, routine, conventional activity in the field.
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity: i) receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); 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); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added)); iv) 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. See MPEP §2106.05(d)(II).
This listing is not meant to imply that all computer functions are well‐understood, routine, conventional activities, or that a claim reciting a generic computer component performing a generic computer function is necessarily ineligible. Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). On the other hand, 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. See MPEP §2106.05(d)(II) – emphasis added.
The claims are directed to an abstract idea with additional generic computer elements that do not add meaningful limitations to the abstract idea because they require no more than a generic computer to perform generic computer functions that are well-understood, routine, and conventional activities previously known in the industry.
For the next step of the analysis, it must be determined whether the limitations present in the claims represent a patent-eligible application of the abstract idea. A claim directed to a judicial exception must be analyzed to determine whether the elements of the claim, considered both individually and as an ordered combination are sufficient to ensure that the claim as a whole amounts to significantly more than the exception itself.
For the role of a computer in a computer implemented invention to be deemed meaningful in the context of this analysis, it must involve more than performance of “well-understood, routine, [and] conventional activities previously known to the industry.” Further, “the mere recitation of a generic computer cannot transform a patent ineligible abstract idea into a patent-eligible invention.”
Applicant’s specification discloses the following:
Applicant describes embodiments of the disclosure at a very high level to include the use of a wide variety of networks, processors, computing devices, storage devices, machine learning models, host systems, operating systems, busses, firmware, software, circuitry and computer-readable storage medium (see Applicant’s specification paras 26, 29-31, 98, 102-106, 114).
Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system.
In summary, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because 1) mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”) and 2) well-understood, routine, conventional activity cannot provide an inventive concept (“significantly more”). The claims do not provide an inventive concept significantly more than the abstract idea. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. (Step 2B: No, the claims do not provide significantly more).
Dependent Claims 2-10 and 12-19 further define the abstract idea that is presented in independent Claims 1 and 11 respectively, and are further grouped as certain methods of organizing human activity and are abstract for the same reasons and basis as presented above. Further, Claims 2, 6-7, 12 and 16-17 recite an additional element beyond the abstract idea. Claims 2, 6-7, 12 and 16-17 recite a third machine learning model. This additional element was analyzed the same as the machine learning models above and was found to represent mere instructions to implement the abstract idea on a generic computer and/or confine the use of the abstract idea (i.e., the trained model(s)) to a particular technological environment or field of use. Further, it is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. For example, as noted above, the Applicant’s specification indicates the use of known machine learning models. 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. Therefore, the dependent claims are also directed to an abstract idea.
Thus, Claims 1-20 are rejected under 35 U.S.C. 101 as being directed to abstract ideas without significantly more.
Relevant Prior Art of Record Not Currently Being Applied
The prior art made of record and not relied upon is considered pertinent to applicant's
disclosure.
Saribekyan (US 20170017773) discloses a method comprising steps (a) a medical cannabis patient at a geographical location using a computing device registers to access a computer network system; (b) a patient verification process is provided, wherein the patient verification process enables the system to verify a physician issued recommendation for the medical cannabis patient; (c) a first directory list is provided, wherein the first directory list comprises a first list of dispensaries, wherein the first list of dispensaries is located in proximity to the geographical location; (d) the medical cannabis patient selects a dispensary from the first list of dispensaries; and (e) a plurality of information is provided.
Bostian et al. (US 20060020220) discloses a method and system for modeling cardiovascular disease using a probability regression model is provided. A parameter estimate of a probability regression model for cardiovascular disease can be generated using predictors derived from cardiovascular sound signals and disease status information. The parameter estimates may automatically attempt to update any time additional data from one or more new subjects are received.
Clifton et al. (Clifton, S. M., Kang, C., Li, J. J., Long, Q., Shah, N., & Abrams, D. M. (2017). Hybrid statistical and mechanistic mathematical model guides mobile health intervention for chronic pain. Journal of Computational Biology, 24(7), 675–688. https://doi.org/10.1089/cmb.2017.0059) discloses prediction of both the expected pain level for a patient at any point in the future and an assessment of the confidence in (and a confidence interval for) that prediction.
Response to Arguments
Regarding rejections under 35 USC § 101 to Claims 1-20, Applicant’s arguments have been fully considered, and are not persuasive. The rejection has been updated in light of latest amendments. Applicant argues:
(a) First, the amended claims include limitations that require an inventory model to select cannabis products using a multi-factor filtering process that accounts for dispensary proximity, medical-card status, allergen avoidance, and exclusion of product forms assigned zero probability by a regimen recommendation model. This filtering logic is not a mental process or a generic computer function; it is a specific technical mechanism that ensures compliance with regulatory and medical constraints while optimizing product selection. The claims further require converting each candidate product dose from a first format to a second format, which corresponds to discrete product portions. This conversion step is a technical transformation that enables machine-generated dosage values to be expressed in actionable units for patient execution, thereby improving usability and reducing dosing errors. (p. 12-13).
Regarding (a), Examiner respectfully disagrees. MPEP 2106.04(d)(1) and MPEP 2106.05(a) indicates that a practical application may be present where the claimed invention provides a technical solution to a technical problem. See, e.g., DDR Holdings, LLC. v. Hotels-com, L.P., 773 F.3d 1245, 1259 (Fed. Cir. 2014) (finding that claiming a website that retained the "look and feel" of a host webpage provided a technological solution to the problem of retention of website visitors by utilizing a website descriptor that emulated the "look and feel" of the host webpage, where the problem arose out of the internet and was thus a technical problem). Here, Applicant’s identified problems of optimizing product selection, improving usability and reducing dosing errors are interpreted as not being rooted in technology. The problems are not caused by nor related to computer technology and the claims do not provide any limitations that may be interpreted as technical improvements to computer technology. The claimed invention is using a computer as a tool and any improvement present is an improvement to the abstract idea of, to paraphrase, determining and updating treatment plans.
(b) Second, the claims recite generating a set of state-contingent product-use instruction variants for anticipated user states, such as increased pain or stress, and automatically updating product-use instructions in real time when such states are detected. This dynamic adaptation is a technical improvement over static care plans because it enables the system to respond to changing conditions without requiring manual intervention. The real-time update mechanism imposes meaningful limits on the claim scope and demonstrates integration into a practical application. (p. 13).
Regarding (b), Examiner respectfully disagrees. MPEP 2106.04(d)(1) states "the word 'improvements' in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B." Here there is no improvement to the computer nor is there an improvement to another technology. Because neither type of improvement is present in the claims, an improvement to technology is not present and there is no practical application. Further, the stated problems of static care plans are interpreted as not being rooted in technology. The problems are not caused by nor related to computer technology and the claims do not provide any limitations that may be interpreted as technical improvements to computer technology. The claims do not reflect a technical improvement but rather are confined to a general-purpose computer.
(c) Third, the claims now include parameter estimation and parameter updating based on a patient-success node that aggregates user well-being and activities-of-daily-living metrics. These steps are not generic retraining; they represent a specific algorithmic improvement to the machine learning platform itself by optimizing probability weightings and internal model connections using outcome-driven metrics. This improvement enhances the accuracy and reliability of the platform over time. (p. 13).
Regarding (c), Examiner respectfully disagrees. MPEP 2106.04(d)(1) states that a practical application may be present where the claimed invention improves the functioning of a computer. See also MPEP2106.05(a)(I). The technological environment of Applicant’s claim is a general-purpose computer (see Applicant’s Spec. Paras 26, 31, 98, 102-104). Applicant has not identified nor can the Examiner locate any physical improvement to the functioning of the computer that results from the implementation of Applicant’s claim. There is no indication that the computer is made to increase accuracy or reliability over time. In fact, the computer may be caused to operate less efficiently through the implementation of Applicant’s claimed invention; we do not know. Because there is no improvement to the functioning of the computer itself, a practical application is not present.
Regarding rejections under 35 USC § 103 to Claims 1-20, Applicant’s arguments have been fully considered and are persuasive regarding the combination of the newly added limitations. Therefore, the Examiner has withdrawn the rejection under 35 USC § 103 to claims 1-20.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIMBERLY VANDER WOUDE whose telephone number is (703)756-4684. The examiner can normally be reached M-F 9 AM-5 PM.
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/K.E.V./Examiner, Art Unit 3681
/PETER H CHOI/Supervisory Patent Examiner, Art Unit 3681
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