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 .
Notice to Applicant
This communication is in response to the amendment filed 08/06/2026. Claims 1, 3, 5, 7-10 have been amended. Claims 1, 3, 5-10 are presented for examination.
Claim Objections
Claims 1, 10 are objected to because of the following informalities:
In claims 1, 10, line(s) 8, “using learning model trained” seems to be a grammatical error. Examiner recommends amending it to read -- using a learning model trained --.
Appropriate correction is required.
Subject Matter Free of Prior Art
Claim(s) 1, 3, 5-10 are allowable over prior art because the prior art of record fail to expressly teach or suggest, either alone or in combination, the features found within the independent claims, in particular: “using learning model trained based on the information stored in the individualized adverse reaction database, calculating a causality score of a causal relationship between drugs included in the prescription information and an adverse reaction indicated in the adverse reaction information, analyzing a possibility of the adverse reaction to be occurred with the drugs included in the prescription information, identifying a specific drug, among the drugs included in the prescription information, that induces the adverse reaction, and determining an alternative drug of the identified specific drug,” “calculating the causality score and the possibility based on answers to the first and second questionnaires.” Because the prior art does not teach or disclose the above features in the specific manner and combinations recited in independent claims 1, 9-10, claims 1, 9-10 are hereby deemed to be allowable over prior art. Originally numbered dependent claims 3, 5-8 incorporate the allowable features of originally numbered independent claim 1, through dependency.
However, the claims are still rejected under 101.
Claim Rejections - 35 USC § 112
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.
Claim(s) 1, 3, 5-10 is/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.
Claims 1, 10 recites “transmit the updated individualized adverse reaction database to an external server” in line 21 (claim 1). However, the specification only mentions transmitting updates and data to external servers; the specification does not describe transmitting entire databases, let alone “the updated individualized adverse reaction database to an external server.” Because no additional information is given, the disclosure fails to sufficiently describe the “transmit the updated individualized adverse reaction database to an external server” step. As such, it constitutes new matter.
Claim(s) 3, 5-9 is/are rejected as being dependent on claim 1.
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.
Claim(s) 1, 3, 5-10 is/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.
Claims 1, 10 recites “using learning model trained based on the information stored in the individualized adverse reaction database, calculating a causality score of a causal relationship between drugs included in the prescription information and an adverse reaction indicated in the adverse reaction information, analyzing a possibility of the adverse reaction to be occurred with the drugs included in the prescription information, identifying a specific drug, among the drugs included in the prescription information, that induces the adverse reaction, and determining an alternative drug of the identified specific drug” in lines 8-16 (claim 1). However, it is unclear if “using learning model trained based on the information stored in the individualized adverse reaction database,” “calculating a causality score of a causal relationship between drugs included in the prescription information and an adverse reaction indicated in the adverse reaction information,” “analyzing a possibility of the adverse reaction to be occurred with the drugs included in the prescription information, identifying a specific drug, among the drugs included in the prescription information, that induces the adverse reaction,” and “determining an alternative drug of the identified specific drug” all refer to individual steps independent of each other; or if the aforementioned “calculating,” “analyzing,” “identifying,” and “determining” are steps performed by “using learning model trained based on the information stored in the individualized adverse reaction database” (as suggested by the grouping of the steps in the same paragraph line). Appropriate clarification is requested for the proper interpretation of the claim limitations, as the ambiguity renders the metes and bounds of the claim unclear. For examination purposes, Examiner interprets the aforementioned “calculating,” “analyzing,” “identifying,” and “determining” are steps performed by “using learning model trained based on the information stored in the individualized adverse reaction database.”
Claim(s) 3, 5-9 is/are rejected as being dependent on claim 1.
Claim 9 recites both a “non-transitory computer readable recording medium… storing a program for performing the method of claim 1.” When both a manufacture and a method are claimed in the same claim, it is unclear whether infringement occurs when the manufacture is constructed or when the manufacture is used. Furthermore, the “method of claim 1” is “performed by a server” (claim 1); therefore, is the “program” stored in the “non-transitory computer readable recording medium” inherently part of the “server,” such that the program of the server is performing the method? Therefore, the scope of the claim is indefinite. See MPEP 2173.05(p).
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, 3, 5-10 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:
Claim 1 is drawn to a method which is within the four statutory categories (i.e., method). Claim 9 is drawn to a computer program stored on a computer-readable recording medium which, for purposes of compact prosecution, is presumed to be within the four statutory categories (i.e., manufacture). Claim 10 is drawn to a device which is within the four statutory categories (i.e., machine).
Independent claim 1 (which is representative of independent claims 9-10) recites receiving prescription information from a user; receiving adverse reaction information from the user; using…model trained based on the information stored…, calculating a causality score of a causal relationship between drugs included in the prescription information and an adverse reaction indicated in the adverse reaction information, analyzing a possibility of the adverse reaction to be occurred with the drugs included in the prescription information, identifying a specific drug, among the drugs included in the prescription information, that induces the adverse reaction, and determining an alternative drug of the identified specific drug; generating optimized prescription information based on the alternative drug and providing the optimized prescription information to the user; collecting feedback information after drug administration based on the optimized prescription information from the user to update the individualized adverse reaction [data]; and…wherein the method further comprises: sending a first questionnaire to the user to ask whether a symptom of the adverse reaction was included in symptoms at the time the prescription information was entered: sending a second questionnaire to the user to ask whether there was a symptom improvement a certain number of days after discontinuation of the drugs; and calculating the causality score and the possibility based on answers to the first and second questionnaires.
Under its broadest reasonable interpretation, the limitations noted above, as drafted, covers certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people…following rules or instructions), but for the recitation of generic computer components. The claims encompass a series of rules or instructions for a person or persons to follow, with or without the aid of a computer, to collect data, analyze the collected data, and provide relevant data (i.e., recommended prescription) based on the analysis accordingly in the manner described in the identified abstract idea, supra. The rules or instructions are the claimed steps as indicated supra. That is, other than reciting generic computer components (discussed infra), the claim amounts to managing personal behavior or relationships or interactions between people following rules or instructions. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships 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 claims recite an abstract idea.
Claim 1 recites additional elements (i.e., server to perform the method; storing the prescription information and the adverse reaction information in an individualized adverse reaction database; learning model trained; transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated individualized adverse reaction database for diagnosis, prescription, dispensing, or usage instructions). Claim 9 recites additional elements (i.e., A non-transitory computer readable recording medium, coupled to a computer that is hardware, and storing a program; storing the prescription information and the adverse reaction information in an individualized adverse reaction database; learning model trained; transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated individualized adverse reaction database for diagnosis, prescription, dispensing, or usage instructions). Claim 10 recites additional elements (i.e., A device…comprising: a processor; store the prescription information and the adverse reaction information in an individualized adverse reaction database; learning model trained; transmit the updated individualized adverse reaction database to an external server configured to utilize the updated individualized adverse reaction database for diagnosis, prescription, dispensing, or usage instructions). Looking to the specifications, a computer server device having a non-transitory computer readable recording medium storing a program, processor is described at a high level of generality (¶ 0026; ¶ 0037-0039; ¶ 00121), such that it amounts to no more than mere instructions to apply the exception using generic computer components. Also, the claims add “storing the prescription information and the adverse reaction information in an individualized adverse reaction database,” which only invokes the database merely as a tool in its ordinary capacity to perform an existing process (i.e., providing, storing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent), and only provides the input data for the performance of the abstract idea, and as such, amounts to insignificant extrasolution activity (i.e., mere data gathering), which does not impose meaningful limits on the scope of the claim. See: MPEP § 2106.05(g). Also, “learning model trained” is only used to generally apply the abstract idea without placing any limits on how the machine learning model functions (i.e., no details about how the function is accomplished) and only recite the outcome of the abstract idea, and thus, provide nothing more than mere instructions to implement an abstract idea on a generic computer, and merely indicates a field of use or technological environment (i.e., machine learning) in which the judicial exception is performed. See MPEP § 2106.05(f). Also, the claims add “transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated individualized adverse reaction database for diagnosis, prescription, dispensing, or usage instructions,” which only invokes the server merely as a tool in its ordinary capacity to perform an existing process (i.e., receiving, processing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent), and only provides the input data for the performance of the abstract idea, and as such, amounts to insignificant extrasolution activity (i.e., mere data gathering), which does not impose meaningful limits on the scope of the claim. See: MPEP § 2106.05(g). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea.
Reevaluated under step 2B, the additional elements noted above do not provide “significantly more” when taken either individually or as an ordered combination. The use of a general purpose computer or computers (i.e., a computer server device having a non-transitory computer readable recording medium storing a program, processor) amounts to no more than mere instructions to apply the exception using generic computer components and 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. Also, the claims add “storing the prescription information and the adverse reaction information in an individualized adverse reaction database,” which only invokes the database merely as a tool in its ordinary capacity to perform an existing process (i.e., providing, storing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent). Furthermore, receiving or transmitting data over a network, electronic recordkeeping, and storing and retrieving information in memory has been recognized by the courts as well-understood, routine, and conventional elements/functions. See: MPEP § 2106.05(d)(II). Also, “learning model trained” is only used to generally apply the abstract idea without placing any limits on how the machine learning model functions (i.e., no details about how the function is accomplished) and only recite the outcome of the abstract idea, and thus, provide nothing more than mere instructions to implement an abstract idea on a generic computer, and merely indicates a field of use or technological environment (i.e., machine learning) in which the judicial exception is performed. See MPEP § 2106.05(f). Also, the claims add “transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated individualized adverse reaction database for diagnosis, prescription, dispensing, or usage instructions,” which only invokes the server merely as a tool in its ordinary capacity to perform an existing process (i.e., receiving, processing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent). Furthermore, receiving or transmitting data over a network, electronic recordkeeping, and storing and retrieving information in memory has been recognized by the courts as well-understood, routine, and conventional elements/functions. See: MPEP § 2106.05(d)(II). 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; similarly, the current invention merely limits the claimed calculations to the healthcare industry which does not impose meaningful limits on the scope of the claim. 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 3, 5-8 include all the limitations of the parent claims and further elaborate on the abstract idea discussed above and incorporated herein.
Claims 3 further defines the analysis and organization of data for the performance of the abstract idea and do not recite any additional elements. Thus, the claims do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Claims 5-6 further recites the additional elements of “generating the learning model for extracting an adverse reaction -inducing drug and determining an alternative drug through machine learning” and “wherein the learning model is further trained to extract the adverse reaction -inducing drug and determine the alternative drug through the machine learning,” which is described at a high level of generality and is only used to generally apply the abstract idea without placing any limits on how the model actually functions (i.e., no description of the mechanism for accomplishing the result), such that using machine learning models amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., artificial intelligence), which does not impose meaningful limits on the scope of the claim. Also, functional limitations further define the analysis and organization of data for the performance of the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the claims as a whole do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Claim 7 further recites the additional elements of “using…external databases,” which is only invoked merely as a tool in its ordinary capacity to perform an existing process (i.e., providing, storing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent), and only provides the input data for the performance of the abstract idea, and as such, amounts to insignificant extrasolution activity (i.e., mere data gathering), which does not impose meaningful limits on the scope of the claim. See: MPEP § 2106.05(g). Also, functional limitations further define the analysis and organization of data for the performance of the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the claims as a whole do not integrate the abstract idea into a practical application. Reevaluated under step 2B, the additional elements noted above do not provide “significantly more” when taken either individually or as an ordered combination. Furthermore, receiving or transmitting data over a network, electronic recordkeeping, and storing and retrieving information in memory has been recognized by the courts as well-understood, routine, and conventional elements/functions. See: MPEP § 2106.05(d)(II). Thus, the claims as a whole do not provide “significantly more.”
Claim 8 further recites the additional elements of “providing at least one of the adverse reaction information, the specific drug inducing the adverse reaction, the alternative drug, the optimized prescription information, or the feedback information to the external server,” which still only invokes the server merely as a tool in its ordinary capacity to perform an existing process (i.e., receiving, processing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent), and only provides the input data for the performance of the abstract idea, and as such, amounts to insignificant extrasolution activity (i.e., mere data gathering), which does not impose meaningful limits on the scope of the claim. See: MPEP § 2106.05(g). Reevaluated under step 2B, the server is still only invoked merely as a tool in its ordinary capacity to perform an existing process (i.e., receiving, processing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent). Furthermore, receiving or transmitting data over a network, electronic recordkeeping, and storing and retrieving information in memory has been recognized by the courts as well-understood, routine, and conventional elements/functions. See: MPEP § 2106.05(d)(II). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the claims as a whole do not integrate the abstract idea into a practical application and do not provide “significantly more.”
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 groupings 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.
Response to Arguments
Applicant's arguments filed 08/06/2026 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed hereinbelow in the order in which they appear in the response filed 08/06/2026.
In the remarks, Applicant argues in substance that:
Regarding the 101 rejections,
“Amended independent claim 1 recites a specific, technical solution to a technical problem in the field of computerized adverse drug reaction (ADR) monitoring and personalized medicine… Amended independent claim 1 achieves this through a concrete, specialized data feedback loop and server-to-server architecture: 1. Automated Dynamic Updating of a Specialized Database: The server does not merely perform generic data organization; it actively manages and updates an individualized adverse reaction database using specific clinical feedback loops (collecting data post- administration based on optimized prescriptions). 2. Specific Questionnaire-Driven Diagnostic Logic: amended independent claim 1 explicitly recite specific technical inputs-namely, automatically triggering and processing a first questionnaire regarding symptom presence at initial prescription entry and a second questionnaire regarding symptom improvement a specific number of days post- discontinuation. 3. Inter-Server Integration for Clinical Action: The method culminates in a technical output step: transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated database for diagnosis, prescription, dispensing, or usage instructions. Far from reciting generic "methods of organizing human activity," amended independent claim 1 dictates a specific, computerized mechanism for gathering patient-specific pharmacological data, running machine-learning-driven causality and probability algorithms, and securely distributing clinical adjustments across networked medical servers. This transforms the data into a functional tool that directly governs medical dispensing systems and external diagnostic servers, thereby integrating any abstract concepts into a practical technological application”;
“The elements combined in amended independent claim 1- specifically: Utilizing a machine learning model trained explicitly on a dynamically updated individualized adverse reaction database; Calculating rigorous causality scores based on temporal, structured clinical inputs (the first and second questionnaires evaluating discontinuation outcomes); and Providing real-time interoperability by exporting the updated individualized database to an external clinical/dispensing server; -amount to significantly more than routine, conventional, or generic computer implementation. While individual components like generic data storage or basic computing may be known in isolation, the claimed combination provides a specialized technological solution to the technical problem of early-stage data scarcity in personalized pharmacovigilance… The specific arrangement of server-side machine learning integrated with targeted clinical questionnaires and external server distribution is not well-understood, routine, or conventional in the art of standard electronic medical record (EMR) processing.”
Regarding the 103 rejections, the cited prior art reference(s) fails to teach the amended claim limitations.
It is respectfully submitted that Examiner has considered Applicant’s arguments and does not find them persuasive. Examiner has attempted to address all of the arguments presented by Applicant; however, any arguments inadvertently not addressed are not persuasive for at least the following reasons:
In response to Applicant’s argument that (a) regarding the 101 rejections,
“Amended independent claim 1 recites a specific, technical solution to a technical problem in the field of computerized adverse drug reaction (ADR) monitoring and personalized medicine… Amended independent claim 1 achieves this through a concrete, specialized data feedback loop and server-to-server architecture: 1. Automated Dynamic Updating of a Specialized Database: The server does not merely perform generic data organization; it actively manages and updates an individualized adverse reaction database using specific clinical feedback loops (collecting data post- administration based on optimized prescriptions). 2. Specific Questionnaire-Driven Diagnostic Logic: amended independent claim 1 explicitly recite specific technical inputs-namely, automatically triggering and processing a first questionnaire regarding symptom presence at initial prescription entry and a second questionnaire regarding symptom improvement a specific number of days post- discontinuation. 3. Inter-Server Integration for Clinical Action: The method culminates in a technical output step: transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated database for diagnosis, prescription, dispensing, or usage instructions. Far from reciting generic "methods of organizing human activity," amended independent claim 1 dictates a specific, computerized mechanism for gathering patient-specific pharmacological data, running machine-learning-driven causality and probability algorithms, and securely distributing clinical adjustments across networked medical servers. This transforms the data into a functional tool that directly governs medical dispensing systems and external diagnostic servers, thereby integrating any abstract concepts into a practical technological application”:
It is respectfully submitted that Applicant argues “a specific, technical solution to a technical problem in the field of computerized adverse drug reaction (ADR) monitoring and personalized medicine… Amended independent claim 1 achieves this through a concrete, specialized data feedback loop and server-to-server architecture: 1. Automated Dynamic Updating of a Specialized Database: The server does not merely perform generic data organization; it actively manages and updates an individualized adverse reaction database using specific clinical feedback loops (collecting data post- administration based on optimized prescriptions). 2. Specific Questionnaire-Driven Diagnostic Logic: amended independent claim 1 explicitly recite specific technical inputs-namely, automatically triggering and processing a first questionnaire regarding symptom presence at initial prescription entry and a second questionnaire regarding symptom improvement a specific number of days post- discontinuation. 3. Inter-Server Integration for Clinical Action: The method culminates in a technical output step: transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated database for diagnosis, prescription, dispensing, or usage instructions. Far from reciting generic "methods of organizing human activity," amended independent claim 1 dictates a specific, computerized mechanism for gathering patient-specific pharmacological data, running machine-learning-driven causality and probability algorithms, and securely distributing clinical adjustments across networked medical servers.” However, the claim limitations to which Applicant seem to refer as providing the “technical solution” (i.e., “server”) is described at a high level of generality, such that it amounts to no more than mere instructions to apply the exception using generic computer components. Also, the claims add “storing the prescription information and the adverse reaction information in an individualized adverse reaction database,” which only invokes the database merely as a tool in its ordinary capacity to perform an existing process (i.e., providing, storing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent), and only provides the input data for the performance of the abstract idea, and as such, amounts to insignificant extrasolution activity (i.e., mere data gathering), which does not impose meaningful limits on the scope of the claim. See: MPEP § 2106.05(g). Furthermore, the claim limitations to which Applicant seem to refer as “2. Specific Questionnaire-Driven Diagnostic Logic: amended independent claim 1 explicitly recite specific technical inputs-namely, automatically triggering and processing a first questionnaire regarding symptom presence at initial prescription entry and a second questionnaire regarding symptom improvement a specific number of days post- discontinuation” are interpreted as rules or instructions to collect data, analyze the collected data, and provide relevant data (i.e., recommended prescription) based on the analysis accordingly, which is the abstract idea, and not additional elements to be interpreted in Step 2A, Prong Two. Also, the claims add “transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated individualized adverse reaction database for diagnosis, prescription, dispensing, or usage instructions,” which only invokes the server merely as a tool in its ordinary capacity to perform an existing process (i.e., receiving, processing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent), and only provides the input data for the performance of the abstract idea, and as such, amounts to insignificant extrasolution activity (i.e., mere data gathering), which does not impose meaningful limits on the scope of the claim. See: MPEP § 2106.05(g). Also, the claim limitations to which Applicant seem to refer as “machine-learning-driven causality and probability algorithms” is only used to generally apply the abstract idea without placing any limits on how the machine learning model functions (i.e., no details about how the function is accomplished) and only recite the outcome of the abstract idea, and thus, provide nothing more than mere instructions to implement an abstract idea on a generic computer, and merely indicates a field of use or technological environment (i.e., machine learning) in which the judicial exception is performed. See MPEP § 2106.05(f). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually.
Even if the claims provide the alleged improvements “for gathering patient-specific pharmacological data, running…causality and probability algorithms, and securely distributing clinical adjustments,” any alleged benefits of the invention are at best, an improvement to rules or instructions to collect data, analyze the collected data, and provide relevant data (i.e., recommended prescription) based on the analysis accordingly, which is the abstract idea. However, an improved abstract idea is still an abstract idea and the claims do not provide a technical improvement.
The disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing any technical improvement or any physical improvement to the computer. See MPEP § 2106.04(d)(1) and 2106.05(a). Furthermore, the computing system did not cause the argued problem and thus it is not a technical problem caused by the technological environment to which the claims are confined and the claims do not provide a technical improvement.
Thus, the claims are directed to an abstract idea and the claim as a whole does not integrate the recited judicial exception into a practical application.
“The elements combined in amended independent claim 1- specifically: Utilizing a machine learning model trained explicitly on a dynamically updated individualized adverse reaction database; Calculating rigorous causality scores based on temporal, structured clinical inputs (the first and second questionnaires evaluating discontinuation outcomes); and Providing real-time interoperability by exporting the updated individualized database to an external clinical/dispensing server; -amount to significantly more than routine, conventional, or generic computer implementation. While individual components like generic data storage or basic computing may be known in isolation, the claimed combination provides a specialized technological solution to the technical problem of early-stage data scarcity in personalized pharmacovigilance… The specific arrangement of server-side machine learning integrated with targeted clinical questionnaires and external server distribution is not well-understood, routine, or conventional in the art of standard electronic medical record (EMR) processing”:
Applicant argues “The elements combined in amended independent claim 1- specifically: Utilizing a machine learning model trained explicitly on a dynamically updated individualized adverse reaction database; Calculating rigorous causality scores based on temporal, structured clinical inputs (the first and second questionnaires evaluating discontinuation outcomes); and Providing real-time interoperability by exporting the updated individualized database to an external clinical/dispensing server; -amount to significantly more than routine, conventional, or generic computer implementation” and “The specific arrangement of server-side machine learning integrated with targeted clinical questionnaires and external server distribution is not well-understood, routine, or conventional in the art of standard electronic medical record (EMR) processing.” However, per MPEP § 2106.05(I)(A), evaluating whether a claim limitation is “well-understood, routine, conventional activity” is not a standalone test for determining eligibility, but only one consideration “For Evaluating Whether Additional Elements Amount To An Inventive Concept.” The claim limitations to which Applicant seem to refer as “Utilizing a machine learning model trained” is only used to generally apply the abstract idea without placing any limits on how the machine learning model functions (i.e., no details about how the function is accomplished) and only recite the outcome of the abstract idea, and thus, provide nothing more than mere instructions to implement an abstract idea on a generic computer, and merely indicates a field of use or technological environment (i.e., machine learning) in which the judicial exception is performed. See MPEP § 2106.05(f). Furthermore, the “individualized adverse reaction database” is only invoked merely as a tool in its ordinary capacity to perform an existing process (i.e., providing, storing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent). Furthermore, receiving or transmitting data over a network, electronic recordkeeping, and storing and retrieving information in memory has been recognized by the courts as well-understood, routine, and conventional elements/functions. See: MPEP § 2106.05(d)(II). Furthermore, the claim limitations to which Applicant seem to refer as “Calculating rigorous causality scores based on temporal, structured clinical inputs (the first and second questionnaires evaluating discontinuation outcomes)” are interpreted as rules or instructions to collect data, analyze the collected data, and provide relevant data (i.e., recommended prescription) based on the analysis accordingly, which is the abstract idea, and not additional elements to be interpreted in Step 2B. Also, the claims add “transmitting the updated individualized adverse reaction database to an external server configured to utilize the updated individualized adverse reaction database for diagnosis, prescription, dispensing, or usage instructions,” which only invokes the server merely as a tool in its ordinary capacity to perform an existing process (i.e., receiving, processing data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent). Furthermore, receiving or transmitting data over a network, electronic recordkeeping, and storing and retrieving information in memory has been recognized by the courts as well-understood, routine, and conventional elements/functions. See: MPEP § 2106.05(d)(II). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually.
Applicant argues “While individual components like generic data storage or basic computing may be known in isolation, the claimed combination provides a specialized technological solution to the technical problem of early-stage data scarcity in personalized pharmacovigilance.” However, “early-stage data scarcity in personalized pharmacovigilance” addresses administrative problems, and not a technical problem to any specific devices, technology, or computers for that matter, and thus, the claims do not provide a technical solution. As stated previously, the computing system did not cause the argued problem and thus it is not a technical problem caused by the technological environment to which the claims are confined. Even a technical solution to a non-technical problem does not integrate the judicial exception into a practical application. Applicant’s claims do not recite the invention of improvements to computer functionality, technology, or any other technological field, but the use of generic computer components to collect data, analyze the collected data, and provide relevant data (i.e., recommended prescription) based on the analysis accordingly, which is an abstract idea, but for the recitation of generic computer components. Examiner cannot find and Appellant has not identified any problem caused by the technological environment to which the claims are confined (i.e., a well-known, general purpose computer). While the specification need not explicitly set forth the improvement, the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing any technical improvement to computer technology, a physical improvement to the computer, or any other technical improvement. See MPEP § 2106.04(d)(1) and 2106.05(a).
Thus, the claim as a whole does not amount to significantly more than the judicial exception.
Thus, Examiner maintains the 101 rejections of claims 1, 3, 5-10, which have been updated to address Applicant’s remarks and to comply with the 2019 Revised Patent Subject Matter Eligibility Guidance and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence in the above Office Action.
In response to Applicant’s argument that (b) regarding the 103 rejections, the cited prior art reference(s) fails to teach the amended claim limitations:
It is respectfully submitted that the amendments have rendered the rejections moot and amended claims 1, 3, 5-10 recite subject matter free of prior art because the prior art does not teach or disclose the amended features in the specific manner and combinations recited. Thus, the claims are now allowable over prior art. Originally numbered dependent claims 3, 5-8 incorporate the allowable features of originally numbered independent claim 1 through dependency.
However, the claims are still rejected under 101.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/EMILY HUYNH/Primary Examiner, Art Unit 3683
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