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 the present application filed on 04/12/2024.
Claims 16-35 are currently pending and have been examined.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 3/19/2024 was filed after the mailing date of the first action on the merits. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
interfacing modules configured for transmitting therapy-related data in claim 16, 28, and 35;
a therapy-support module configured to control the transmission of therapy-related data in claim 16.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
interfacing modules configured for transmitting therapy-related data is interpreted as a part of the therapy optimizer system (p. 17, lines 30-32) (all subsystems can also be implemented as software systems on generic or specialized computational hardware (p. 6, lines 29-31)).
a therapy-support module configured to control the transmission of therapy-related data is interpreted as a part of the therapy optimizer system (p. 4-5, lines 31-32, 1-7) (all subsystems can also be implemented as software systems on generic or specialized computational hardware (p. 6, lines 29-31)).
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 16-35 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 analysis:
Independent Claims 16, 28, and 35 are within the four statutory categories. Claims 16, 28, and 35 are directed to a system, method, and computer program (i.e. a process) respectively. Dependent Claims 17-27, and 29-34 recite a system and method respectively and therefore also fall within one of the four statutory categories.
Step 2A analysis- prong one:
The substantially similar independent claims, taking Claim 16 as exemplary, recite the following:
A therapy optimizer system, the therapy optimizer system comprising:
interfacing modules configured for transmitting therapy-related data with a clinical data base, a clinical monitor, a dose-response simulator, and a patient monitor; and a therapy-support module configured to control the transmission of therapy-related data by the interfacing modules,
wherein the therapy-support module is further configured to process the transmitted therapy-related data to generate therapy-related recommendations to be additionally transmitted by the interfacing modules.
The series of steps as shown in underline above, given the broadest reasonable interpretation, cover the abstract idea of certain methods of organizing human activity because they recite managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions- in this case, processing data to generate recommendations) e.g., see MPEP 2106.04(a)(2). Any limitations not identified as part of the abstract idea are deemed “additional elements” and will be discussed in further detail below.
Dependent Claims 17-27 and 29-34 include other limitations directed toward the abstract idea. For example, Claim 17 recites the types of diseases, Claims 18 and 29 recite transmitting data related to patient health records, Claims 19 and 30 recite data related to monitoring patients, Claims 20 and 31 recite transmitting data related to dose-response, Claims 21 and 32 recite transmitting data related to the patient, Claims 22 and 33 recite transforming therapy-related data, Claims 23 and 34 recite analyzing therapy related data for their sufficiency in generating recommendations, Claim 24 recites generating data-input requests, Claim 25 recites generating therapy-related recommendations, Claim 26 recites sufficiency criterion is related to recommendation accuracy, Claim 27 recites the recommendation accuracy is set according to additional data. The dependent claims only serve to narrow the abstract idea set forth in the independent claims, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, see MPEP 2106.04. Hence, the dependent claims are further directed toward certain methods of organizing human activity.
Step 2A analysis- prong two:
Claims 16, 28, and 35 are not integrated into practical application because the additional elements (i.e. the non-underlined limitations above- in this case, the interfacing modules, clinical data base, clinical monitor, dose-response simulator, patient monitor, and therapy-support module of Claim 16, and the interfacing modules, clinical data base, clinical monitor, dose-response simulator, and patient monitor of Claims 28 and 35) are recited at a high level of generality (i.e. as a generic processor performing generic computer functions) such that they amount to no more than mere instructions to apply the exceptions using generic computer components. For example, applicant’s specification explains that the therapy-support module serves the purpose of emulating different interdependent medical aspects of the addressed condition CKD-MBD (p. 9, lines 1-4). The interfacing module to the patient monitor (220) corresponds to patient-side contributions to the medical condition and its therapy, the interfacing module to the clinical monitor corresponds to clinician-side contributions to the medical condition and its therapy, and the interfacing module to the drug-dose monitor corresponds to effects of separate drugs, their dosing, and combinational effects to the medical condition and its therapy (p. 9, lines 4-9). One first subsystem of the CDSS, a patient monitor, can be employed for monitoring and analyzing the medical patient status and behavior: medication adherence, patient activity, diet, self-assessment through sensors and electronic patient-reported outcomes (p. 4, lines 6- 9). One second subsystem of the CDSS, a dose-response simulator, can be employed for simulating drug-dose response of a patient with certain medical status. For each CKD-MBD related drug (e.g., vitamin D, phosphate binder, etc.) and by considering the specificity of the patient (e.g., biomarkers, comorbidities, lifestyle, medications, etc.), a dose-response relation can be computed (p. 4, lines 13-17). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the idea. Therefore, Claims 16, 28, and 35 are directed to an abstract idea without practical application.
Dependent Claims 18-27 and 29-34 also recite additional elements. Claims 18 and 29 recite the previously recited interfacing modules and a new additional element (a clinical database). Claim 19 recites the previously recited interfacing modules and a new additional element (a clinician-used clinical monitor). Claim 20 recites the previously recited interfacing modules and a new additional element (a dose-response simulator). Claim 21 recites the interfacing modules and a new additional element (a patient-used patient monitor). Claims 22 and 33 recite the previously recited interfacing modules and the therapy-support module. Claims 23-25 and 34 recite the previously recite therapy-support module and interfacing modules. Claims 26 and 27 recite the previously recited interfacing modules. Claim 30 recites the previously recited interfacing modules and the clinical monitor. Claim 32 recites the interfacing modules and the patient monitor.
Step 2B analysis:
The claims, when considered individually or in combination, do not include any additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed with respect to step 2A prong two, the additional elements of the interfacing modules, clinical data base, clinical monitor, dose-response simulator, patient monitor, and therapy-support module of Claim 16, and the interfacing modules, clinical data base, clinical monitor, dose-response simulator, and patient monitor of Claims 28 and 35 amount to mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”). MPEP2106.05(I)(A) indicates that merely saying "apply it” or equivalent to the abstract idea cannot provide an inventive concept ("significantly more").
Dependent claim 17 does not recite an additional element and only serves to further define the abstract idea by specifying the types of diseases.
Dependent Claims 19-27 and 30-34 narrow previously recited additional elements. Claim 19 and 30 narrows previously recited interfacing modules by specifying the modules transmits clinical data. Claims 20 and 31 narrow the previously recited interfacing modules by specifying the modules transmit data related to dose-response, Claims 21 and 32 narrow the previously recited interfacing modules by specifying the modules transmit data related to the patient, Claims 22 and 33 narrow the previously recited interfacing modules by specifying the modules transform therapy-related data, Claims 23 and 34 narrow the previously recited therapy-support module by specifying it analyzes therapy related data for their sufficiency in generating recommendations, Claim 24 narrows the previously recited therapy-support module by specifying it generates data-input requests, Claim 25 narrows the previously recited therapy-support module by specifying the module generated therapy-related recommendations, Claim 26 narrows the previously recited interfacing modules by specifying the modules receive transmitted data regarding the generated sufficiency criterion which is related to recommendation accuracy, Claim 27 recites the recommendation accuracy is set according to additional data which is transmitted to the interfacing module. Claims 18 and 29 recite new additional elements of a clinical database. However, these additional elements are described only at a high level of generality and are being used in their expected fashion, so these additional elements do not integrate the abstract idea into a practice application because they do not impose any meaningful limits on the abstract idea The claims do not recite additional elements that integrate the judicial exception into a practical application when considered both individually and as an ordered combination.
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 does not add anything that is already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, Claims 16-35 are rejected under 35 U.S.C. 101 as being directed to a non-statutory subject matter.
Claim Rejections - 35 USC § 103
Claims 16, 18-21, and 29-32 are rejected under 35 USC 103 as being unpatentable over Heldman et al. (US 11367519 B1) in view of Hengstenberg et al. (US 20160114114 A1).
Regarding Claim 16, Heldman discloses the following:
A therapy optimizer system, the therapy optimizer system comprising: interfacing modules configured for transmitting therapy-related data (Heldman discloses at least one electronic component for transmitting and receiving signals is required… the movement data and/or such suggested or determined parameters may be transmitted to storage or other remote locations as described. Additionally, the movement data and/or second or next level of therapy parameters may additionally be transmitted to a central server, cloud based server, or other such database for storage and backup purposes (col. 16, lines 15-47).)
with a clinical database, (Heldman discloses utilizing physiological and electrophysiological information from sensors, and many embodiments preferably utilize a database, or a system of databases, of patient and treatment histories to correlate current subject information with historical data (col. 11, lines 12-17). This is interpreted as a clinical database.)
a dose-response simulator, (Heldman discloses a quantification algorithm adapted to quantify symptom severity and to calculate a quantification score of at least one symptom based at least in part on the acquired movement data; and a treatment algorithm adapted to predict when a drug or medication should be administered to prevent an increase in symptom severity based in part on early detection of changes symptom severity and historical data of at least the first subject and/or other subjects, and to provide a recommended drug or medication regimen or protocol comprising a drug, drug dosage, and/or instructions for administration of the drug and/or drug dosage, the recommended regimen or protocol based at least in part on the calculated quantification score (col. 35, lines 12-25, see also Fig. 11). This is interpreted as a dose-response simulator.)
a clinical monitor,… and a patient monitor; (Heldman discloses a continuous monitoring system may be employed wherein the movement disorder diagnostic device continuously senses, measures and quantifies the subject's external body movements over extended periods of time…(col. 14, lines 13-16). This is interpreted as a clinical monitor. Some embodiments utilize…multiple motion sensors, other sensors related to physiological characteristics…processing and interface components (e.g., smartphone application) to monitor physical activity, sleep quality, speech patterns, community mobility, self-reported patient information on symptom level or severity and quality of life (col. 28, lines 48-52). This is interpreted as a patient monitor.
wherein the therapy-support module is further configured to process the transmitted therapy-related data to generate therapy-related recommendations to be additionally transmitted by the interfacing modules (Heldman discloses optimization or tuning algorithm(s) which are used to determine or recommend optimum therapy settings or parameters. Such optimization algorithms may include, but are not limited to simplex algorithms, extensions of the simplex algorithm designed for quadratic and/or linear function programming, combinatorial algorithms, and other multi-variant optimization algorithms (col. 16, lines 49-55).)
Heldman does not disclose the therapy-support module controlling the transmission of data which is met by Hengstenberg:
and a…module configured to control the transmission of therapy-related data by the …modules,… (Hengstenberg teaches connections 5, 7 originate from the control system 3, so that the control system 3 can send a control signal S via the connection 5 to a transfer unit 9 described in further detail below. In addition, the control signal S in this exemplary embodiment is returned to the control system 3 via the connection 7 [0048].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the therapy-support model controlling the transmission of data which is taught by Hengstenberg. This modification would create a system and methods capable of properly monitoring and controlling the data transmission (see Hengstenberg, ¶ 0005).
Regarding Claim 18, Heldman and Hengstenberg teach the limitations as shown in the rejection of Claim 16 above. Heldman further discloses the following:
wherein one of the interfacing modules is further configured to transmit data related to patient health records with a clinical database. (Heldman discloses utilizing physiological and electrophysiological information from sensors, and many embodiments preferably utilize a database, or system of databases, of patient and treatment histories to correlate current subject information and data with historical data. The systems and methods preferably provide for pharmaceutical parameters such as drug titrations, doses and times. The present invention further includes a system and methods of storing and cataloging the movement related information and patient specific treatments in a database system (col. 11, lines 13-22).)
Regarding Claim 29, this claim recites limitations that are substantially similar to Claim 18 above; thus, the same rejection applies.
Regarding Claim 19, Heldman and Hengstenberg teach the limitations as shown in the rejection of Claim 16 above. Heldman further discloses the following:
wherein one of the interfacing modules is further configured to transmit data related to one or more of drug-dose adjustments, visit assessments, or medical patient constraints and one or more of clinical patient characteristics, biomarkers, drug treatments, medical warnings, or support requests with a clinician-used clinical monitor. (Heldman discloses methods for semi-automatically and automatically adjusting, or tuning, treatment parameters (col. 11, lines 41-44). One embodiment presents… therapy parameters, (e.g., drug dosage, stimulation parameters, or the like), (62, lines 3-5). The present invention further includes a system and methods of storing and cataloging the movement related information and patient specific treatments in a database system to be used for continuous improvement of the treatment protocols for use with subjects in the future (col. 11, lines 20-24). The display is capable of displaying multiple types and forms of data, messages, warnings and other information simultaneously and also of emphasizing certain information based on importance or potential emergency (col. 62, lines 63-66).)
Regarding Claim 30, this claim recites limitations that are substantially similar to Claim 19 above; thus, the same rejection applies.
Regarding Claim 20, Heldman and Hengstenberg teach the limitations as shown in the rejection of Claim 16 above. Heldman further discloses the following:
…and one or more of drug intake, diet, biomarkers, or patient characteristics … (Heldman discloses to further provide an action recommendation corresponding to a suggested activity, exercise, diet, and/or environmental condition to prevent the onset or recurrence of symptoms, wherein the recommended drug or medication regimen or protocol is adapted to provide a desired drug profile in the subject's bloodstream…(col. 36, lines 23-27).)
Heldman does not disclose the use of a simulator for drug dose response which is met by Hengstenberg:
wherein one of the interfacing modules is further configured to transmit data related to a patient's dose-response relation…with a drug dose-response simulator. (Hengstenberg teaches the concentration of the drug in the breathing gas c1(k) and in the blood circulation cp(k), but also the concentration c2, c3 of the drug in the second and third compartments V2, V3 as well as the concentration ce at the site of action WO (see FIG. 3), are calculated with the simulation calculation. These concentrations may be taken into account in the generation of the control signal S in partial step 41 [0083].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate a drug dose response simulator as taught by Hengstenberg. This modification would create a system and methods capable of determining the proper dose required to avoid unnecessary problems (see Hengstenberg, ¶ 0008).
Regarding Claim 31, this claim recites limitations that are substantially similar to Claim 20 above; thus, the same rejection applies.
Regarding Claim 21, Heldman and Hengstenberg teach the limitations as shown in the rejection of Claim 16 above. Heldman further discloses the following:
wherein one of the interfacing modules is further configured to transmit data related to one or more of drug-dose adjustments, physical activity, visit assessments, or a questionnaire for clinical data and one or more of drug intake, diet, physical activity, or patient-reported outcomes and sensor measurements with a patient-used patient monitor. (Heldman discloses the subject-worn device or system may temporarily store the subject's movement or physiological data, or other data such as audio or video sensor data, in onboard memory and/or transmit this data to an external device… the subject-worn device or system may directly transmit the data to a centralized database (col. 40, lines 48-54).)
Regarding Claim 32, this claim recites limitations that are substantially similar to Claim 21 above; thus, the same rejection applies.
Claims 17, 22 and 33 are rejected under 35 USC 103 as being unpatentable over Heldman and Hengstenberg in view of Gejdos et al. (US 20090150439 A1).
Regarding Claim 17, Heldman and Hengstenberg teach the limitations as shown in the rejection of Claim 16 above. Heldman and Hengstenberg do not teach the following limitations met by Gejdos:
wherein the system is configured to support a therapy of a disease comprising CKD-MBD, hypotension, diabetes, coronary heart/artery disease, asthma, obesity, or cancer. (Gejdos teaches the information to be shared can originate from health management devices 104, such as glucose meters, containing a glucose measurement engine, used by people with diabetes to manage their disease, and from other medical information systems 200 [0021].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the system being in support of diabetes as taught by Gejdos. This modification would create a system and methods capable of assisting patients with diabetes so these patients can reduce the frequency of necessary visits to the doctor (see Gejdos, ¶ 0002-3).
Regarding Claim 22, Heldman and Hengstenberg teach the limitations as shown in the rejection of Claim 16 above. Heldman further discloses:
wherein the interfacing modules are further configured to…the processing of the therapy-support module…the respective interfacing modules. (Heldman discloses at least one electronic component for transmitting and receiving signals is required… the movement data and/or such suggested or determined parameters may be transmitted to storage or other remote locations as described. Additionally, the movement data and/or second or next level of therapy parameters may additionally be transmitted to a central server, cloud based server, or other such database for storage and backup purposes (col. 16, lines 15-47). Optimization or tuning algorithm(s) which are used to determine or recommend optimum therapy settings or parameters. Such optimization algorithms may include, but are not limited to simplex algorithms, extensions of the simplex algorithm designed for quadratic and/or linear function programming, combinatorial algorithms, and other multi-variant optimization algorithms (col. 16, lines 49-55).)
Heldman and Hengstenberg do not teach transforming data from one format to a target format which is met by Gejdos:
transform …data …from a data format used in the processing …to a data format of the data transmitted to the…modules. (Gejdos teaches the extract, transform and load (ETL) process involves retrieving data from external system 200, transforming (and optionally cleansing) the data into the appropriate format, if necessary, for target system 100 and then loading that information into target system 100 [0026].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate transforming the data from one format to a target format as taught by Gejdos. This modification would create a system and methods capable of analyzing data without the requirement of a doctor (see Gejdos, ¶ 0002-3).
Regarding Claim 33, this claim recites limitations that are substantially similar to Claim 22 above; thus, the same rejection applies.
Claims 23-26, 28, and 34-35 are rejected under 35 USC 103 as being unpatentable over Heldman and Hengstenberg in view of Mehta et al. (US 20220101061 A1).
Regarding Claim 23, Heldman and Hengstenberg teach the limitations as shown in the rejection of Claim 16 above. Heldman further discloses the following:
wherein the therapy- support module is further configured to analyze the therapy-related data transmitted to the interfacing modules (Heldman discloses various clinically observed or measured metrics or analytical data processing values…such metrics being able to be measured by the present invention objectively, such measures of analysis including:…heart rate variability measurements compared with therapy or treatment (see Figs. 2A-C).)
Heldman and Hengstenberg do not teach the following limitations met by Mehta:
…with respect to… sufficiency for generating…[recommendations]. (Mehta teaches one or more machine learning prediction models are automatically generated for at least a portion of the selected one or more of the plurality of data input fields. For example, a machine learning model is generated for a selected data input field….a model must have a prediction accuracy that exceeds a threshold amount before it is considered helpful to a user and can be used for automation [0014].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the determination of the sufficiency of the recommendation as taught by Mehta. This modification would create a system and methods capable of improving the efficiency and accuracy of the system (see Mehta, ¶ 0001).
Regarding Claim 34, this claim recites limitations that are substantially similar to Claim 23 above; thus, the same rejection applies.
Regarding Claim 24, Heldman, Hengstenberg, and Mehta teach the limitations as shown in the rejection of Claim 23 above. Heldman further discloses:
wherein the therapy- support module is further configured to (Heldman discloses optimization or tuning algorithm(s) which are used to determine or recommend optimum therapy settings or parameters. Such optimization algorithms may include, but are not limited to simplex algorithms, extensions of the simplex algorithm designed for quadratic and/or linear function programming, combinatorial algorithms, and other multi-variant optimization algorithms (col. 16, lines 49-55).)
Heldman and Hengstenberg do not teach the following limitations met by Mehta:
generate data-input requests to be transmitted by the respective interfacing modules when the therapy-related data transmitted to the interfacing module are insufficient for generating therapy-related recommendations. (Mehta teaches a machine learning model is trained and then confirmed to meet an accuracy threshold. For example, an accuracy score is determined for each trained machine learning model [0028]. In the event the training data is not sufficient, processing proceeds back to 403 where additional monitoring data can be captured, for example, on subsequent interactions with the form when the form in the appropriate completion state [0042].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the addition of more data if the recommendation is not sufficient as taught by Mehta. This modification would create a system and methods capable of improving the efficiency and accuracy of the system (see Mehta, ¶ 0001).
Regarding Claim 25, Heldman, Hengstenberg, and Mehta teach the limitations as shown in the rejection of Claim 23 above. Heldman further discloses:
wherein the therapy- support module is further configured to generate, based on the therapy-related data transmitted to the interfacing modules, therapy-related recommendations to be transmitted by the respective interfacing modules (Heldman discloses optimization or tuning algorithm(s) which are used to determine or recommend optimum therapy settings or parameters. Such optimization algorithms may include, but are not limited to simplex algorithms, extensions of the simplex algorithm designed for quadratic and/or linear function programming, combinatorial algorithms, and other multi-variant optimization algorithms (col. 16, lines 49-55).)
Heldman and Hengstenberg do not teach the following limitations met by Mehta:
when the…data transmitted… are sufficient for generating…recommendations. (Mehta teaches a machine learning model is trained and then confirmed to meet an accuracy threshold. For example, an accuracy score is determined for each trained machine learning model…Models that meet the accuracy threshold can be used to enable automation for the corresponding data input field [0028].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the determination of the sufficiency of the recommendation as taught by Mehta. This modification would create a system and methods capable of improving the efficiency and accuracy of the system (see Mehta, ¶ 0001).
Regarding Claim 26, Heldman, Hengstenberg, and Mehta teach the limitations as shown in the rejection of Claim 25 above. Heldman further discloses:
…and the generated therapy-related recommendations… to be transmitted by the respective interfacing modules (Heldman discloses optimization or tuning algorithm(s) which are used to determine of recommend optimum therapy settings or parameters. Such optimization algorithms may include, but are not limited to simplex algorithms, extensions of the simplex algorithm designed for quadratic and/or linear function programming, combinatorial algorithms, and other multi-variant optimization algorithms (col. 16, lines 49-55).)
Heldman and Hengstenberg do not teach the following limitations met by Mehta:
wherein sufficiency criterion for the analysis of the…data transmitted …is related to a pre-set recommendation accuracy (Mehta teaches a user can configure an accuracy threshold that must be met before a generated machine learning model is utilized for predicting responses for a data input field [0023].)
additionally include the recommendation accuracy and the generated data- input requests (Mehta teaches the trained models are evaluated for accuracy. For example, for each data input field, the models generated for the field are evaluated for accuracy [0048, see also Fig. 5]. In the event the training data is not sufficient, processing proceeds back to 403 where additional monitoring data can be captured, for example, on subsequent interactions with the form when the form in the appropriate completion state. [0042, see also Fig. 4].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the determination of the sufficiency of the recommendation as taught by Mehta. This modification would create a system and methods capable of improving the efficiency and accuracy of the system (see Mehta, ¶ 0001).
Regarding Claim 28, Heldman discloses the following:
A computer-implemented method for supporting the therapy of diseases, the method comprising: transmitting therapy-related data to interfacing modules configured for transmitting therapy-related data to a clinical database, (Heldman discloses the present invention relates to systems and methods for providing recommended doses and instructions for pharmaceutical treatments (col. 37, lines 45-47). At least one electronic component for transmitting and receiving signals is required… the movement data and/or such suggested or determined parameters may be transmitted to storage or other remote locations as described. Additionally, the movement data and/or second or next level of therapy parameters may additionally be transmitted to a central server, cloud based server, or other such database for storage and backup purposes (col. 16, lines 15-47).)
with a clinical data base, (Heldman discloses utilizing physiological and electrophysiological information from sensors, and many embodiments preferably utilize a database, or a system of databases, of patient and treatment histories to correlate current subject information with historical data (col. 11, lines 12-17). This is interpreted as a clinical database.)
a dose-response simulator, (Heldman discloses a quantification algorithm adapted to quantify symptom severity and to calculate a quantification score of at least one symptom based at least in part on the acquired movement data; and a treatment algorithm adapted to predict when a drug or medication should be administered to prevent an increase in symptom severity based in part on early detection of changes symptom severity and historical data of at least the first subject and/or other subjects, and to provide a recommended drug or medication regimen or protocol comprising a drug, drug dosage, and/or instructions for administration of the drug and/or drug dosage, the recommended regimen or protocol based at least in part on the calculated quantification score (col. 35, lines 12-25, see also Fig. 11). This is interpreted as a dose-response simulator.)
a clinical monitor,… and a patient monitor; (Heldman discloses a continuous monitoring system may be employed wherein the movement disorder diagnostic device continuously senses, measures and quantifies the subject's external body movements over extended periods of time…(col. 14, lines 13-16). This is interpreted as a clinical monitor. Some embodiments utilize…multiple motion sensors, other sensors related to physiological characteristics…processing and interface components (e.g., smartphone application) to monitor physical activity, sleep quality, speech patterns, community mobility, self-reported patient information on symptom level or severity and quality of life (col. 28, lines 48-52). This is interpreted as a patient monitor.
generating, based on the therapy-related data transmitted to the interfacing modules, therapy-related recommendations to be transmitted by the respective interfacing modules; (Heldman discloses optimization or tuning algorithm(s) which are used to determine or recommend optimum therapy settings or parameters. Such optimization algorithms may include, but are not limited to simplex algorithms, extensions of the simplex algorithm designed for quadratic and/or linear function programming, combinatorial algorithms, and other multi-variant optimization algorithms (col. 16, lines 49-55).)
Heldman does not disclose the controlling of the interfacing modules to transmit data which is met by Hengstenberg:
and controlling the interfacing modules to transmit respective data-input requests and/or therapy-related recommendations. (Hengstenberg teaches connections 5, 7 originate from the control system 3, so that the control system 3 can send a control signal S via the connection 5 to a transfer unit 9 described in further detail below. In addition, the control signal S in this exemplary embodiment is returned to the control system 3 via the connection 7 [0048].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the therapy-support model controlling the transmission of data which is taught by Hengstenberg. This modification would create a system and methods capable of properly monitoring and controlling the data transmission (see Hengstenberg, ¶ 0005).
Heldman and Hengstenberg do not teach the determination of the recommendation sufficiency which is met by Mehta:
analyzing the…data…with respect to their sufficiency for producing therapy-related recommendations; (Mehta teaches one or more machine learning prediction models are automatically generated for at least a portion of the selected one or more of the plurality of data input fields. For example, a machine learning model is generated for a selected data input field….a model must have a prediction accuracy that exceeds a threshold amount before it is considered helpful to a user and can be used for automation [0014].)
generating, based on the sufficiency analysis, data-input requests…(Mehta teaches a machine learning model is trained and then confirmed to meet an accuracy threshold. For example, an accuracy score is determined for each trained machine learning model [0028]. In the event the training data is not sufficient, processing proceeds back to 403 where additional monitoring data can be captured, for example, on subsequent interactions with the form when the form in the appropriate completion state [0042].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the addition of more data if the recommendation is not sufficient as taught by Mehta. This modification would create a system and methods capable of improving the efficiency and accuracy of the system (see Mehta, ¶ 0001).
Regarding Claim 35, this Claim recites limitations that are substantially similar to those recited in Claim 28 above; thus, the same rejection applies. Heldman further discloses the following:
A computer program comprising instructions, which, when executed by a computer, cause the computer to perform operations (Heldman discloses the software preferably will take advantage of the smartphone’s internal Bluetooth to collect kinematic data from the motion sensors (col. 30, lines 45-57, see also Fig. 6).
Claim 27 is rejected under 35 USC 103 as being unpatentable over Heldman, Hengstenberg, and Mehta as applied to Claim 26 in view of Hee et al. (KR 102450128 B1).
Regarding Claim 27, Heldman, Hengstenberg, and Mehta teach the limitations as shown in the rejection of Claim 26 above. Heldman further discloses:
data transmitted to the interfacing module (Heldman discloses the various components of the system must be able to communicate with each other in order to transmit signals, data, commands, and the like between and amongst each other. Wireless communication is preferred for all communication of data to and from the device (col. 42, lines 58-62).)
Heldman and Hengstenberg do not teach determining the recommendation accuracy which is met by Mehta:
wherein the recommendation accuracy…(Mehta teaches a machine learning model is trained and then confirmed to meet an accuracy threshold. For example, an accuracy score is determined for each trained machine learning model…Models that meet the accuracy threshold can be used to enable automation for the corresponding data input field [0028].)
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the determination of the sufficiency of the recommendation as taught by Mehta. This modification would create a system and methods capable of improving the efficiency and accuracy of the system (see Mehta, ¶ 0001).
Heldman, Hengstenberg, and Mehta do not teach determining the recommendation accuracy which is met by Hee:
is set according to additional data…(Hee teaches the biometric recognition support apparatus 110 using individual thresholds according to an embodiment of the present invention obtains biometric information about a user and determines a similarity between registered biometric information corresponding to the user stored in a database and input biometric information… an individual threshold corresponding to the user is set using the similarity determination record, and biometric authentication for the user is performed using …the individual threshold (p. 3, ¶ 0004).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have modified the system and method for transmitting relevant data, using a database, monitors, and a simulator, and generating a therapy recommendation as disclosed by Heldman to incorporate the accuracy value being set according to additional data as taught by Hee. This modification would create a system and methods capable of keeping the processes up to date and therefore as accurate as possible (see Hee, p. 2, ¶ 0003).
Relevant Art Made of Record Not Currently Being Applied
The following references are considered pertinent to Applicant’s disclosure but are not currently being applied:
Tran et al. (US 20200251213 A1) teaches systems and methods for recommending lifestyle modification for a subject including using pharmacogenomics to predict the impact of medications and dosages.
Kutzko et al. (US 20210241918 A1) teaches a computer implemented method for predicting the health and making treatment plan recommendations including the use of a communication interface.
Tucker et al. (US 20160335412 A1) teaches systems and methods for simulating a patient response to a given drug dosage using a simulator to recommend an appropriate dosage level.
Conclusion
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