Response to Amendment
This communication is in response to the amendment filed on 2/20/2026. Claims 1-3 and 5-13 are pending.
Claim Objections
The objections to Claims 1, 11, and 12 are withdrawn based on the amendments filed on 2/20/2026.
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 and 5-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Is the Claim to a Process, Machine, Manufacture or Composition of Matter?
Claim 1 recites an information processing device, and Claim 11 recites an information processing method. Thus, these claims are to a machine and a method, which are among the statutory categories of invention.
Step 2A: Prong One: Does the Claim Recite an Abstract Idea?
Independent claim 1 recites:
An information processing device comprising:
a first identification unit that identifies a cultivation condition for cultivating a specific crude drug, with use of a first model that associates a crude drug with a cultivation condition for cultivating the crude drug by a diversity-promoting cultivation method for promoting biodiversity and controlling an ecosystem to produce vegetation. [the examiner finds that the foregoing underlined elements recite mathematical concepts, and also a mental process because they can be performed by a human using pen and paper]; and
a sensor device which transmits sensor data to a database,
the sensor device being disposed in a farm field where the specific crude drug is cultivated and where the farm field is being cultivated using an open-field crop cultivation method in which plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings,
a second identification unit that identifies a health factor offering a specific health benefit and including an herbal medicine, with use of a second model that associates a health benefit with a health factor offering the health benefit and including an herbal medicine [the examiner finds that the foregoing underlined elements recite mathematical concepts, and also a mental process because they can be performed by a human using pen and paper];
a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine which has ingredient compositions depending on at least one of their production areas and cultivation condition, resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription [the examiner finds that the foregoing underlined elements recite mathematical concepts, and also a mental process because they can be performed by a human using pen and paper]; and
a controller that controls blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit.
Step 2A: Prong Two: Does the Claim Recite Additional Elements That Integrate The Abstract Idea Into a Practical Application?
The elements that are not underlined above are the additional elements (i.e., using a “first information processing device” comprising “a first identification unit” that performs the identifying step, and “a first model” to perform the associating step; “a sensor device which transmits sensor data to a database, the sensor device being disposed in a farm field where the specific crude drug is cultivated and where the farm field is being cultivated using an open-field crop cultivation method in which plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings”, “a second identification unit” and “a second model” to perform the identifying step, “a blending quantity calculation unit” to perform the calculating step; and “a controller that controls blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit”).
The examiner submits that each of the additional elements does no more than generally link the use of the abstract idea to a particular technological environment or field of use because they are merely an incidental or token addition to the claim that does not alter or affect how the process steps of Claim 1 are performed. The first information processing device, first identification unit, first model, second identification unit, second model, and blending quantity calculation unit are broadly recited, and amount to no more than use of a generic computer to perform the identifying, associating, identifying, and calculating steps. The sensor device is a broadly recited, generic sensor that amounts to nothing more than mere gathering of data for use in the abstract idea. The controller is generic hardware, and merely insignificantly applies a result of the abstract idea (see MPEP 2106.05(g)).
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For example, there is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
Step 2B: Does the Claim Recite Additional Elements That Amount to Significantly More Than the Abstract Idea?
The examiner submits that the additional elements do not amount to significantly more than the abstract idea for the same reasons discussed above with respect to the conclusion that the additional elements do not integrate the abstract idea into a practical application.
Independent Claims 11 and 12 recites the same identifying, associating, identifying, and calculating steps, and the same sensor, as Claim 1, and are also abstract ideas for the same reasons discussed above. Claim 11 includes no additional elements, and Claim 12 merely recites non-transitory computer readable medium, which is merely use of a generic computer.
Dependent Claims 2-3 and 5-10 merely recite further details of the mathematical concepts and/or mental process, and are also not patent eligible. Claim 13 merely recites generic computer hardware for outputting an insignificant application of a result of the abstract idea.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 6, 8, 11, and 12-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shibata et al (U.S. Pub. No. 2021/0010993, hereinafter “Shibata”) in view of Funabashi (U.S. Pub. No. 2017/0199880), Baugh et al (U.S. Pub. No. 2019/0385730, hereinafter “Baugh”), and Watabe (JP-2016018224-A).
Regarding Claim 1, Shibata teaches an information processing device (Fig. 1) comprising: a first identification unit that identifies a cultivation condition (microbiome types 105a) for cultivating a specific crude drug (Fig. 1, environmental data 103; paragraphs [0134] and [0139], crop data which is included in environmental data 103 includes specific type of plant to be grown; paragraph [0043], medicine), with use of a first model that associates a crude drug with a cultivation condition for cultivating the crude drug by a diversity-promoting cultivation method for promoting biodiversity and controlling an ecosystem to produce vegetation (recommendation engine 106 recommends agronomic program 107 based on environmental data 103, which includes specific type of plant, and microbiome type 105a; paragraphs [0161], supporting microbiome diversity; [0162], [0227], increasing biodiversity).
Shibata does not specifically teach a sensor device which transmits sensor data to a database, the sensor device being disposed in a farm field where the specific crude drug is cultivated and where the farm field is being cultivated using an open-field crop cultivation method in which plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings. However, it is noted that the Background section of Applicant’s Specification as filed defines, in paragraph [0002], synecoculture as a method “where plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings”. Further, Funabashi teaches, in Fig. 1, sensor devices 11 that acquire information in a synecoculture system (see paragraph [0004]) and transmit the information to a synecoculture database (Fig. 5, paragraphs [0158]-[0160]). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the sensor, database, and synecoculture system of Funabashi in the system of Shibata, In order to allow ecosystems to be actively utilized (see Funabashi, paragraph [0007]).
Shibata does not teach a second identification unit that identifies a health factor offering a specific health benefit and including an herbal medicine, with use of a second model that associates a health benefit with a health factor offering the health benefit and including an herbal medicine; a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine which has ingredient compositions, resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription; and a controller that controls blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit. However, Baugh teaches a second identification unit that identifies a health factor offering a specific health benefit and including an herbal medicine, with use of a second model that associates a health benefit with a health factor offering the health benefit and including an herbal medicine (paragraph [0089], modeling software, targeted treatments, which are equated to health factor and herbal medicine, for preferred benefit or outcome, which is equated to health benefit; paragraph [0090], complex herbal medicines; paragraph [0091], personalized drug discovery model); a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine which have ingredient compositions (paragraph [0090], complex herbal medicines, paragraphs [0101]-[0104], blending ingredients into predetermined formulation), resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription (paragraph [0090], complex herbal medicines for a variety of indications from tinnitus to treating the common cold; paragraph [0091], advancement in patient treatment); and a controller that controls blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit (paragraphs [0101]-[0104], blending ingredients into predetermined formulation). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the model of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063]), and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Shibata and Baugh do not specifically teach that the blending is performed depending on at least one of their production areas and cultivation condition. However, Watabe teaches, on page 9, that the amount of herbal medicines that would be included in a blend may vary based on where the herbal medicine was grown (e.g., in Japan versus in China), because the component ratio data may be different between medicines grown in different areas; this may also be equated to different cultivation conditions between different areas. It would have been obvious to one skilled in the art before the effective filing date of the invention to include the standardizing of the medicinal ingredients based on where the herbs were grown, as is taught in Watabe, in the system of Shibata and Baugh, because it is not easy to make the medicinal components of agricultural products grown in the open field constant (see Watabe, page 9.
Regarding Claim 6, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 1. Shibata does not teach wherein the second identification unit identifies health factors offering the specific health benefit and including an herbal medicine and a lifestyle. However, Baugh teaches wherein the second identification unit (paragraph [0089], modeling software, targeted treatments (equated to health factor and herbal medicine) for preferred benefit or outcome (equated to health benefit); paragraph [0090], complex herbal medicines; paragraph [0091], personalized drug discovery model) identifies health factors offering the specific health benefit and including an herbal medicine and a lifestyle (paragraph [0090], herbal medicines; paragraphs [0098]-[0099], lifestyle factors and dietary supplements are linked to desired outcome by the model). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the model of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063]), and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Regarding Claim 8, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 1. Shibata does not teach a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine such that beneficial ingredients are equal to or above a reference value of the beneficial ingredients and toxic ingredients are equal to or below a reference value of the toxic ingredients. However, Baugh teaches a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine such that beneficial ingredients are equal to or above a reference value of the beneficial ingredients and toxic ingredients are equal to or below a reference value of the toxic ingredients (paragraphs [0090]-[0094], complex herbal medicines; paragraphs [0101]-[0104], any number of ingredients can be used to blend into a predetermined formulation; the blended predetermined formulation would be blended to have specific amounts, i.e. equal to reference values, of each of the ingredients, whether they are toxic or non-toxic ingredients). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the medicine blending of Baugh in the system of Shibata, in order to direct patients to a most effective compound (see Baugh, paragraph [0091]), and use powerful analytical and statistical techniques to relate to individuals with personalized medical conditions or needs (see Baugh, paragraph [0092]).
Regarding Claim 11, Shibata teaches an information processing method (Fig. 1) comprising: identifying a cultivation condition (microbiome types 105a) for cultivating a specific crude drug (Fig. 1, environmental data 103; paragraphs [0134] and [0139], crop data which is included in environmental data 103 includes specific type of plant to be grown; paragraph [0043], medicine), with use of a first model that associates a crude drug with a cultivation condition for cultivating the crude drug by a diversity-promoting cultivation method for promoting biodiversity and controlling an ecosystem to produce vegetation (recommendation engine 106 recommends agronomic program 107 based on environmental data 103, which includes specific type of plant, and microbiome type 105a; paragraphs [0161], supporting microbiome diversity; [0162], [0227], increasing biodiversity).
Shibata does not specifically teach a sensor device which transmits sensor data to a database, the sensor device being disposed in a farm field where the specific crude drug is cultivated and where the farm field is being cultivated using an open-field crop cultivation method in which plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings. It is noted that the Background section of Applicant’s Specification as filed defines, in paragraph [0002], synecoculture as a method “where plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings”. Further, Funabashi teaches, in Fig. 1, sensor devices 11 that acquire information in a synecoculture system (see paragraph [0004]) and transmit the information to a synecoculture database (Fig. 5, paragraphs [0158]-[0160]). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the sensor, database, and synecoculture system of Funabashi in the system of Shibata, In order to allow ecosystems to be actively utilized (see Funabashi, paragraph [0007]).
Shibata does not teach identifying a health factor offering a specific health benefit and including an herbal medicine, with use of a second model that associates a health benefit with a health factor offering the health benefit and including an herbal medicine; calculating a blending quantity of crude drugs that are to be blended to produce an herbal medicine which has ingredient compositions, resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription; and controlling blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit. However, Baugh teaches identifying a health factor offering a specific health benefit and including an herbal medicine, with use of a second model that associates a health benefit with a health factor offering the health benefit and including an herbal medicine (paragraph [0089], modeling software, targeted treatments, which are equated to health factor and herbal medicine, for preferred benefit or outcome, which is equated to health benefit; paragraph [0090], complex herbal medicines; paragraph [0091], personalized drug discovery model); calculating a blending quantity of crude drugs that are to be blended to produce an herbal medicine which have ingredient compositions (paragraph [0090], complex herbal medicines, paragraphs [0101]-[0104], blending ingredients into predetermined formulation), resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription (paragraph [0090], complex herbal medicines for a variety of indications from tinnitus to treating the common cold; paragraph [0091], advancement in patient treatment); and controlling blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit (paragraphs [0101]-[0104], blending ingredients into predetermined formulation). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the model of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063]), and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Shibata and Baugh do not specifically teach that the blending is performed depending on at least one of their production areas and cultivation condition. However, Watabe teaches, on page 9, that the amount of herbal medicines that would be included in a blend may vary based on where the herbal medicine was grown (e.g., in Japan versus in China), because the component ratio data may be different between medicines grown in different areas; this may also be equated to different cultivation conditions between different areas. It would have been obvious to one skilled in the art before the effective filing date of the invention to include the standardizing of the medicinal ingredients based on where the herbs were grown, as is taught in Watabe, in the system of Shibata and Baugh, because it is not easy to make the medicinal components of agricultural products grown in the open field constant (see Watabe, page 9.
Regarding Claim 12, Shibata teaches a non-transitory computer readable storage medium configured to cause a computer (Fig. 1) to function as: a first identification unit that identifies a cultivation condition (microbiome types 105a) for cultivating a specific crude drug (Fig. 1, environmental data 103; paragraphs [0134] and [0139], crop data which is included in environmental data 103 includes specific type of plant to be grown; paragraph [0043], medicine), with use of a first model that associates a crude drug with a cultivation condition for cultivating the crude drug by a diversity-promoting cultivation method for promoting biodiversity and controlling an ecosystem to produce vegetation (recommendation engine 106 recommends agronomic program 107 based on environmental data 103, which includes specific type of plant, and microbiome type 105a; paragraphs [0161], supporting microbiome diversity; [0162], [0227], increasing biodiversity).
Shibata does not specifically teach a sensor device which transmits sensor data to a database, the sensor device being disposed in a farm field where the specific crude drug is cultivated and where the farm field is being cultivated using an open-field crop cultivation method in which plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings. It is noted that the Background section of Applicant’s Specification as filed defines, in paragraph [0002], synecoculture as a method “where plowing, fertilizer, agricultural chemicals, or anything is not used except for seeds and seedlings”. Further, Funabashi teaches, in Fig. 1, sensor devices 11 that acquire information in a synecoculture system (see paragraph [0004]) and transmit the information to a synecoculture database (Fig. 5, paragraphs [0158]-[0160]). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the sensor, database, and synecoculture system of Funabashi in the system of Shibata, In order to allow ecosystems to be actively utilized (see Funabashi, paragraph [0007]).
Shibata does not teach a second identification unit that identifies a health factor offering a specific health benefit and including an herbal medicine, with use of a second model that associates a health benefit with a health factor offering the health benefit and including an herbal medicine; a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine which has ingredient compositions, resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription; and a controller that controls blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit. However, Baugh teaches a second identification unit that identifies a health factor offering a specific health benefit and including an herbal medicine, with use of a second model that associates a health benefit with a health factor offering the health benefit and including an herbal medicine (paragraph [0089], modeling software, targeted treatments, which are equated to health factor and herbal medicine, for preferred benefit or outcome, which is equated to health benefit; paragraph [0090], complex herbal medicines; paragraph [0091], personalized drug discovery model); a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine which have ingredient compositions (paragraph [0090], complex herbal medicines, paragraphs [0101]-[0104], blending ingredients into predetermined formulation), resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription (paragraph [0090], complex herbal medicines for a variety of indications from tinnitus to treating the common cold; paragraph [0091], advancement in patient treatment); and a controller that controls blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit (paragraphs [0101]-[0104], blending ingredients into predetermined formulation). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the model of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063]), and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Shibata and Baugh do not specifically teach that the blending is performed depending on at least one of their production areas and cultivation condition. However, Watabe teaches, on page 9, that the amount of herbal medicines that would be included in a blend may vary based on where the herbal medicine was grown (e.g., in Japan versus in China), because the component ratio data may be different between medicines grown in different areas; this may also be equated to different cultivation conditions between different areas. It would have been obvious to one skilled in the art before the effective filing date of the invention to include the standardizing of the medicinal ingredients based on where the herbs were grown, as is taught in Watabe, in the system of Shibata and Baugh, because it is not easy to make the medicinal components of agricultural products grown in the open field constant (see Watabe, page 9.
Regarding Claim 13, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 1. Shibata does not specifically teach wherein the controller controls the blending of the crude drugs by transmitting instructions to a blending device that performs the blending of the crude drugs. However, Baugh teaches wherein the controller controls the blending of the crude drugs by transmitting instructions to a blending device that performs the blending of the crude drugs (paragraphs [0101]-[0104], blending ingredients into predetermined formulation by kiosk or vending machine, which electronically controls blending device). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the blending of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063]), and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Claim(s) 2-3, 5, and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shibata in view of Funabashi, Baugh, and Watabe, further in view of Kaloudis et al (U.S. Pub. No. 2021/0365879, hereinafter “Kaloudis”).
Regarding Claim 2, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 1. Shibata further teaches wherein the first identification unit constructs the first model by retrieving a cultivation parameter corresponding to the cultivation condition for cultivating the specific crude drug, from cultivation parameters that are associated with cultivation of crude drugs and that include a parameter associated with the diversity-promoting cultivation method (paragraph [0139], environmental data 103 includes soil data and crop data, including desired crop type(s)).
Shibata does not teach retrieving the cultivation parameter according to a gradient method. However, Kaloudis teaches in paragraph [0041] that a model based on parameter fitting using a gradient descent method is well known. It would have been obvious to one skilled in the art before the effective filing date of the invention to use a gradient algorithm such as is taught in Kaloudis in the model of Shibata, because such parameter fitting algorithms are well known (see Kaloudis, paragraph [0041]).
Regarding Claim 3, Shibata in view of Funabashi, Baugh, Watabe, and Kaloudis teaches everything that is claimed above with respect to Claim 2. Shibata further teaches, wherein the parameter associated with the diversity-promoting cultivation method includes one or more pieces of information regarding a quantity of solar radiation, diversity of soil microorganisms, types of mixed vegetation, a height of a ridge, an amount of water in soil, and drainage of soil (paragraph [0139], environmental data 103 includes soil data and crop data, including desired crop type(s)).
Regarding Claim 5, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 1. Shibata does not teach wherein the second identification unit constructs the second model by retrieving a health parameter corresponding to the health factor offering the specific health benefit, from health parameters that are associated with health and that include a parameter associated with an herbal medicine. However, Baugh teaches wherein the second identification unit constructs the second model by retrieving a health parameter corresponding to the health factor offering the specific health benefit, from health parameters that are associated with health and that include a parameter associated with an herbal medicine (paragraph [0089], modeling software, targeted treatments (equated to health factor and herbal medicine) for preferred benefit or outcome (equated to health benefit); paragraph [0090], complex herbal medicines; paragraph [0091], personalized drug discovery model). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the model of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063]), and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Shibata in view of Baugh does not teach retrieving the health parameter according to a gradient method. However, Kaloudis teaches in paragraph [0041] that a model based on parameter fitting using a gradient descent method is well known. It would have been obvious to one skilled in the art before the effective filing date of the invention to use a gradient algorithm such as is taught in Kaloudis in the model of Shibata and Baugh, because such parameter fitting algorithms are well known (see Kaloudis, paragraph [0041]).
Regarding Claim 7, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 6. Shibata does not teach wherein the second identification unit constructs the second model by retrieving a health parameter corresponding to the health factor offering the specific health benefit, from the health parameters that include parameters associated with an herbal medicine and a lifestyle. However, Baugh teaches wherein the second identification unit (paragraph [0089], modeling software, targeted treatments (equated to health factor and herbal medicine) for preferred benefit or outcome (equated to health benefit); paragraph [0090], complex herbal medicines; paragraph [0091], personalized drug discovery model) constructs the second model by retrieving a health parameter corresponding to the health factor offering the specific health benefit, from the health parameters that include parameters associated with an herbal medicine and a lifestyle (paragraph [0090], herbal medicines; paragraphs [0098]-[0099], lifestyle factors and dietary supplements are linked to desired outcome by the model). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the model of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063]), and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Shibata in view of Baugh does not teach retrieving the health parameter according to a gradient method. However, Kaloudis teaches in paragraph [0041] that a model based on parameter fitting using a gradient descent method is well known. It would have been obvious to one skilled in the art before the effective filing date of the invention to use a gradient algorithm such as is taught in Kaloudis in the model of Shibata and Baugh, because such parameter fitting algorithms are well known (see Kaloudis, paragraph [0041]).
Claim(s) 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shibata in view of Funabashi, Baugh, and Watabe, further in view of Gallant (U.S. Pub. No. 2004/0242454).
Regarding Claim 9, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 8. Shibata does not teach wherein the blending quantity calculation unit calculates the blending quantity of the crude drugs such that the beneficial ingredients are equal to or above the reference value of the beneficial ingredients and the toxic ingredients are equal to or below the reference value of the toxic ingredients, and such that a change of the specific health benefit with respect to the blending quantity of the crude drugs is maximized. However, Baugh teaches wherein the blending quantity calculation unit calculates the blending quantity of the crude drugs such that the beneficial ingredients are equal to or above the reference value of the beneficial ingredients and the toxic ingredients are equal to or below the reference value of the toxic ingredients, and such that a change of the specific health benefit with respect to the blending quantity of the crude drugs is maximized (paragraphs [0089]-[0094], complex herbal medicines for preferred outcome; paragraphs [0101]-[0104], any number of ingredients can be used to blend into a predetermined formulation; the blended predetermined formulation would be blended to have specific amounts (i.e. equal to reference values) of each of the ingredients, whether they are toxic or non-toxic ingredients). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the medicine blending of Baugh in the system of Shibata, in order to direct patients to a most effective compound (see Baugh, paragraph [0091]), and use powerful analytical and statistical techniques to relate to individuals with personalized medical conditions or needs (see Baugh, paragraph [0092]).
Shibata in view of Baugh does not teach calculating the blending quantity of the crude drugs by linear programming or non-linear programming, such that an objective function representing a change of the specific health benefit with respect to the blending quantity of the crude drugs is maximized. However, Gallant teaches calculating the blending quantity of the crude drugs (paragraph [0004], mixture of drugs) by linear programming or non-linear programming (paragraph [0007], linear or non-linear programming), such that an objective function representing a change of the specific health benefit with respect to the blending quantity of the crude drugs is maximized (paragraph [0009], maximize objective function of expected effectiveness against a target). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the linear and non-linear programming, and objective function, of Gallant in the system of Shibata and Baugh, in order to allow creation of a drug therapy at a lower cost, with greater effect on a desired biological target, and with less severe side effects (see Gallant, paragraph [0020]).
Regarding Claim 10, Shibata in view of Funabashi, Baugh, and Watabe teaches everything that is claimed above with respect to Claim 9. Shibata does not teach wherein the objective function is obtained on a basis of a relation between herbal medicines and health benefits, the relation being acquired by construction of the second model. However, Baugh teaches a relation between herbal medicines and health benefits, the relation being acquired by construction of the second model (paragraphs [0089]-[0094], modelling software links complex herbal medicines to preferred outcome). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the model of Baugh in the system of Shibata, in order to help a consumer better identify consumer goods and services that have greater efficacy (see Baugh, paragraph [0063], and in order to identify new compounds of interest (see Baugh, paragraph [0088]).
Shibata in view of Baugh does not teach an objective function obtained on a basis of a relation between herbal medicines and health benefits. However, Gallant teaches wherein the objective function is obtained on a basis of a relation between medicines and health benefits, the relation being acquired by construction of the second model (paragraph [0009], maximize objective function of expected effectiveness against a target). It would have been obvious to one skilled in the art before the effective filing date of the invention to use an objective function such as is taught in Gallant in the system including herbal medicines that is taught in Shibata and Baugh, in order to allow creation of a drug therapy at a lower cost, with greater effect on a desired biological target, and with less severe side effects (see Gallant, paragraph [0020]).
Prior Art of Record
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure.
Yin (CN-102327297-A) teaches, in claims 1 and 4, determining a quality index and a mixing proportion for an herbal medicine based on producing area.
Chuang (CA-2578181-A1 teaches, in paragraph [0062], that performing quality control for herbal preparations based on location and condition of cultivation.
Response to Arguments
Applicant's arguments filed 2/20/2026 have been fully considered but they are not persuasive.
Regarding the 101 rejection of the Claims, the Examiner disagrees that the amended claim recite additional specific features which do not fall within the alleged judicial exception and which recite significantly more than any alleged abstract idea. It is noted that Applicant merely alleges this on pages 9-10, and provides no arguments. Updated 101 rejections of the amended Claims are provided above.
Regarding the prior art rejections of the Claims, Applicant argues that the combination of Baugh and Watabe does not teach “a blending quantity calculation unit that calculates a blending quantity of crude drugs that are to be blended to produce an herbal medicine which has ingredient compositions depending on at least one of their production areas and cultivation condition, resulting in a desired health benefit that matches or exceeds that of a blending method described in a classic prescription; and a controller that controls blending of the crude drugs that are to be blended to produce the herbal medicine based on the blending quantity calculated by the blending quantity calculation unit”. The Examiner disagrees. Watabe teaches adjusting quantities of medicinal components based on production area and cultivation condition, which may be incorporated into the blending quantity determination of Baugh, i.e. the blending quantity of an ingredient in the system of Baugh may be adjusted based on the teachings of Watabe. The blended herbal medicine output by the combination of Baugh and Watabe would have “ingredient compositions depending on at least one of their production areas and cultivation condition”. Updated rejections of the Claims are provided above. It is noted that the Yin and Chuang references (see the Prior Art of Record section, above) also teach preparing herbal medicines based on cultivation condition and/or production area.
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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/CYNTHIA L DAVIS/Examiner, Art Unit 2857
/SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857