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 a final rejection
Claims 1, 13, 23, 24 are pending
Claims 2-12, 14-22 were cancelled
Claims 1, 13 were amended
Claim 23, 24 was added
Claims 1, 13, 23, 24 are rejected under 35 USC § 101
Claims 1, 13, 23, 24 are rejected under 35 USC § 112
Priority
Acknowledgement is made of Applicant’s claim for a foreign priority date of 8-31-2021
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 4-24-2023, is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1. 13, 23-24 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 pre-AIA the applicant regards as the invention.
Regarding claims 1 and 13
Claims 1 and 13 recites the limitation "the first prediction model/step predicts that a subject dog will not contract/develop the disease" in the third limitation of claim 1 and the fifth limitation of claim 13. There is insufficient antecedent basis for this limitation specific to the “disease of the dog” in the claim.
Furthermore it is not clear what applicant means by “wherein the first prediction model predicts that a subject dog will not contract the disease, when, inborn data about genetic information of the dog in which the dog possesses a mutation in the MDR1 gene and no other genetic mutations, is accepted”. Examiner is unclear whether the disease of the dog refers to a specific illness that the dog will not develop based on the dog’s inborn mutation of the MDR1 gene or whether the “disease” refers to ivermectin sensitivity as a result of the mutation of the MDR1 gene (See page 11, line 20 in the specification). The Examiner interprets the claim as the dog not displaying any disease (since the gene is a silent mutation or benign variant) as long as ivermectin is not administered to the dog.
Since claims 23 is dependent on claim 1 and claim 24 is dependent on claim 13 all claims 1, 13, 23, 24 are rejected under 35 U.S.C. 112(b) or 35 U.S.C 112 (pre AIA ).
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, 13, 23, 24 are not patent eligible because the claimed invention is directed to an abstract idea without significantly more.
Analysis
First, claims are directed to one or more of the following statutory categories: a process, a machine, a manufacture, and a composition of matter. Regarding claims 1, 13, 23, 24 the claims recite an abstract idea of predicting the occurrence of future disease in animals.
Independent Claim 1 is rejected under 35 U.S.C 101 based on the following analysis.
-Step 1 (Does the claim fall within a statutory category? YES): claim 1 recites an apparatus to predict the occurrence of future disease in animals.
-Step 2A Prong One (Does the claim fall within at least one of the groupings of abstract ideas?: YES): The claimed invention:
A prediction apparatus comprising:
A first prediction model … which predicts occurrence of future disease or disease-prone state an animal based on inborn data including one or more selected from the group consisting of genetic, pedigree, and appearance information of the
A second prediction model .. which modifies…, occurrence of future disease or future disease-prone state in an animal … based on acquired data including one or more selected from the group consisting of information on diet, bacterial flora, body, living environment, diagnosis/medical checkup/examination, contracted disease, and medical treatment of the
wherein the first prediction model predicts that a subject dog will not contract the disease, when, inborn data about genetic information of the dog in which the dog possesses a mutation in the MDR1 gene and no other genetic mutations, is accepted, and
the second prediction model modifies the prediction by first prediction model and predicts that the dog will develop exercise-induced ataxia caused by heartworm, when acquired data about the dog's living environment in which the dog is kept outdoors is accepted
belonging to the grouping of mental processes under concepts performed in the human mind (including an observation, evaluation, judgement, opinion) as it recites predicting the occurrence of future disease in animals. Alternatively it belongs to the grouping of mathematical concepts including mathematical relationships as it recites predicting the occurrence of future disease in animals. (refer to MPP 2106.04(a)(2)). Accordingly this claim recites an abstract idea.
-Step 2A Prong Two (Are there additional elements in the claim that imposes a meaningful limit on the abstract idea? NO). Claim 1 recites:
executed by a processor … by using a preset program
executed by a processor … by using a machine learning model.
machine learning model;
Amounting to no more than mere instructions to apply the exception using a generic computer, or merely using a computer as a tool to implement the abstract idea as even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. (refer to MPEP 2106.05(f)). Support for this can be found in the specification, paragraphs (Page 26, lines 3-25, Page 27, lines 8-17). Accordingly, the claim as a whole does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
-Step 2B (Does the additional elements of the claim provide an inventive concept?: NO. As discussed previously with respect to Step 2A Prong Two, claim 1 recites:
executed by a processor … by using a preset program
executed by a processor … by using a machine learning model.
machine learning model;
Amounting to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)) Support for this can be found in the specification, paragraphs (Page 26, lines 3-25, Page 27, lines 8-17). Accordingly, the additional elements alone, and in combination do not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
Independent Claim 13 is rejected under 35 U.S.C 101 based on the following analysis.
-Step 1 (Does the claim fall within a statutory category? YES): claim 13 recites a method to predict the occurrence of future disease in animals.
-Step 2A Prong One (Does the claim fall within at least one of the groupings of abstract ideas?: YES): The claimed invention:
A prediction method comprising:
a step of … obtaining inborn data including one or more selected from the group consisting of genetic, pedigree, and appearance information of an animal;
a first prediction step…
a step of … obtaining acquired data including one or more selected from the group consisting of information on diet, intestinal bacterial flora, body, living environment, diagnosis/medical checkup/examination, contracted disease, and medical treatment of theanimal; and
a second prediction step … modifies the prediction of first prediction step, …, the occurrence of the future disease or disease-prone state based on the acquired data.
wherein, when data that subject dog possesses a mutation in the MDR1 gene and no other genetic mutations are confirmed is obtained in the step of a computer obtaining inborn data, then in the first prediction step, computer predicts that the dog will not develop the disease,
then in the step of the computer obtaining acquired data, data indicating that the dog is kept outdoors is obtained as information about living environment,
then in the second prediction step, computer modifies the prediction of the first prediction step and predicts that the dog will develop ataxia caused by heartworm
belonging to the grouping of mental processes under concepts performed in the human mind (including an observation, evaluation, judgement, opinion) as it recites predicting the occurrence of future disease in animals. Alternatively it belongs to the grouping of mathematical concepts including mathematical relationships as it recites predicting the occurrence of future disease in animals. (refer to MPP 2106.04(a)(2)). Support for this can be found in the specification, paragraphs (Page 26, lines 3-25, Page 27, lines 8-17). Accordingly this claim recites an abstract idea.
-Step 2A Prong Two (Are there additional elements in the claim that imposes a meaningful limit on the abstract idea? NO). Claim 13 recites:
using a preset program;
using a machine learning model;
Computer;
machine learning model;
Amounting to no more than mere instructions to apply the exception using a generic computer, or merely using a computer as a tool to implement the abstract idea as even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. Support for this can be found in the specification, paragraphs (Page 26, lines 3-25, Page 27, lines 8-17). Accordingly, the claim as a whole does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
-Step 2B (Does the additional elements of the claim provide an inventive concept?: NO. As discussed previously with respect to Step 2A Prong Two, claim 13 recites:
using a preset program;
using a machine learning model;
Computer;
machine learning model;
Amounting to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)) Support for this can be found in the specification, paragraphs (Page 26, lines 3-25, Page 27, lines 8-17). Accordingly, the additional elements alone, and in combination do not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
Dependent Claims:
Step 2A Prong One: The following dependent claims recites additional limitations that further define the abstract idea of predicting the occurrence of future disease in animals. The claim limitations include:
Claims 23, 24: wherein the .. model has learned that the probability of heartworm disease onset is high in dogs kept outdoors.
Step 2A Prong Two (Are there additional elements in the claim that imposes a meaningful limit on the abstract idea? NO). The following dependent claims recite mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, the claims as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims include:
Claims 23, 24: machine learning model
Step 2B (Does the additional elements of the claim provide an inventive concept?: NO). As discussed previously with respect to Step 2A Prong Two, the following dependent claims recite mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, the claim does not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible. The claims include:
Claims 23, 24: machine learning model
Claim Rejection
Due to the 112 (b) rejection no reference or combination of references could be found to reject the set of claims since the claims are indefinite and not understood by the examiner.
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure, and is listed in the attached form PTO-892 (Notice of References Cited). Unless expressly noted otherwise by the Examiner, all documents listed on form PTO-892 are cited in their entirety.
Koizumi (JP 2022135180 A) - DISEASE PREDICATION SYSTEM, PREMIUM CALCULATION SYSTEM AND DISEASE PREDICTION METHOD – teaches: a disease prediction system, a learnt model generation method and a disease prediction method capable of predicting a possibility that animals will be affected by disease in the future in a simple way.SOLUTION: A disease prediction system comprises reception means 31 of receiving occupancy data and diversity data of intestinal microbiota of animals other than humans, and determination means 11 of predicting and determining whether the animals will be affected by disease from the occupancy rate data and diversity data of the intestinal microbiota of the animals input to the reception means 31 using a learnt model. The determination means performs learning by using the occupancy data and diversity data of the intestinal microbiota of animals other than humans and the presence or absence of disease within a predetermined period from the acquisition time of the occupancy data and diversity data of the intestinal microbiota of the animals as teacher data; uses input as the occupancy data and diversity data of the intestinal microbiota of the animals; and uses output as predictive determination as to whether the animals will be affected by disease.
Fukuda (US 20210151185 A1) - INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING PROGRAM – teaches: An information processing device includes a CPU and a storage unit that stores a command executable by the CPU. The CPU acquires breed information representing a breed of a pet and symptom information on a symptom of the pet, predicts a disease or external injury suffered by the pet based on the acquired breed information and symptom information, and extracts an animal hospital that is able to handle the disease or external injury of the pet based on a prediction result.
Kollanda (US 20240221950 A1) - MULTI-MODAL INPUT PROCESSING – teaches: improvements in multi-modal and multi-sensor diagnostic devices, that utilize machine learning algorithms to diagnose patients based on data from different sensor types and formats. Current machine learning algorithms that classify a patient's diagnosis focus on one modality of data output from one type of sensor or device. This is because, among other reasons, it is difficult determine which modalities or features from different modalities will be most important to a diagnosis, and also very difficult to identify an algorithm that can effectively to combine them to diagnose health disorders.
Vaidya (US 20230326582 A1) - COMBINATION OF RADIOMIC AND PATHOMIC FEATURES IN THE PREDICTION OF PROGNOSES FOR TUMORS – teaches: using a first machine learning model to generate a first medical prediction associated with a lesion in a medical scan using one or more intra-lesional radiomic features associated with the lesion and the one or more peri-lesional radiomic features associated with a peri-lesional region around the lesion. A second machine learning model is used to generate a second medical prediction associated with the lesion using one or more pathomic features associated with the lesion. A combined medical prediction associated with the lesion is generated using the first medical prediction and the second medical prediction as inputs to a third model.
Matsumoto (JP 2023006876 A) teaches: a disease incidence prediction system and a disease incidence prediction method for predicting a possibility of incidence of a specific disease of an animal by a simple method, by Providing a disease incidence prediction system comprising reception means for receiving information on presence or absence of bacteria belonging to family Fusobacteriaceae and/or presence or absence of bacteria belonging to family Veillonellaceae in a sample obtained from an animal; and determining means for predicting and determining a possibility of incidence of the animal with keratoconjunctivitis sicca from the information input to the reception means of the presence or absence of bacteria belonging to family Fusobacteriaceae and/or the presence or absence of bacteria belonging to family Veillonellaceae.
Response to Arguments
Applicant's arguments filed 12-10-2025, have been fully considered but not found
persuasive.
Applicant amended independent claims 1, 13, cancelled claims 2-12, 14-22 and added claim 23, 24 as posted in the above analysis with additions underlined and deletions as .
In response to applicant's arguments regarding claim rejection under 35 U.S.C § 101.
Several steps are taken in the analysis as to whether an invention is rejected under 101. The first step is to determine if the claim falls within a statutory category. In this case it does for claims 1 and 13 since the claims recite a method, and apparatus to predict the occurrence of future disease in animals.
The second step under 2A prong one is to determine if the claims recite an abstract idea, which would be the case if the invention can be grouped as either: a) mathematical concepts; (b) mental processes; or (c) certain methods of organizing human activity (encompassing (i) fundamental economic principles, (ii) commercial or legal interactions or (iii) managing personal behavior or relationships or interactions between people). The current invention is classified as an abstract idea since it may be grouped as a mental process. Alternatively it may be grouped as mathematical concepts including mathematical relationships as it recites predicting the occurrence of future disease in animals.
The third step under 2A Prong Two is to determine if additional elements in the claim imposes a meaningful limit on the abstract idea in order to integrate it into a practical idea. The current invention does not represent a practical idea since the additional elements amount to mere instructions to implement an abstract idea on a computer, or merely use a generic computer as a tool to implement the abstract idea.
the fourth step under 2B is to determine if additional elements of the claim provide an inventive concept. An invention may be classified as an inventive concept if a computer-implemented processes is determined to be significantly more than an abstract idea (and thus eligible), where generic computer components are able in combination to perform functions that are not merely generic, and non-conventional even if generic computer operations on a generic computing device is used to implement the abstract idea.
Step 2A Prong ONE
The Applicant offers no argument against independent claims 1, 13 reciting an abstract idea as posted in the Office Action.
The Examiner explains that The method to select the abstract idea is to strip the additional elements from the claims. As seen below the recited boldened words constitute the abstract idea after stripping the un-boldened additional elements of amended limitation of claim 1:
a first prediction model executed by a processor which predicts, by using a preset program, occurrence of future disease or disease-prone state an animal based on inborn data including one or more selected from the group consisting of genetic, pedigree, and appearance information of the
and a second prediction model executed by a processor, which modifies, byoccurrence of future disease or future disease-prone state in an animal based on acquired data including one or more selected from the group consisting of information on diet, bacterial flora, body, living environment, diagnosis/medical checkup/examination, contracted disease, and medical treatment of the.
wherein the first prediction model predicts that a subject dog will not contract the disease, when, inborn data about genetic information of the dog in which the dog possesses a mutation in the MDR1 gene and no other genetic mutations, is accepted, and
the second prediction model modifies the prediction by first prediction model and predicts that the dog will develop exercise-induced ataxia caused by heartworm, when acquired data about the dog's living environment in which the dog is kept outdoors is accepted.
Seen below the recited boldened words constitute the abstract idea after stripping the un-boldened additional elements of amended limitation of claim 13:
a step of a computer obtaining inborn data including one or more selected from the group consisting of genetic, pedigree, and appearance information of an animal;
a first prediction step wherein the computer predicts the occurrence of a future disease or disease-prone state in th by using a preset program;
a step of the computer obtaining acquired data including one or more selected from the group consisting of information on diet, intestinal bacterial flora, body, living environment, diagnosis/medical checkup/examination, contracted disease, and medical treatment of the; and
a second prediction step wherein the computer, modifies the prediction of first prediction step using a machine learning model, the occurrence of the future disease or disease-prone state based on the acquired data.
wherein, when data that subject dog possesses a mutation in the MDR1 gene and no other genetic mutations are confirmed is obtained in the step of a computer obtaining inborn data, then in the first prediction step, computer predicts that the dog will not develop the disease,
then in the step of the computer obtaining acquired data, data indicating that the dog is kept outdoors is obtained as information about living environment,
then in the second prediction step, computer modifies the prediction of the first prediction step and predicts that the dog will develop ataxia caused by heartworm
The selected abstract idea (boldened limitations) of claims 1 and 13 can be implemented by pencil and paper and thus belong to the grouping of mental processes under concepts performed in the human mind (including an observation, evaluation, judgement, opinion) as it recites predicting the occurrence of future disease in animals. Alternatively it belongs to the grouping of mathematical concepts including mathematical relationships as it recites predicting the occurrence of future disease in animals. (refer to MPP 2106.04(a)(2)). Accordingly independent claims 1 and 7 recite an abstract idea.
Step 2A Prong TWO
The Applicant argues that the invention encompassed by the amended claims 1 and 13 enables prediction of whether a dog will develop a disease based on seemingly unrelated information, such as specific genetic mutations and living environment, thereby bringing progress to the relevant technical field. Therefore, the invention described in the amended claims integrated into a practical application.
The Examiner disagrees since the Applicant’s arguments are not persuasive. The Applicant’s arguments pertain to a colloquial interpretation of a practical application which does not correspond to additional elements imposing a meaningful limit on the abstract idea required to deem the invention a practical application.
Neither claim 1 or 13 recite additional elements that impose a meaningful limit on the abstract idea:
Claims 1: recites the following additional elements:
executed by a processor … by using a preset program
executed by a processor … by using a machine learning model.
machine learning model;
Claim 13: recites the following additional elements:
using a preset program;
using a machine learning model;
computer.
machine learning model;
The additional elements as recited above amount to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Support for this can be found in the specification, paragraphs (Page 26, lines 3-25, Page 27, lines 8-17). Accordingly, the claim as a whole does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The use of a processor that uses a program to predict future disease incidence from innate data of animals or a machine-learning model which modifies the prediction of future disease incidence from acquired data is not enough to classify the claims as integrated into a practical application. In order to integrate the abstract idea into a practical application the additional elements should be shown to impose a meaningful limit on the abstract idea. A colloquial interpretation of a practical application is not enough.
In order to integrate the abstract idea into a practical idea the Applicant could demonstrate at least one of the conditions enumerated below applies:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo
The Applicant has not demonstrated any of the above listed conditions.
Regarding Step 2B
Similar to the analysis under Step 2A Prong Two, the additional elements amount to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Support for this can be found in the specification, paragraphs (Page 26, lines 3-25, Page 27, lines 8-17). Accordingly, the claim does not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
In order evaluate whether the claim recites additional elements that amount to an inventive concept what could be shown is:
Adding a specific limitation (unconventional other than what is well-understood, routine, conventional (WURC) activity in the field - see MPEP 2106.05(d)
The Applicant has not demonstrated the above listed condition.
As a result, the Examiner restates the rejection of the invention under 35 USC §101.
In response to applicant's arguments regarding claim rejection under 35 U.S.C § 103.
The applicant's arguments with respect to claims 1, 3-10, 12-13, 15, 17-18, 20-21 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
As a result the Examiner restates the rejection of the invention under 35 USC §103
Claim 23, 24 was added
Claims 1, 13, 23, 24 are rejected under 35 USC § 101
Claims 1, 13, 23, 24 are rejected under 35 USC § 112
For reasons of record and as set forth above, the examiner maintains the rejection of claims 1, 13, 23, 24 as being directed to a judicial exception without significantly more, and thereby being directed to non-statutory subject matter under 35 USC §101. In addition claims 1, 13, 23, 24 are rejected under 35 USC §112 based on claim indefiniteness and insufficient antecedent basis. In reaching this decision, the Examiner considered all evidence presented and all arguments actually made by Applicant.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PIERRE L MACCAGNO whose telephone number is (571)270-5408. The examiner can normally be reached M-F 8:00 to 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid can be reached at (571)270-1813. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PIERRE L MACCAGNO/Examiner, Art Unit 3687
/STEVEN G.S. SANGHERA/Primary Examiner, Art Unit 3684