DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/11/2025 has been entered.
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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Response to Amendment
In the amendment dated 12/11/2025, the following has occurred: Claims 1, 8 and 10 have been amended; Claims 2, 3, 7, and 11 have been canceled.
Claims 4, 9, and 12 – 17 have been previously canceled.
Claims 1 , 5 , 6, 8, and 10 are pending.
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 , 5 , 6, 8, and 10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The claim(s) recite(s) subject matter within a statutory category as a process (claims 10), machine (claims 1, 5, and 6) which recite steps abstract idea steps of
receiving
(1) a diversity index of the microbiota in the animal samples,
(2) the occupancy rate of each bacterial family, including one or more occupancy rates selected from the group consisting of the occupancy rate of the Coprobacillaceae family, the occupancy rate of the Enterococcaceae family, and the occupancy rate of the Peptostreptococcaceae family, and
predict and determine whether the animal will be afflicted with a disease from the diversity index of (1) and occupancy rate of (2);
occupancy rate of each bacterial family, including one or more occupancy rates selected from the group consisting of the occupancy rate of the Coprobacillaceae family, the occupancy rate of the Enterococcaceae family, and the occupancy rate of the Peptostreptococcaceae family in the intestinal flora of the animal or label set based on thereof, and
a presence or absence of disease affliction within a predetermined period of time from a time of acquisition of the occupancy rate data and diversity data of the intestinal flora.
These steps of claims 1 , 5 , 6, 8, and 10, as drafted, under the broadest reasonable interpretation, includes mathematical concepts. The claims recite the steps of first inputting data or acquiring data. Second, the claims that process that data using an algorithm. The algorithm and the training of the algorithm are mathematical processes. The step of determining an insurance premium is using the predictive results as input into another algorithm.
It should be emphasized that there is no practical application. The result of the invention is data. Even if that data is later claimed to be displayed, although not currently done, then that would be considered an extra solution activity.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 5 and 6, reciting particular aspects of how insurance premium calculation may be performed in the mind but for recitation of generic computer components).
This judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception (such as recitation of causing a computer amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f))
add insignificant extra-solution activity to the abstract idea (such as recitation of receiving or acquiring occupancy rate data amounts to mere data gathering, see MPEP 2106.05(g))
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 5 and 6, additional limitations which amount to invoking computers as a tool to perform the abstract idea, claims). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field of use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as claims 1 , 5 , 6, 8, and 10; training, predicting, and determining, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii))
Additional Elements
Computer or system including processor – page 17, lines 9 – 14 “a personal computer, a tablet terminal, and the like are mentioned”
Machine learning – page 11, lines 9 – 15, “Artificial intelligence may be either a general-purpose type or a specialized type, may be any of a deep neural network, a convolutional neural network, or the like, and published software can be used” page 18, lines 16 – 25 XGBoost, CatBoost, a deep neural network… and page 12, lines 2 – 6, “As published machine learning algorithms, for example, XGBoost, CatBoost, and LightGBM are mentioned.”
Training – page 11, line 21 – page 12, line 1 For example, the Deep Learning GPU Training System (DIGITS) published by NVIDIA can be used.”
DNA Sequencer – page 8, lines 11, 12 or page 9, lines 18 “ a sequencer such as NGS” page 10, lines 4, 5, “An example of amplicon analysis (bacterial flora analysis) of the 16S rRNA gene using NGS (next-generation sequencer) is specifically described.”
processor for calculating the below (1) and (2), page 9, lines 16 – 25 “Occupancy rate data and diversity data of intestinal flora can be measured using a known metagenomic analysis method or bacterial flora analysis method, such as amplicon sequencing using a sequencer such as NGS. For example, there is mentioned a method in which a sample such as feces is collected from an animal, and DNA and RNA base sequence information of any organisms contained in the sample is analyzed using a next-generation sequencer to identify the organisms contained in the sample.”
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 5 and 6, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, determining insurance premiums or calculating occupancy rate, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii)). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Response to Arguments
Applicant’s arguments, see Rejection under 35 U.S.C. § 103, filed 12/11/2025, with respect to claims 1-3, 5, 6, 10, and 11 have been fully considered and are persuasive. The 35 U.S.C. § 103 rejections of claims 1-3, 5, 6, 10, and 11 has been withdrawn.
Applicant's arguments filed 12/11/2025 have been fully considered but they are not persuasive.
Rejection under 35 U.S.C. § 101
The Applicant states, “Consequently, the present system reads microbial community base sequence data from samples such as animal feces, calculates diversity index and occupancy rates of specified bacterial families, and predicts whether the animal is afflicted with a disease using a trained model based on those diversity indices and occupancy rates.” The Examiner believes that the claimed math to determine a value is why the invention is an abstract idea.
The Applicant states, “Furthermore, the prediction system of the claims is characterized in that the trained model is generated by machine learning using, as training data, diversity indices of gut microbiota from animals other than humans or a label set…” The Examiner notes that this is more of a mathematical chain.
The Applicant states, “As such, the prediction system of the invention as encompassed by the amended claims does not correspond to mental processes or general-purpose computers.” The Examiner agrees and this rejection was removed.
The Applicant states, “Moreover, as a whole, the prediction system of the present claims is integrated into a practical application. The corrected prediction system can predict whether an animal will contract a disease based on animal-derived samples such as feces. A system capable of predicting disease onset from animal-derived samples is not common…” The Examiner that the result of the invention is a value with a potential application and not a practical application. The use of the value is not claimed.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Neal R Sereboff whose telephone number is (571)270-1373. The examiner can normally be reached M - T, M - F 8AM - 6PM.
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/NEAL SEREBOFF/
Primary Examiner
Art Unit 3626