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 .
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.
Election/Restrictions
Applicant’s election without traverse of Species A1(claim 3) and B2 (claims 9-10) in the reply filed on 12/22/2025 is acknowledged. Claims 4-5, 8 and 11-12 of species not elected are withdrawn.
Status of claims
Claims 1-20 are pending.
Claims 4-5, 8 and 11-12 are withdrawn.
Claims 1-3 and 18-19 are amended.
Claim 1 is an independent claim.
Claims 1-3, 6-7, 9-10 and 13-20 are examined on the merits.
Priority
As detailed on the 08/27/2025 filing receipt, this application claims domestic priority to as early as 07/14/2023.
Information Disclosure Statement
The Information Disclosure Statements filed on 08/19/2025 and 09/05/2025 are in compliance with the provisions of 37 CFR 1.97 and have been considered in full. A signed copy of list of references cited from the IDS is included with this Office Action.
Drawings
The drawings filed 08/18/2025 are accepted.
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, 6-7, 9-10 and 13-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Analysis of claims in Step 1.
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
Independent claim 1 is directed to a 101 process, here a "method for modifying a nutritional product recommendation for a non-human animal subject," with process steps such as "retrieving…, receiving…"
[Step 1: claims 1-3, 6-7, 9-10 and 13-20: YES]
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Mental processes recited include:
Claim 1 recites: "(c) processing said activity data or said behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop another condition that differs from said condition in (a); and (d) producing a modified nutritional product recommendation by modifying said initial nutritional product recommendation based, at least in part, on said activity data or said behavioral data processed in (c)," are acts of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Claim 3 recites: "wherein said modifying said initial nutritional product recommendation comprises modifying an amount of a said initial nutritional product or an amount of one or more ingredients in said initial nutritional product." Modifying nutritional product recommendation is an act of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Claim 18 recite: "(f) processing said new activity data or said new behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop said another condition or a third condition that differs from said condition in (a) or said another condition in (c); and(g) modifying said initial modified nutritional product recommendation based, at least in part, on said new activity data or said new behavioral data processed in (f)." are acts of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Mathematical concepts recited include:
Claim 20 recites: "processing is performed by a machine learning algorithm." Machine learning algorithms are mathematical concepts and/or formulas.
Claims 1 and 18 are involved with determining qualitative or quantitative measures, predicting whether said non-human animal subject is likely to have or develop another condition and producing a modified nutritional product recommendation; claim 3 is involved with modifying nutritional product recommendation; These claim elements are involved with acts of evaluating, analyzing, observing and judging data as indicated above. Acts of evaluating and analyzing data could be practically performed in the human mind and/or with pen and paper because they merely require making observations, evaluations, judgments, and opinions (See MPEP 2106.04(a)(2) subsection III). Therefore, under the broadest reasonable interpretation, the indicated claims above can be practically carried out in the human mind or with pen and paper as claimed, which falls under the "Mental processes" grouping of abstract ideas.
Claim 20 recites mathematical concepts and formulas as discussed above. Machine learning algorithms are mathematical concepts and/or formulas that falls under the “mathematical concepts” grouping of abstract ideas.
As such, claims 1-3, 6-7, 9-10 and 13-20 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). The above indicated judicial exceptions are not integrated into a practical application because the claims do not recite an additional elements that apply, rely on or use the judicial exception in such a manner to amount to integration into a practical application. For example, there are no limitations that reflect an improvement to technology or applies or uses the recited judicial exception in some other meaningful way. Rather, the instant claims recite additional elements that equate to mere instructions to implement an abstract idea or insignificant extra solution activity. Specifically, the instant claims recite the following additional elements:
Claim 1 recites "(a) retrieving, from a database, a data set associated with an initial nutritional product recommendation to improve, ameliorate, or prevent a condition in said non- human animal subject, wherein said initial nutritional product recommendation is based, at least in part, on genetic data and phenotype data of said non-human animal subject; (b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject " and "(d) producing a modified nutritional product recommendation…"
Claim 6 recites “wherein said activity tracking device is a collar.”.
Claim 7 recites: " wherein said collar is a Global Positioning System (GPS)-connected collar"
Claim 18 recites: "(e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device;"
Claim 19 recites: "displaying a notification comprising said modified nutritional product recommendation on a graphical user interface of a personal electronic device of a user."
The elements of claims 1 and 18 as indicated above equate to insignificant extra solutional activities of data gathering and outputting. Data gathering serves as input to the recited judicial exception in the claims. Claim 1 recites a “tracking device,” claim 6 recites a “tracking device is a collar" and claim 10 recites " said collar is a Global Positioning System (GPS)-connected collar." The tracking device, collar and GPS connected collar are used to collect data that contributes nominally of insignificantly to the execution of the claimed method. As stated in (MPEP 2106.05(b)(III), “Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not integrate a judicial exception or provide significantly more.” Claim 19 recites a notification comprising said modified nutritional product recommendation on a graphical user interface of a personal electronic device of a user, which equates to outputting via generic computer components. Limitations that equate to mere data gathering and outputting via generic computer components, such as receiving data at a computer or outputting data via a graphic display device, amount to insignificant extra-solution activity as set forth by the courts in Mayo, 566 U.S. at 79, 101 USPQ2d at 1968 and OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Claim 19 also invokes the computer components merely as tools to execute the abstract idea. The use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. (see MPEP 2106.05(f)). As such, as currently recited, the claims do not appear to recite an improvement to technology or apply or use the recited judicial exception in some other meaningful way. Therefore, claims 1-3, 6-7, 9-10 and 13-20 are directed to an abstract idea (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to well-understood, routine and conventional activities, insignificant extra-solution activity or mere instructions to implement the abstract idea on a generic computer. The instant claims recite the following additional elements:
Claim 1 recites "(a) retrieving, from a database, a data set associated with an initial nutritional product recommendation to improve, ameliorate, or prevent a condition in said non- human animal subject, wherein said initial nutritional product recommendation is based, at least in part, on genetic data and phenotype data of said non-human animal subject; (b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject " and "(d) producing a modified nutritional product recommendation…"
Claim 6 recites “wherein said activity tracking device is a collar.”.
Claim 7 recites: "wherein said collar is a Global Positioning System (GPS)-connected collar"
Claim 18 recites: "(e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device;"
Claim 19 recites: "displaying a notification comprising said modified nutritional product recommendation on a graphical user interface of a personal electronic device of a user."
The additional elements indicated above do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. The limitations equate to mere data gathering and outputting activities, which are insignificant extra solutional activities. As discussed, limitations that equate to mere data gathering and outputting via generic computer components, such as receiving data at a computer or outputting data via a graphic display device, amount to insignificant extra-solution activity as set forth by the courts in Mayo, 566 U.S. at 79, 101 USPQ2d at 1968 and OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). As explained by the Supreme Court, the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional. (see MPEP 2106.05(g)). Also, limitations that equate to mere data gathering and outputting via generic computer components, such as receiving data at a computer or outputting data, amount to insignificant extra-solution activity as set forth by the courts in Mayo, 566 U.S. at 79, 101 USPQ2d at 1968 and OIP Techs., Inc, v, Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). The use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more as identified by the courts in Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Also, the use of GPS tracking collar to collect activity data is well-known and conventional as disclosed by Dore ("Review of GPS collar deployments and performance on nonhuman primates." Primates 61.3 (2020): 373-387.; cited on the attached “Notice of References Cited” form 892). Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-3, 6-7, 9-10 and 13-20 are not patent eligible.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 6-7, 9-10 and 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Friesen (US 2006/0045909 A1, published Mar. 2, 2006; cited on the 08/19/2025 IDS Document), in view of Donavon (US 2016/0012748 A1, published Jan. 14, 2016; cited on the attached “Notice of References Cited” form 892).
Regarding independent claim 1, Friesen teaches the claim limitation of (a) retrieving, from a database, a data set associated with an initial nutritional product recommendation to improve, ameliorate, or prevent a condition in said non- human animal subject, wherein said initial nutritional product recommendation is based, at least in part, on genetic data and phenotype data of said non-human animal subject with “The illustrative data in Table 11 summarize characteristics of four canine breed clusters that may be used to develop specific foods tailored to meet nutritional needs for wellness, including preventing or treating conditions prevalent in the breed cluster.” ([0063]); “A computer-aided system for designing a nutritional formula for an animal is a further embodiment of the invention. The system comprises, on one to a plurality of user-interfaceable media, (a) a data set, herein referred to as a first data set, relating a plurality of breed clusters to genome-related attributes of each breed cluster; and (b) an algorithm, herein referred to as a first algorithm. This algorithm is capable, while drawing on the first data set, of (i) processing input data on one or more genome-related attributes of the animal to define a breed cluster to which the animal can be allocated, and (ii) designing a nutritional formula appropriate to nutritional needs of the breed cluster.” ([0131]); and “Zoographical attributes can comprise one or more attributes relating to genotype. Examples of such attributes include, without limitation, the breed of the animal, whether pedigreed, registered by a body such as AKC or otherwise; pedigree if known; in the case of animals of mixed breed, the breed heritage of the animal including the breed(s) of its parents and, if available, ancestors of earlier generations; sex; coat type (e.g., long, short, wiry, curly, smooth) and coloration; evident hereditary conditions and disorders; etc.” ([0073]).
Friesen teaches the claim limitation of (c) processing said activity data or said behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop another condition that differs from said condition in (a) with “In various embodiments of the invention, genome-based breed clusters identified according to an analysis such as that illustrated above have particular nutritional needs to promote wellness, e.g., to prevent and treat disease conditions associated with each cluster. Thus, illustratively, among canines, Clusters I, II, III and IV can have nutritional needs that are common to breeds within each cluster, but distinct from one cluster to another. Based on these nutritional needs, specific foods can be developed that are tailored to lifestyle, body type, activity level and other phenotypic attributes of each cluster, including incidence of particular diseases to be prevented or treated.” ([0051]); “Zoographical attributes can comprise one or more attributes relating to physiological condition. Examples of such attributes include, without limitation, age (chronological and, if determinable, physiological); weight; dimensions (e.g., height at shoulder, length of legs, length of back, etc.); veterinary medical history; reproductive history, including whether neutered, number and size of litters, etc.; present wellness or disease state and any recent changes therein, including any condition or disorder diagnosed, and any symptoms whether or not diagnosis has been made; presence of parasites, including fleas; appetite and any recent changes therein; physical activity level; mental acuity; behavioral abnormalities; disposition (e.g., timid, aggressive, obedient, nervous); etc.” ([0074]) and Table 11. Table 11 provides information on canine breed cluster, size, shedding, trainability, activity level and associated frequently diagnosed diseases.
Friesen teaches the claim limitation of (d) producing a modified nutritional product recommendation by modifying said initial nutritional product recommendation based, at least in part, on said activity data or said behavioral data processed in (c), wherein said modifying said initial nutritional product recommendation improves, ameliorates, or prevents said another condition with “In one embodiment, the system further comprises (c) a second data set recording phenotypic attributes characteristic of each breed cluster; and (d) a third data set relating to effects of BDCs (i) on such phenotypic attributes, as modified by specific zoographical attributes, and optionally (ii) on specific wellness attributes of individual animals. According to this embodiment, the first algorithm is further capable, while drawing on the second and third data sets, of processing input data on one or more zoographical attributes and optionally one or more wellness attributes of the animal to derive the nutritional formula. The nutritional formula is not only appropriate to nutritional needs of the breed cluster but further promotes wellness of the animal by taking into account zoographical attributes such as age and optionally specific wellness attributes such as an existing disease condition.” ([0133]); “The system optionally further comprises a user interface. The first, second, and third data sets can reside in one database or in a plurality of separate databases. The zoographical attributes acting as modifiers in the third data set can include any of those mentioned hereinabove. The first algorithm is optionally capable of processing input data that comprise diagnostic data from a biofluid or tissue sample obtained from the animal.” ([0134]); “The system can, if desired, further comprise (e) a fourth data set relating to contents of BDCs in food ingredients and, optionally, costs of these ingredients; and (f) a second algorithm capable of selecting food ingredients from the fourth data set to define a food composition having a nutritional formula as defined by the first algorithm. This second algorithm optionally takes account of costs of ingredients to define a food composition having advantageous overall cost. The system can further comprise a computer-controlled mixing system capable of preparing the food composition defined by the second algorithm.” ([0135]) and “Formulating food is not the only function of the invention. In various embodiments, the breed clusters and phenotypic information for each cluster may be used in designing pharmaceutical compositions for an animal; in designing wellness programs for an animal; in programs to determine if supplements are needed in an animal's diet as well as the types and quantities of supplements that should be recommended; in designing therapeutic regimens for an animal, e.g., a regimen that includes an exercise program to prevent onset of a chronic condition that is prevalent in the cluster; or to formulate foods that comprise BDCs that may be important in treating and/or preventing a disease or a genetic disorder.” ([0111]).
Friesen does not teach the claim limitation of (b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject of claim 1. However, this limitation is taught by Donavon.
Donavon teaches the claim limitation of (b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject with “In this case, three separate devices were used to acquire specific data about Frasier; 1) a collar-mounted device including an accelerometer used to track activity levels, 2) a device that tracks food and water consumption from Frasier's food and water bowls using standard load cells and 3) a 2′×3′ scale device that tracks Frasier's weight using load cells.” ([0106]) and “Certain exemplary embodiments of sensing/measuring devices 60 are depicted in FIG. 2. For instance, the device 60 may comprise an on-animal monitor 60 a, which may be coupled to the collar, leash, or other accessory of the animal. On-animal devices of this type may be configured to measure, among other things, animal surroundings, animal activity, body temperature, ambient temperature, elevation/altitude changes, UV exposure, and the like.” ([0074]).
It would have been prima facia obvious to combine the teachings of Friesen and Donavon to arrive at the claimed invention. A person of ordinary skill in the art would have been motivated to modify the method of Friesen to include an activity tracking device as taught by Donavon to better collect data for analysis to improve nutrition, health, and/or wellness protocols for the animal ([0002]). Furthermore, there would have been a reasonable expectation of success, since Friesen and Donavon teach methods that pertain to monitoring animal activities for the purpose of providing nutrition recommendations.
Regarding claim 2, Friesen teaches the claim limitation of wherein said initial nutritional product recommendation comprises a nutritional product comprising a supplement, a treat, a food, or any combination thereof with “Formulating food is not the only function of the invention. In various embodiments, the breed clusters and phenotypic information for each cluster may be used in designing pharmaceutical compositions for an animal; in designing wellness programs for an animal; in programs to determine if supplements are needed in an animal's diet as well as the types and quantities of supplements that should be recommended; in designing therapeutic regimens for an animal, e.g., a regimen that includes an exercise program to prevent onset of a chronic condition that is prevalent in the cluster; or to formulate foods that comprise BDCs that may be important in treating and/or preventing a disease or a genetic disorder.” ([0111]) and “The invention additionally provides a kit comprising a food prepared by a method as described herein, a food supplement, and optionally a means of communicating information and/or instructions on adding the food supplement to the food and feeding the resulting supplemented food to an animal.” [0015]
Regarding claim 3, Friesen teaches the claim limitation of wherein said modifying said initial nutritional product recommendation comprises modifying an amount of a said initial nutritional product or an amount of one or more ingredients in nutritional product with “In one embodiment, a method for selecting a food further comprises identifying one or more specific zoographical attributes of the animal. In this embodiment, the food selected has a nutritional formula modified to take account of the specific zoographical attributes.” ([0071]); “The invention also provides a method for promoting wellness of an animal comprising (a) identifying a genome-based breed cluster to which the animal belongs; (b) selecting a nutritional formula that is matched at least in part to nutritional needs for wellness of animals of the breed cluster; and (c) feeding to the animal a food comprising bioactive dietary components in amounts and ratios dictated by the nutritional formula.” ([0011]); “Nutritional needs for wellness thus can be satisfied not merely by supplying sufficient of the basic nutrients required for maintenance of life, but by supplying amounts and balances of different nutrients and BDCs that, when fed to the animal, promote one or more aspects of wellness.” ([0031]); and “The ingredients providing the BDCs can be selected by an algorithm. Algorithms for formulating food compositions based on a nutritional formula are well known in the art. Such algorithms access a data set having analysis of various ingredients and draw on that data set to compute the amounts of such ingredients in a food composition having the desired nutritional formula.” ([0095]).
Regarding claim 9, Friesen teaches the claim limitation of wherein said condition or said another condition is an allergic reaction with “The nutritional needs for wellness of animals of a particular breed cluster can be based at least in part on one or more phenotypic attributes characteristic of the breed cluster. Such phenotypic attributes can include physical attributes, such as size, coat type or activity level, cognitive attributes such as trainability, and/or prevalence of or predisposition to one or more diseases, e.g., cardiovascular diseases, obesity, diabetes, dermatitis, eye diseases, kidney diseases, thyroid diseases, arthritis or age-related degenerative diseases. Phenotypic attributes characteristic of a breed cluster can be derived at least in part from data, published or otherwise, on phenotypic attributes of individual breeds within the breed cluster.” ([0037]) and “The method of claim 1 further comprising identifying one or more specific wellness attributes of the animal selected from the group consisting of disease states, states of parasitic infestation, hair and skin condition, sensory acuteness, dispositional and behavioral attributes, and cognitive function; wherein the food selected has a nutritional formula modified to take account of the specific wellness attribute(s).” (Friesen, claim 9). The recited “allergic reaction” corresponds to “dermatitis” and “hair and skin condition” as taught by Friesen.
Regarding claim 10, Friesen teaches the claim limitation of wherein said allergic reaction is an allergic itch with “The nutritional needs for wellness of animals of a particular breed cluster can be based at least in part on one or more phenotypic attributes characteristic of the breed cluster. Such phenotypic attributes can include physical attributes, such as size, coat type or activity level, cognitive attributes such as trainability, and/or prevalence of or predisposition to one or more diseases, e.g., cardiovascular diseases, obesity, diabetes, dermatitis, eye diseases, kidney diseases, thyroid diseases, arthritis or age-related degenerative diseases. Phenotypic attributes characteristic of a breed cluster can be derived at least in part from data, published or otherwise, on phenotypic attributes of individual breeds within the breed cluster.” ([0037]) and “The method of claim 1 further comprising identifying one or more specific wellness attributes of the animal selected from the group consisting of disease states, states of parasitic infestation, hair and skin condition, sensory acuteness, dispositional and behavioral attributes, and cognitive function; wherein the food selected has a nutritional formula modified to take account of the specific wellness attribute(s).” (Friesen, claim 9). The recited “allergic itch” corresponds to “dermatitis” and “hair and skin condition” as taught by Friesen.
Regarding claim 13, Friesen teaches the claim limitation of wherein said activity data comprises data related to activity type, data related to an activity level, consumption data, sleep data, or any combination thereof with Table 11. Table 11 provides information on canine breed cluster, size, shedding, trainability, activity level and associated frequently diagnosed diseases.
Regarding claim 14, Friesen teaches the claim limitation of wherein said consumption data comprises calories or water consumed by said non-human animal subject with Table 1. Table 1 lists the typical components of a companion animal diet that includes water.
Regarding claim 17, Friesen teaches the claim limitation of wherein said genetic data is not associated with a breed type with “The invention provides a new approach to enhancing animal nutrition and health care based on the genotype of an animal. Unlike previous efforts to provide genotype-specific foods, e.g., breed-specific foods, methods provided herein utilize a more comprehensive genomic profile of an animal species, coupled with rigorous statistical analysis, to define breed clusters that exhibit a nutritionally appropriate degree of genetic similarity within clusters and more marked genetic diversity between clusters. Breed clusters so defined are described herein as “genome-based” breed clusters. Without being bound by theory, it is believed that members of such a breed cluster typically have a common phylogeny, i.e., are descended from a single ancestral population. Except where the context demands otherwise, the term “breed cluster” herein means a genome-based breed cluster, as opposed to a cluster of breeds grouped according to criteria other than genotype. Thus traditional classifications of animal breeds based on phenotypic criteria such as AKC's classification of canine breeds into seven groups (sporting, hound, working, terrier, toy, non-sporting and herding groups) do not meet the definition of “breed clusters” as understood herein.” ([0021]).
Regarding claim 18, Friesen teaches the claim limitation of (f) processing said new activity data or said new behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop a third condition that differs from said condition in (a) or said another condition in (c) with “Wellness of an animal herein encompasses all aspects of the physical, mental, and social well-being of the animal, and is not restricted to the absence of infirmity. Wellness attributes include without limitation states of disease or physiological disorder, states of parasitic infestation, hair and skin condition, sensory acuteness, dispositional and behavioral attributes, and cognitive function. Nutritional needs for wellness thus can be satisfied not merely by supplying sufficient of the basic nutrients required for maintenance of life, but by supplying amounts and balances of different nutrients and BDCs that, when fed to the animal, promote one or more aspects of wellness.” ([0031]).; “Zoographical attributes can comprise one or more attributes relating to physiological condition. Examples of such attributes include, without limitation, age (chronological and, if determinable, physiological); weight; dimensions (e.g., height at shoulder, length of legs, length of back, etc.); veterinary medical history; reproductive history, including whether neutered, number and size of litters, etc.; present wellness or disease state and any recent changes therein, including any condition or disorder diagnosed, and any symptoms whether or not diagnosis has been made; presence of parasites, including fleas; appetite and any recent changes therein; physical activity level; mental acuity; behavioral abnormalities; disposition (e.g., timid, aggressive, obedient, nervous); etc.” ([0074]) and Table 11. Table 11 provides information on canine breed cluster, size, shedding, trainability, activity level and associated frequently diagnosed diseases.
Friesen teaches the claim limitation of (g) modifying said modified nutritional product recommendation based, at least in part, on said new activity data or said new behavioral data processed in (f), wherein said modifying said modified nutritional product recommendation improves, ameliorates, or prevents said third condition with “In one embodiment, a method for selecting a food further comprises identifying one or more specific zoographical attributes of the animal. In this embodiment, the food selected has a nutritional formula modified to take account of the specific zoographical attributes.” ([0071]) and “The illustrative data in Table 11 summarize characteristics of four canine breed clusters that may be used to develop specific foods tailored to meet nutritional needs for wellness, including preventing or treating conditions prevalent in the breed cluster.” ([0063]).
However, Friesen does not teach the claim limitation of (e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device of claim 18. This limitation is taught by Donavon as discussed below.
Regarding claim 19, Friesen teaches the claim limitation of displaying a notification comprising said modified nutritional product recommendation on a graphical user interface of a personal electronic device of a user with “The present invention also provides consumer communication apparatus. Such apparatus helps an owner understand which genotypic cluster his/her animal, e.g., canine, belongs to. Such apparatus can include any one or more of a variety of point of sale displays which are well known in the art of marketing. In various embodiments, a consumer communication apparatus includes a computer kiosk, at a point of sale or elsewhere, which allows the owner to input information, e.g., on a touch screen, including for example breed and age, and in certain embodiments other information may be required to be input. Based on the input information, the computer identifies an appropriate food formulation, or if only one formulation is appropriate, the correct food formulation, for the animal. In various embodiments, the computer kiosk provides frequently asked questions along with answers. In other embodiments, the computer kiosk provides a tutorial or primer on the science that is involved in development of the food formulations. In various embodiments, the computer kiosk may be used to market new products and/or new technology. In other embodiments, the computer kiosk may be used to collect survey information from consumers.” ([0125]) and “In some embodiments, the kiosk runs a web page or a group of web pages over the Internet. In other embodiments, an owner inputs information and/or receives information via web pages on a computer. In such embodiments, the web pages on the computer may perform one or more functions in a similar fashion to the kiosk described above. In still other embodiments, an owner responds to a questionnaire in a written format and the questionnaire is then input to a system that determines the most appropriate food formulation for a particular animal. In still other embodiments, an owner responds to questions orally and such oral responses may be recorded electronically or in a paper format by a health care professional and such response is input to a system that determines the most appropriate food formulation for a particular animal.” ([0126]).
Friesen does not teach the claim limitation of wherein said activity tracking device is a collar of claim 6; wherein said collar is a Global Positioning System (GPS)-connected collar of claim 7; wherein said behavioral data comprises a repetitive behavior of claim 15; said repetitive behavior comprises itching, chewing, scratching, sighing, aggression, neurosis, anxiety, abnormal energy level, or any combination thereof of claim 16; (e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device of claim 18(e) and wherein said processing is performed by a machine learning algorithm of claim 20. However, these limitations are taught by Donavon.
Regarding claim 6, Donavon teaches the claim limitation of wherein said activity tracking device is a collar with “In this case, three separate devices were used to acquire specific data about Frasier; 1) a collar-mounted device including an accelerometer used to track activity levels, 2) a device that tracks food and water consumption from Frasier's food and water bowls using standard load cells and 3) a 2′×3′ scale device that tracks Frasier's weight using load cells.” ([0106]) and “Certain exemplary embodiments of sensing/measuring devices 60 are depicted in FIG. 2. For instance, the device 60 may comprise an on-animal monitor 60 a, which may be coupled to the collar, leash, or other accessory of the animal. On-animal devices of this type may be configured to measure, among other things, animal surroundings, animal activity, body temperature, ambient temperature, elevation/altitude changes, UV exposure, and the like.” ([0074]).
Regarding claim 7, Donavon teaches the claim limitation of wherein said collar is a Global Positioning System (GPS)-connected collar with “The data being acquired can be categorized into a range of data types. For instance, and as discussed in further detail below, the data can be provided by an individual (e.g., owner, caretaker, or veterinary personnel) based upon observation or personal knowledge, or may be derived from sensor or measurement technology placed on or around the animal or at locations the animal frequents (e.g., collar/leash, feeding/water stations, litter box, etc.); that is, the animal's environment. All data that is collected becomes resident in a common data structure (whether specific for the particular animal or across a broader spectrum of breeds or types of animal).” ([0034]); “Certain exemplary embodiments of sensing/measuring devices 60 are depicted in FIG. 2. For instance, the device 60 may comprise an on-animal monitor 60 a, which may be coupled to the collar, leash, or other accessory of the animal. On-animal devices of this type may be configured to measure, among other things, animal surroundings, animal activity, body temperature, ambient temperature, elevation/altitude changes, UV exposure, and the like.” ([0074]) and “…GPS or other location-monitoring technologies to pinpoint location of the animal (e.g., in/out of house, etc.)” ([0061]) and “Thus, a variety of sensors and measuring devices may be utilized in the data collection step. Exemplary sensors include, but are not limited to, accelerometers (single axis or multi-axis), gyroscopes, weighing scales, weight transducers, force transducers, displacement transducers, orientation sensors (e.g., compasses), pressure transducers, weight sensors, force sensors, pedometers, displacement sensors, pressure sensors, load cells, photographic cameras, video cameras, camcorders, RF location beacons, contact thermometers, non-contact thermometers, such as infrared thermometers, laser thermometers, infrared pyrometers, laser pyrometers, litters or litter additives that change their properties, such as color, odor, outgassing, fluorescence, luminescence, when come in contact with animal waste, either urine or excrements. Other sensors may also be used to determine an animal's presence or absence at a particular location or height, such as optical sensors, optical reflecting sensors, LED/photodiode pair optical sensors, LED/phototransistor pair optical sensors, laser diode/photodiode pair optical sensors, laser diode/phototransistor pair optical sensors, optocouplers, optical fiber coupled optical sensors, magnetic sensors, weight sensors, force sensors, displacement sensors, pressure sensors (relative/differential or absolute), various proximity sensors, such as inductive proximity sensors, magnetic proximity sensors, capacitive proximity sensors, global positioning system (GPS) devices, a global navigation satellite system (GNSS) devices, and/or a combination thereof. In general, all types of sensors and sensing techniques, whether now known or later developed, that are capable of generating data which is representative of motion and/or presence of an animal are intended to fall within the scope of the present disclosure.” ([0068]).
Regarding claim 15, Donavon teaches the claim limitation of wherein said behavioral data comprises a repetitive behavior with “In addition, collected data and analysis on certain parameters can be indicative of a number of particular issues for the animal. For example, one or more changes in animal activity; changes in rest periods/intensity; changes in food/water consumption; changes in steps taken; changes in weight; irregular elimination behavior; body temperature; results of blood, urine, and/or stress tests; and combinations thereof, may be indicative or otherwise informative of certain cancers in the animal. By way of another example, changes in food/water consumption; changes in weight; seasonality; abnormal scratching; hair loss; changes in appearance; and combinations thereof, may be indicative or otherwise informative of allergies in the animal (whether food allergies, environmental allergies, or bacterial/viral allergies). By way of another example, changes in activity; number of steps (e.g., pacing); heart rate; increased water intake and decreased food intake; vocalization (e.g., whining); and combinations thereof, may be indicative or otherwise informative of anxiety, stress, or boredom in the animal. By way of another example, the age; breed; reproductive aspects (e.g., estrus, spay/neuter status, etc.); rest patterns; activity patterns including number of steps and calories burned; changes in caloric intake; changes in feeding patterns; and combinations thereof, may be indicative of the life stage (or a change thereof) of the animal. By way of another example, increases in water intake; increases or decreases in body weight; the age and breed of the animal; urine color; decreases in activity; food type; and combinations thereof, may be indicative of diabetes in the animal. These collected data and analysis may, in turn, lead to outcomes and recommendations regarding one or more of changes in environment; initiating, limiting, or increasing exercise protocols; administration or cessation of vitamins, supplements, or medication; initiating or modifying training protocols; nutritional/feeding changes; veterinary visits; combinations thereof; and the like.” ([0059]).
Regarding claim 16, Donavon teaches the claim limitation of wherein said repetitive behavior comprises itching, chewing, scratching, sighing, aggression, neurosis, anxiety, abnormal energy level, or any combination thereof with “In addition, collected data and analysis on certain parameters can be indicative of a number of particular issues for the animal. For example, one or more changes in animal activity; changes in rest periods/intensity; changes in food/water consumption; changes in steps taken; changes in weight; irregular elimination behavior; body temperature; results of blood, urine, and/or stress tests; and combinations thereof, may be indicative or otherwise informative of certain cancers in the animal. By way of another example, changes in food/water consumption; changes in weight; seasonality; abnormal scratching; hair loss; changes in appearance; and combinations thereof, may be indicative or otherwise informative of allergies in the animal (whether food allergies, environmental allergies, or bacterial/viral allergies). By way of another example, changes in activity; number of steps (e.g., pacing); heart rate; increased water intake and decreased food intake; vocalization (e.g., whining); and combinations thereof, may be indicative or otherwise informative of anxiety, stress, or boredom in the animal. By way of another example, the age; breed; reproductive aspects (e.g., estrus, spay/neuter status, etc.); rest patterns; activity patterns including number of steps and calories burned; changes in caloric intake; changes in feeding patterns; and combinations thereof, may be indicative of the life stage (or a change thereof) of the animal. By way of another example, increases in water intake; increases or decreases in body weight; the age and breed of the animal; urine color; decreases in activity; food type; and combinations thereof, may be indicative of diabetes in the animal. These collected data and analysis may, in turn, lead to outcomes and recommendations regarding one or more of changes in environment; initiating, limiting, or increasing exercise protocols; administration or cessation of vitamins, supplements, or medication; initiating or modifying training protocols; nutritional/feeding changes; veterinary visits; combinations thereof; and the like.” ([0059]).
Regarding claim 18, as discussed above, Friesen does not teach the claim limitation of (e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device. However, Donavan teaches this limitation with “The data being acquired can be categorized into a range of data types. For instance, and as discussed in further detail below, the data can be provided by an individual (e.g., owner, caretaker, or veterinary personnel) based upon observation or personal knowledge, or may be derived from sensor or measurement technology placed on or around the animal or at locations the animal frequents (e.g., collar/leash, feeding/water stations, litter box, etc.); that is, the animal's environment. All data that is collected becomes resident in a common data structure (whether specific for the particular animal or across a broader spectrum of breeds or types of animal).” ([0034]) and “As discussed above, the outcomes and recommendations for improving or enhancing the nutrition, health, and or wellness of the animal are determined using various data 2 collected from the animal (FIG. 1). This can involve any one or more characteristics, or parameters, exhibited or possessed by the animal, or otherwise present in connection with the animal (such as environmental factors), In a particular embodiment, the foregoing analysis is performed on one or more of a health, diet, behavior, and environmental parameter of the animal.” ([0042]).
Regarding claim 20, Friesen teaches wherein said processing is performed by an algorithm with “The invention further provides a computer-aided system for designing a nutritional formula for an animal. The system comprises, on one to a plurality of user-interfaceable media, (a) a data set relating a plurality of breed clusters to genome-related attributes of each breed cluster; and (b) an algorithm capable, while drawing on the data set, of (i) processing input data on one or more genome-related attributes of the animal to define a breed cluster to which the animal can be allocated, and (ii) designing a nutritional formula appropriate to nutritional needs of the breed cluster.” ([0010]).
However, Friesen does not explicitly teach the claim limitation of wherein said processing is performed by a machine learning algorithm of claim 20. This limitation is taught by Donavon.
Donavon teaches the claim limitation of wherein said processing is performed by a machine learning algorithm with “With respect to data analysis, this may include the many types of software development methodologies and tools/program languages that exist, such as cloud-based data architectures, “Big Data” analytics systems and methods (e.g., via Amazon's Elastic MapReduce (EMR) and/or Google's I/O), and HTML based applications (e.g., HTML5). These methodologies, tools, and programs may be executed alone or, more preferably, in conjunction with one or more of (1) inventor's and applicant's expert knowledge in animal nutrition, health, and wellness; (2) expert knowledge of other individuals and groups in practice and academia; (3) expert knowledge of data scientists and research and development individuals and groups to create additional, or alternative, predictive analytics algorithms based on the treatment of the data collected on individual animals (i.e., data scientists associated with the applicant, as well as, other third party groups and partners); and (4) emerging machine-learning technologies that are capable of automating data analysis using high-speed processors to identify significant trend and insights within the data set.” ([0075]).
It would have been prima facia obvious to combine the teachings of Friesen and Donavon to arrive at the claimed invention. A person of ordinary skill in the art would have been motivated to modify the method of Friesen to include an activity tracking collar with GPS of claims 6-7 as taught by Donavon to easily collect activity and geolocation data for analysis to provide for the advantage of inferring the health status of the animal. A person of ordinary skill in the art would have also been motivated to modify the method of Friesen to include obtaining repetitive behavioral data of claims 15-16 and obtaining new activity data or new behavioral data of claim 18(e) as taught by Donavon for the advantage of inferring allergies and/or mental state of the animal. The collected data are indicative or informative of the animal’s health and mental status, which would allow for the recommendation of nutrition, health, and/or wellness protocols directed to improve the animal’s overall well-being. A person of ordinary skill in the art would have also been motivated to modify the method of Friesen to use a machine learning algorithm to process the data of claim 20 as taught by Donavon for the purpose of automating data analysis to quickly and efficiently process data. Furthermore, there would have been a reasonable expectation of success, since Friesen and Donavon teach methods that pertain to monitoring animal activities for the purpose of providing nutrition recommendations.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-3, 6-7, 9-10 and 13-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2, 4, 7, and 16-19 of Application No. 19178472 (reference application) in view of Donavon (US 2016/0012748 A1, published Jan. 14, 2016; cited on the attached “Notice of References Cited” form 892). Although the claims at issue are not identical, they are not patentably distinct from each other because both sets of claims recite a method of obtaining genetic and phenotypic data that is associated with a condition and producing a nutritional product for improving the condition of the non-human subject. Overall, the difference is that the claims of the instant application are broader in scope than the claims of the reference application and thus the instant claims are anticipated by the reference application (see MPEP 804.II.B.2). See table below for the similarities between the claims.
This is not a provisional nonstatutory double patenting rejection because the patentably indistinct claims have been patented.
Instant claims, App. #19303233, 12/22/2025
Reference claims, App. #19178472, 09/30/2025
1. (Currently Amended) A method for modifying a nutritional product recommendation for a non-human animal subject, the method comprising;
(a) retrieving, from a database, a data set associated with an initial nutritional product recommendation to improve, ameliorate, or prevent a condition in said non- human animal subject, wherein said initial nutritional product recommendation is based, at least in part, on genetic data and phenotype data of said non-human animal subject;
(b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject;
(c) processing said activity data or said behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop another condition that differs from said condition in (a); and
(d) producing a modified nutritional product recommendation by modifying said initial nutritional product recommendation based, at least in part, on said activity data or said behavioral data processed in (c),
wherein said modifying said initial nutritional product recommendation improves, ameliorates, or prevents said another condition.
18. (Currently Amended) The method of claim 1, further comprising:(e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device;(f) processing said new activity data or said new behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop or said another condition in (c); and(g) modifying said modified nutritional product recommendation based, at least in part, on said new activity data or said new behavioral data processed in (f), wherein said modifying said modified nutritional product recommendation improves, ameliorates, or prevents
1. (Previously Allowed) A method of producing a personalized combination nutritional product, the method comprising assembling a combination product comprising a food and a nutritional supplement for a non-human animal subject based, at least in part on:(a) receiving: genetic data at a plurality of genomic loci of the non-human animal subject, wherein at least one genomic locus of the plurality of genomic loci is associated with a first condition, wherein the first condition is not a breed type; phenotypic data pertaining to a plurality of phenotypes of the non-human animal subject that is associated with a second condition, wherein the plurality of phenotypes comprises a species, a food allergy, an age, a weight, or a breed; and environmental data for the non-human animal subject that is associated with a third condition, wherein the environmental data comprises a climate or geographical location of residence;(b) processing a data set comprising the genetic data, the phenotypic data, and the environmental data to determine qualitative or quantitative measures of each that predict whether the non-human animal subject is likely to have or develop the first condition, the second condition, and the third condition; and(c) ranking at least two of the first condition, the second condition, and the third condition to identify a highest-ranking condition for the non-human animal subject, wherein the combination product improves, ameliorates, or prevents the highest-ranking condition.
16. (Previously Allowed) The method of claim 1, wherein the food is formulated to improve, ameliorate, or prevent the highest-ranking condition and one or more additional conditions identified based, at least in part, on the data set.
18. (Previously Allowed) The method of claim 1, further comprising receiving activity data for the non-human animal subject that comprises an activity level, an activity type, calories burned, or time asleep for the non-human animal subject, wherein the data set further comprises the activity data.
19. (Previously Allowed) The method of claim 1, further comprising receiving behavioral data for the non-human animal subject that comprises chewing, itching, aggression, neurosis, anxiety, or energy level of the non-human animal subject, wherein the data set further comprises the behavioral data.
2. (Currently Amended) The method of claim 1, wherein said initial nutritional product recommendation comprises a nutritional product comprising a supplement, a treat, a food, or any combination thereof.
2. (Previously Allowed) The method of claim 1, wherein the food comprises a kibble, a wet food, a canned food, a fresh food, or any combination thereof.
4. (Previously Allowed) The method of claim 1, wherein the combination product further comprises a treat.
17. (Currently Amended) The method of claim 1, wherein the food improves, ameliorates, or prevents the highest-ranking condition and the nutritional supplement improves, ameliorates, or prevents a second highest-ranking condition of the first condition, the second condition, and the third condition.
3. (Currently Amended) The method of claim 1, wherein said modifying said initial nutritional product recommendation comprises modifying an amount of a
7. (Previously Allowed) The method of claim 1, wherein the food comprises an increased or a decreased amount of an existing ingredient of a standard food as determined AAFCO guidelines or guidelines of a similar standard-setting body corresponding to the non-human animal subject, wherein the increased or the decreased amount of the existing ingredient, at least in part, improves, ameliorates, or prevents the highest-ranking condition.
17. (Currently Amended) The method of claim 1, wherein the food improves, ameliorates, or prevents the highest-ranking condition and the nutritional supplement improves, ameliorates, or prevents a second highest-ranking condition of the first condition, the second condition, and the third condition.
13. (Original) The method of claim 1, wherein said activity data comprises data related to activity type, data related to an activity level, consumption data, sleep data, or any combination thereof.
14. (Original) The method of claim 13, wherein said consumption data comprises calories or water consumed by said non-human animal subject.
18. (Previously Allowed) The method of claim 1, further comprising receiving activity data for the non-human animal subject that comprises an activity level, an activity type, calories burned, or time asleep for the non-human animal subject, wherein the data set further comprises the activity data.
16. (Original) The method of claim 15, wherein said repetitive behavior comprises itching, chewing, scratching, sighing, aggression, neurosis, anxiety, abnormal energy level, or any combination thereof.
19. (Previously Allowed) The method of claim 1, further comprising receiving behavioral data for the non-human animal subject that comprises chewing, itching, aggression, neurosis, anxiety, or energy level of the non-human animal subject, wherein the data set further comprises the behavioral data.
Reference application #19178472 does not teach the activity tracking device in claim 1. However, this limitation is taught by Donavon.
Regarding claim 1, Donavon teaches the claim limitation of (b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject with “In this case, three separate devices were used to acquire specific data about Frasier; 1) a collar-mounted device including an accelerometer used to track activity levels, 2) a device that tracks food and water consumption from Frasier's food and water bowls using standard load cells and 3) a 2′×3′ scale device that tracks Frasier's weight using load cells.” ([0106]) and “Certain exemplary embodiments of sensing/measuring devices 60 are depicted in FIG. 2. For instance, the device 60 may comprise an on-animal monitor 60 a, which may be coupled to the collar, leash, or other accessory of the animal. On-animal devices of this type may be configured to measure, among other things, animal surroundings, animal activity, body temperature, ambient temperature, elevation/altitude changes, UV exposure, and the like.” ([0074]).
It would have been prima facia obvious to combine the teachings of Reference application #19178472 and Donavon to arrive at the claimed invention. A person of ordinary skill in the art would have been motivated to modify the method of Reference application #19178472 to include an activity tracking device as taught by Donavon to better collect data for analysis to improve nutrition, health, and/or wellness protocols for the animal ([0002]). Furthermore, there would have been a reasonable expectation of success, since Reference application #19178472 and Donavon teach methods that pertain to monitoring animal activities for the purpose of providing nutrition recommendations.
Claims 1-3, 6-7, 9-10 and 13-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2, 19 and 30-32 of Application No. 18353737 (reference application) in view of Donavon (US 2016/0012748 A1, published Jan. 14, 2016; cited on the attached “Notice of References Cited” form 892). Although the claims at issue are not identical, they are not patentably distinct from each other because both sets of claims recite a method of obtaining genetic and phenotypic data that is associated with a condition and producing a nutritional product for improving the condition of the non-human subject. Overall, the difference is that the claims of the instant application are broader in scope than the claims of the reference application and thus the instant claims are anticipated by the reference application (see MPEP 804.II.B.2). See table below for the similarities between the claims.
This is not a provisional nonstatutory double patenting rejection because the patentably indistinct claims have been patented.
Instant claims, App. #19303233, 12/22/2025
Reference claims, App. #18353737, 03/05/2025
1. (Currently Amended) A method for modifying a nutritional product recommendation for a non-human animal subject, the method comprising;
(a) retrieving, from a database, a data set associated with an initial nutritional product recommendation to improve, ameliorate, or prevent a condition in said non- human animal subject, wherein said initial nutritional product recommendation is based, at least in part, on genetic data and phenotype data of said non-human animal subject;
(b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject;
(c) processing said activity data or said behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop another condition that differs from said condition in (a); and
(d) producing a modified nutritional product recommendation by modifying said initial nutritional product recommendation based, at least in part, on said activity data or said behavioral data processed in (c),
wherein said modifying said initial nutritional product recommendation improves, ameliorates, or prevents said another condition.
1. (Currently Amended) A method for identifying a nutritional product recommended for a non-human animal subject, the method comprising:(a) receiving genetic data at a plurality of genomic loci of the non-human animal subject, wherein at least one genomic locus of the plurality of genomic loci is associated with a first condition, wherein the first condition is not a breed type;(b) receiving phenotypic data pertaining to a plurality of phenotypes of the non-human animal subject, wherein at least one phenotype of the plurality of phenotypes is associated with a second condition;(c) producing a genotype-phenotype profile for the non-human animal subject by processing a data set comprising the genetic data and the phenotypic data to determine qualitative or quantitative measures of the at least one genomic locus of the plurality of genomic loci, and qualitative or quantitative measures of the at least one phenotype of the plurality of phenotypes;(d) applying a machine learning prediction model to the genotype-phenotype profile of the non-human animal subject to identify the nutritional product recommended for the non- human subject, based at least in part, on a likelihood that the non-human animal subject has:(i) the first condition or a risk of developing the first condition; and[[']] (ii) the second condition or a risk of developing the second condition;(e) ranking the first conditionand the second condition based, at least in part, on severity of the first condition and the second condition to identify a highest ranking condition of the first condition and the second condition; and(f) administering the nutritional product to the non-human animal subject, wherein the nutritional product:(i) comprises a [[base ]]food; and(ii) improves, ameliorates, or prevents at least the highest ranking condition or the risk of developing at least the highest ranking condition in the non-human animal subject.
2. (Currently Amended) The method of claim 1, wherein said initial nutritional product recommendation comprises a nutritional product comprising a supplement, a treat, a food, or any combination thereof.
32. (Currently Amended) The method of claim 1, wherein the nutritional product further comprises a treat, or both
3. (Currently Amended) The method of claim 1, wherein said modifying said initial nutritional product recommendation comprises modifying an amount of a
19. (Previously Presented) The method of claim 1, wherein the machine learning prediction model comprises a clustering algorithm, a decision tree algorithm, a statistical algorithm, gradient boosted machine (GBM), or any combination thereof.
9. (Original) The method of claim 1, wherein said condition or said another condition is an allergic reaction.
10. (Original) The method of claim 9, wherein said allergic reaction is an allergic itch
2. (Currently Amended) The method of claim 1, wherein the first condition or the second condition comprises one or more genetic conditions, one or more nutritional conditions, one or more clinical conditions, one or more fitness conditions, one or more dermatological conditions, [[or]] one or more allergy conditions, or any combination thereof.
18. (Currently Amended) The method of claim 1, further comprising:(e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device;(f) processing said new activity data or said new behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop or said another condition in (c); and(g) modifying said modified nutritional product recommendation based, at least in part, on said new activity data or said new behavioral data processed in (f), wherein said modifying said modified nutritional product recommendation improves, ameliorates, or prevents
19. (Currently Amended) The method of claim 1, further comprising displaying[[ed]] a notification comprising said modified nutritional product recommendation on a graphical user interface of a personal electronic device of a user.
30. (Previously Presented) The method of claim 29, further comprising providing a notification to a guardian of the non-human animal subject or a veterinarian of the non-human animal subject at one or more of the plurality of time points, wherein the notification comprises: (i) the first condition or the risk of developing the first condition and the second condition or the risk of developing the second condition in the non-human animal subject; (ii) the updated profile of the non-human animal subject; (iii) a recommendation for a product, a behavioral modification, or any combination thereof, for the non-human animal subject; (iv) a prescription of a therapeutic or prophylactic intervention for the non-human animal subject; or (v) any combination of (i) to (iv).
20. (Original) The method of claim 1, wherein said processing is performed by a machine learning algorithm.
31. (Previously Presented) The method of claim 1, further comprising: receiving biomarker data, activity data, environment data, behavioral data, or clinical data for the non-human animal subject; producing an updated genotype-phenotype profile for the non-human animal subject by processing the biomarker data, the activity data, the environment data, the behavioral data, or the clinical data, or the combination thereof, to determine quantitative or qualitative measures thereof; and applying the machine learning prediction model to the updated genotype-phenotype profile of the non-human animal subject to identify: a new nutritional product or a new amount of the nutritional product recommended for the non-human animal subject; or a behavioral modification for the non-human animal subject.
Reference application #18353737 does not teach the activity tracking device in claim 1. However, this limitation is taught by Donavon.
Regarding claim 1, Donavon teaches the claim limitation of (b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject with “In this case, three separate devices were used to acquire specific data about Frasier; 1) a collar-mounted device including an accelerometer used to track activity levels, 2) a device that tracks food and water consumption from Frasier's food and water bowls using standard load cells and 3) a 2′×3′ scale device that tracks Frasier's weight using load cells.” ([0106]) and “Certain exemplary embodiments of sensing/measuring devices 60 are depicted in FIG. 2. For instance, the device 60 may comprise an on-animal monitor 60 a, which may be coupled to the collar, leash, or other accessory of the animal. On-animal devices of this type may be configured to measure, among other things, animal surroundings, animal activity, body temperature, ambient temperature, elevation/altitude changes, UV exposure, and the like.” ([0074]).
It would have been prima facia obvious to combine the teachings of Reference application #18353737 and Donavon to arrive at the claimed invention. A person of ordinary skill in the art would have been motivated to modify the method of Reference application #18353737 to include an activity tracking device as taught by Donavon to better collect data for analysis to improve nutrition, health, and/or wellness protocols for the animal ([0002]). Furthermore, there would have been a reasonable expectation of success, since Reference application #18353737 and Donavon teach methods that pertain to monitoring animal activities for the purpose of providing nutrition recommendations.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KETTIP KRIANGCHAIVECH whose telephone number is (571)272-1735. The examiner can normally be reached 8:30am-5:00pm EDT.
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/K.K./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686