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KR-102961922-B1 - METHOD FOR COMPREHENSIVE HEALTH INSPECTION OF PETS FOR PREDICTING SKIN DISEASES, INTESTINAL DISEASES, AND ORAL DISEASES BASED ON SKIN SAMPLES

KR102961922B1KR 102961922 B1KR102961922 B1KR 102961922B1KR-102961922-B1

Abstract

A comprehensive health examination method for a pet according to the present invention, which predicts skin diseases, intestinal diseases, and oral diseases based on skin specimens of a pet, comprises: a step of generating a plurality of microbiome data based on a plurality of specimens collected from a plurality of skin sites of a pet subject to examination; a step of generating a disease prediction profile including an intestinal disease prediction profile, a skin disease prediction profile, and an oral disease prediction profile by processing the plurality of microbiome data based on at least one of a list of microorganisms of interest for each disease and the importance of each skin site for each disease; a step of searching for a similar standard profile corresponding to each disease prediction profile by comparing the disease prediction profile with a plurality of standard profiles stored in a pet standard database; a step of calculating a risk for each disease based on the similarity between the similar standard profile and the disease prediction profile; and a step of generating a health status report for the pet subject to examination based on the calculated risk.

Inventors

  • 이준형
  • 김선균

Assignees

  • 주식회사 리비오젠

Dates

Publication Date
20260507
Application Date
20250821

Claims (10)

  1. In a comprehensive health examination method for pets that predicts skin diseases, intestinal diseases, and oral diseases based on a skin specimen of a pet performed by a processor, A step of generating multiple microbiome data based on multiple samples collected from multiple skin sites of a pet subject to examination by the above processor; A step of generating a disease prediction profile including an intestinal disease prediction profile, a skin disease prediction profile, and an oral disease prediction profile by applying different weights to the plurality of microbiome data based on a skin area weighting table storing a list of microorganisms of interest for each disease and the importance of each skin area for each disease, by the above processor; A step of comparing the disease prediction profile with a plurality of standard profiles for each disease and disease stage stored in a pet standard database by the processor, and searching for a similar standard profile among the plurality of standard profiles that corresponds to the disease prediction profile based on the similarity between the disease prediction profile and the standard profile; A step of, by the processor, primarily calculating a baseline risk for each disease based on the similarity between the similar standard profile and the disease prediction profile, and secondarily calculating a final risk for each disease by correcting the baseline risk according to a microorganism-specific contribution score based on the disease-promoting or disease-protective correlation of microorganisms included in the list of microorganisms of interest; and A step of generating a health status report for a pet subject to inspection based on the calculated final risk level by the above processor; A comprehensive health examination method for pets including
  2. In Article 1, A step performed after the step of generating the plurality of microbiome data above, and a step of filtering microbiome data by skin area by a processor, A step of determining reference microbiome data based on at least one of the abundance and composition ratio of filtered microorganisms among a plurality of microbiome data by the above processor; A step of determining by the processor whether the composition ratio of the filtering microorganisms in each of the comparison target microbiome data, excluding the reference microbiome data among the plurality of microbiome data, exceeds the filtering threshold of the filtering microorganisms included in the reference microbiome data; A step of deleting the comparison target microbiome data that exceeds the filtering threshold when exceeded by the above processor; and A step of retaining comparison target microbiome data that does not exceed the filtering threshold when not exceeded by the above processor; A comprehensive health examination method for pets characterized by including
  3. In Article 2, The step of filtering microbiome data by skin area described above is, A step of generating filtered microbiome data by skin area by applying a filtering weight as it approaches the median value of the above filtering criteria; A comprehensive health examination method for pets characterized by further including
  4. In paragraph 1, The step of generating the above health status report is, A method for a comprehensive health examination of a pet, characterized by including the step of automatically generating a corresponding phrase among a predefined first result phrase according to a combination of the species, age, periodontal disease risk score, skin disease risk score, and intestinal disease risk score of the pet being examined by the above processor.
  5. In paragraph 4, The step of generating the above health status report is, A step of determining, by the processor above, whether at least one of the periodontal disease risk score, skin disease risk score, and intestinal disease risk score exceeds a predetermined risk threshold; A step of outputting the first result phrase by the processor when the risk threshold is less than the above; A comprehensive health examination method for pets, further comprising the step of outputting, by the processor, a second result phrase corresponding to the risk score among a plurality of second result phrases predefined as sub-items of the first result phrase when the risk threshold is exceeded.
  6. delete
  7. In paragraph 1, The above skin area weighting table is, A method for a comprehensive health examination of a pet, characterized in that the weighting by skin type is adjusted according to a weighting adjustment rule table corresponding to at least one of the species, age, sex, weight, oral care status, and presence of specific diseases of the pet being examined.
  8. delete
  9. In paragraph 1, A step of secondarily securing multiple microbiome data for each skin area by the above processor; A step of determining the likelihood of progression of at least one of periodontal disease, skin disease, and intestinal disease based on the amount of change in the abundance and composition ratio of microorganisms between each time point by the above processor, and outputting a prediction result and a warning signal; A comprehensive health examination method for pets characterized by further including
  10. In paragraph 1, The step of generating the above disease prediction profile is, A step of obtaining environmental variables of the pet subject to inspection by the above processor; A step of obtaining, by the above processor, the abundance and composition ratio of environmental microorganisms from domestic and overseas population standard databases in which the difference in abundance and composition ratio due to the above environmental variable exceeds a threshold value; and A step of generating a disease prediction profile based on the environmental variables and the abundance and composition ratio of the environmental microorganisms by the above processor; A comprehensive health examination method for pets characterized by including

Description

Method for Comprehensive Health Inspection of Pets for Predicting Skin Diseases, Intestinal Diseases, and Oral Diseases Based on Skin Samples The present invention relates to a technology for diagnosing the health status of companion animals, and more specifically, to a comprehensive health examination method for predicting skin diseases, intestinal diseases, and oral diseases by analyzing the microbiome contained in a skin specimen of a companion animal. Previously, the health status of pets was primarily assessed through visual inspection, blood tests, X-rays, or direct physical examinations by veterinarians, and the likelihood of skin, oral, or intestinal diseases was determined based on external signs such as skin rashes, hair loss, bad breath, and diarrhea. However, this approach had limitations in that it was difficult to detect subtle changes in the early stages of the disease, as signs often appeared only after the illness had progressed to a certain extent. Existing microbial analysis techniques have primarily involved collecting oral or stool samples to analyze the microbiome. However, collecting oral samples can cause discomfort and stress to pets, while collecting stool samples is cumbersome and difficult to manage hygienically. Furthermore, relying solely on samples collected from a single site limits the ability to comprehensively predict the pet's overall health status. Existing technologies required several improvements in these aspects. While visual inspection and mechanical diagnostic methods are effective for identifying already advanced lesions, they were not suitable for early detection of microbial imbalances that appear in the early stages of disease development. Furthermore, oral and stool-based microbiome analyses were limited to specific disease groups, posing limitations in simultaneously diagnosing or predicting skin, oral, and intestinal diseases. Figure 1 is a flowchart showing the overall flow of a comprehensive health examination method for pets performed by a pet examination server including a processor. Figure 2 is a flowchart showing the flow of the step (S150) of filtering microbiome data by skin area according to the present invention. FIG. 3 is a flowchart showing the flow of the step (S500) of generating a health status report of a pet subject to inspection according to the present invention. Figure 4 shows a skin area weighting table used in step S200 of the present invention. Figure 5 shows a weight adjustment rule table used in the S10 method of the present invention. Figure 6 shows a risk reflection table based on microorganisms of interest that is used in the process of adjusting the risk calculated in step S400 of the present invention. FIG. 7 is a flowchart showing the step of obtaining multiple microbiome data for each skin area in a time-series manner according to the present invention to analyze the possibility of disease progression. FIG. 8 is a diagram showing the flow of a step for generating a prediction profile by considering environmental variables of a pet according to an exemplary embodiment of the present disclosure. FIG. 9 is a diagram showing abundance data according to one embodiment of the present invention. FIG. 10 is a diagram illustrating occurrence frequency data according to one embodiment of the present invention. FIG. 11 is a diagram showing correlation data according to one embodiment of the present invention. FIG. 12 is a conceptual diagram showing the configuration of a pet inspection server according to one embodiment of the present invention. Embodiments of the present invention will be described in detail below with reference to the drawings. The description below is intended only to illustrate the embodiments and is not intended to limit or restrict the scope of the rights according to the present invention. Anything that can be easily inferred by a person skilled in the art from the detailed description and embodiments of the invention should be interpreted as falling within the scope of the rights according to the present invention. Detailed descriptions of matters widely known to those skilled in the art regarding the present invention are omitted. The terms used in this invention are described as general terms widely used in the technical field relating to this invention; however, the meaning of the terms used in this invention may vary depending on the intent of those skilled in the field, the emergence of new technologies, examination standards, or case law. Some terms may be selected at the discretion of the applicant, and in such cases, the meaning of the arbitrarily selected terms will be explained in detail. The terms used in this invention should be interpreted not merely in their dictionary meanings, but in a sense that reflects the overall context of the specification. FIG. 1 is a flowchart showing the overall flow of a comprehensive health examination method (S10) for pets performed by a pet examination server (10) inc