WO2023090715A2

WO2023090715A2 - Method and system for predicting skin irritation information for prescription containing retinol, and anti-irritant or anti-inflammatory composition against retinol, comprising irritation reducing agent as active ingredient

Info

Publication number: WO2023090715A2
Application number: PCT/KR2022/017219
Authority: WO
Inventors: 김경회; 강성수; 신중곤; 김윤관; 전승현; 김주현; 이선주
Original assignee: 주식회사 엘지생활건강
Priority date: 2021-11-17
Filing date: 2022-11-04
Publication date: 2023-05-25
Also published as: WO2023090715A3

Abstract

The present invention relates to a method and a system for predicting whether a prescription containing retinol will cause irritation, selecting a prescription on the basis of the prediction of whether irritation will be induced, and recommending a product matching the selected prescription. According to the present invention, a personally optimized prescription and product information may be selected and provided by predicting whether a product causes irritation, which may differ for each individual depending on the genetic information thereof, even for the same product. In addition, the present invention relates to: an anti-irritant or anti-inflammatory composition against retinol, comprising an irritation reducing agent as an active ingredient; and an information provision method for selecting a personalized irritation reducing agent for reducing irritation or inflammation caused by retinol, the method comprising a step for checking a polymorphic site of a retinol sensitivity single nucleotide polymorphism marker.

Description

Method and system for predicting skin irritation information of prescription containing retinol, and anti-irritation or anti-inflammatory composition using retinol containing irritation reliever as an active ingredient

The present invention relates to a method and system for predicting skin irritation information of a prescription containing retinol, and a composition for anti-irritation or anti-inflammatory using retinol containing an irritation reliever as an active ingredient.

Retinol is a type of vitamin A and is also referred to as a pure vitamin. Retinol is an FDA-approved ingredient for anti-wrinkle and anti-aging effects, and is widely used in anti-aging functional cosmetics. However, it is well known that skin irritation (stinging, exfoliation, dryness, etc.) often occurs when using retinol products (retinoid dermatitis). There are severe individual differences in the sensation of skin irritation caused by retinol, and the mechanism of occurrence has not yet been accurately identified. Currently, it is common to judge retinol sensitivity after directly using retinol products. In order to minimize side effects and apply the anti-aging efficacy of retinol to more people, research on causes of retinol sensitivity and development of diagnostic methods should be preceded.

Skin sensitivity can be influenced by environmental factors and factors such as age, sex and genetic variation. According to a number of recent genome wide field analysis studies (GWAS), it has been revealed that genetic mutations located in several genes are significantly related to these phenotypes in the case of skin irritation sensation or sensitive skin. In addition, individual genetic studies also confirmed the fact that the degree of skin irritation for the same substance can vary depending on the genotype. Retinol sensitivity is expected to exhibit similar properties.

However, it is difficult to find cases where genetic associations have been specifically analyzed for retinol sensitivity. In addition, since most of the studies were conducted on Europeans and Americans, and studies on Asian races were mainly on Chinese, it is difficult to apply the results of previous studies to Koreans as they are (Kemp et al., Molecules. 2017 Feb. 26;22(3), 2017).

Discovery of genetic mutations and genes associated with retinol sensitivity is expected to provide important information for understanding biological mechanisms and understanding and predicting individual retinol sensitivity. Therefore, in the present invention, genetic mutations and causative genes associated with retinol sensitivity are discovered in Koreans by using candidate gene analysis, and a model for predicting retinol sensitivity is developed using genetic mutations. In addition, based on big data of genetic information and skin measurement information, we aim to develop effective materials that can reduce retinol sensitivity in Koreans and apply them to products. In addition, stimulation information including the presence or absence of stimulation or stimulation level is predicted by comparing the stimulation score calculated by a predetermined method with the critical stimulation score determined through a statistical analysis method or a machine learning technique, and furthermore, a plurality of prescriptions including retinol. It is an object of the present invention to provide a method and system capable of recommending which prescription is suitable for application to a corresponding user.

On the other hand, retinol has the effect of increasing collagen synthesis in the skin and accelerating the turnover of the stratum corneum to promote cell generation. As the amount of retinol increases, its efficacy greatly increases, but even a small amount of retinol causes skin irritation. In addition to having the disadvantage that retinol itself is very unstable and denatured or decomposed over time, the use of retinol is extremely limited because it has a problem that its potency decreases and its effectiveness decreases.

There have been many attempts to solve the above problems with retinol by adding other ingredients together with retinol. Looking at cases where other substances have been added to alleviate the stimulation of retinol so far, cyclooxygenase ( Cheonmundong extract (10-2005-0121397), which suppresses inflammation and relieves skin irritation by inhibiting the production of PGE2, an inflammation-inducing eicosanoid in the Cyclooxygenase pathway, prevents skin irritation and inflammation and sensitive skin There is a watermelon endothelial extract (Korean Patent Publication No. 10-2005-0080480) that alleviates

Skin irritation caused by retinol does not simply appear in one form, but involves various inflammatory stimuli such as itching, stinging, and burning, and various inflammatory stimuli such as erythema and edema. Since it appears, the amount of use is limited, and there was a problem that it was not sufficient to relieve irritation simply by using one anti-inflammatory raw material.

According to a number of recent genome wide field analysis studies (GWAS), it has been revealed that genetic mutations located in several genes are significantly related to these phenotypes in the case of skin irritation sensation or sensitive skin. In addition, individual genetic studies also confirmed the fact that the degree of skin irritation for the same substance can vary depending on the genotype. Retinol sensitivity is expected to exhibit similar properties.

Under this background, the present inventors select a specific single nucleotide polymorphism (SNP) marker that has a significant correlation with retinol sensitivity and provide a personalized irritation reliever that can help relieve irritation or inflammation by retinol based on genetic information. The present invention was completed by confirming that it could be done.

One object of the present invention is to provide a single nucleotide polymorphism (SNP) marker for determining retinol sensitivity.

Another object of the present invention is to provide a composition for determining retinol sensitivity, including a probe capable of detecting a single nucleotide polymorphism (SNP) marker for determining retinol sensitivity or an agent capable of amplifying it.

Another object of the present invention is to provide a kit or microarray for determining retinol sensitivity comprising the above composition.

Another object of the present invention is to provide a method for providing information on retinol sensitivity, comprising identifying a polymorphic site of the single nucleotide polymorphism marker.

Another object of the present invention is to provide a method for predicting stimulation information of a prescription containing retinol.

Another object of the present invention is to provide a prescription selection method based on predictive stimulation information of a prescription containing retinol.

Another object of the present invention is to provide a prescription selection system based on the prediction of stimulation information of a prescription containing retinol and the presence or absence of the predicted stimulation.

Another object of the present invention is to provide single nucleotide polymorphism (SNPs) markers that affect skin irritation when a substance according to a prescription containing retinol is applied.

One object of the present invention is to provide a composition for anti-irritation or anti-inflammation by retinol containing an irritation reliever as an active ingredient.

Another object of the present invention is to provide a cosmetic composition, a quasi-drug composition, or a pharmaceutical composition comprising the composition as an active ingredient.

Another object of the present invention is to provide an information providing method for selecting a customized irritation reliever for irritation relief or inflammation relief by retinol, including the step of identifying a polymorphic site of a retinol-sensitive single nucleotide polymorphism marker.

Each description and embodiment disclosed in the present invention can also be applied to each other description and embodiment. That is, all combinations of the various elements disclosed herein fall within the scope of the present invention. In addition, it cannot be seen that the scope of the present invention is limited by the specific descriptions described below.

One aspect of the present invention provides a single nucleotide polymorphism (SNP) marker for determining retinol sensitivity.

Another aspect of the present invention provides a composition for determining retinol sensitivity, including a probe capable of detecting a single nucleotide polymorphism (SNP) marker for determining retinol sensitivity or an agent capable of amplifying it.

An individual's skin type can be classified according to the degree of retinol sensitivity.

As used herein, the term "polymorphism" refers to the case in which two or more alleles exist in one locus, and among polymorphic sites, a single nucleotide polymorphism in which only a single base differs from person to person (single nucleotide polymorphism, SNP). Preferred polymorphic markers have two or more alleles that exhibit an incidence of 1% or more, more specifically 10% or 20% or more in a selected population. A 'genetic polymorphic marker' is generally two or more genes at the same genetic locus (base). It refers to the case where an allele is observed, and generally, depending on the individual, there is a major allele/major allele, a major allele/minor allele, and a minor allele. Cases of minor allele/minor allele exist. In the present invention, it may be used interchangeably with "polymorphic marker", and may mean bases and base sites of lower alleles, or may be defined together with chromosome number and base position, but is not limited thereto.

As used herein, the term "allele" refers to several types of a gene present in the same locus of a homologous chromosome. Alleles are also used to indicate polymorphism, for example, SNPs have two types of alleles. In addition, it means a combination of two or more bases having the same number and base position of chromosomes, and the bases are a major allele with a high frequency of occurrence in individuals of a specific group and a lower frequency of occurrence than the upper allele. Includes minor allele.

In the present invention, the term "prescription" may be a substance having a composition of specific components, and is a concept that may further include a single or a plurality of substances together with a recommended method of use or a recommended lifestyle. In addition, it may mean cosmetics including a substance having a composition of a specific component as one component, but is not particularly limited thereto as long as it includes a substance having a composition of a specific component.

Specifically, the genetic polymorphic markers of the present invention are associated with retinol sensitivity, and when one or more minor alleles are possessed among two alleles, retinol sensitivity is the major allele allele)/major allele. That is, in the case of a major allele/minor allele and a minor allele/minor allele, the major allele/major allele ), it can be seen that the degree of skin irritation is higher or lower than the degree of skin irritation caused by retinol.

Since the single nucleotide polymorphism marker of the present invention can predict the individual's unique retinol sensitivity characteristics, it can also provide information on active ingredients that effectively act on changes in skin irritation caused by retinol, and personal customized skin care product information And life pattern information may be provided, but is not limited thereto.

In the present invention, the term "rs_id" refers to an rs-ID, an independent indicator assigned to all SNPs initially registered by NCBI, which began accumulating SNP information in 1998. rs_id described in this table means a SNP marker, which is a polymorphic marker of the present invention.

The single nucleotide polymorphism marker may be one or more single nucleotide polymorphism markers selected from the single nucleotide polymorphism markers shown in Table 1. The single nucleotide polymorphism markers shown in Table 1 may determine the degree of correlation with the degree of retinol sensitivity.

Specifically, the single nucleotide polymorphism marker may be one or more single nucleotide polymorphism markers selected from Table 1 related to the degree of skin irritation caused by retinol.

The association significance of skin irritation by retinol of the single nucleotide polymorphism marker of the present invention is less than 0.05, less than 0.01, less than 0.001, less than 0.0001, less than 0.00001, less than 0.000001, less than 0.0000001, less than 0.00000001, or less than 0.000000001, such as a p-value characterized by, but not limited to, a p-value. Specifically, the p-value may be less than 0.01, and more specifically, the p-value may be less than 0.1, but is not limited thereto.

The single nucleotide polymorphism (SNP) marker of the present invention may be any one or more selected from the markers shown in Table 1, but is not limited thereto. The single nucleotide polymorphism (SNP) markers may be one or more, and may be used in combination of a number capable of determining retinol sensitivity, such as two or more, three or more, four or more, but is not limited thereto.

The marker may be a SNP itself, a polynucleotide composed of 5-100 consecutive DNA sequences including the SNP site, or a polynucleotide composed of a sequence complementary thereto, but is not limited thereto.

In one embodiment, the single nucleotide polymorphism marker may be any one or more selected from the markers shown in Table 1 related to skin irritation by retinol, but is not limited thereto.

A description of markers selected from among the markers shown in Table 1 may be as follows.

For example, if the SNP ID is rs2293348, Chr.Position (GRCh ver. 37) is described as "7:55266757" and Allele is disclosed as G>A, this is the 55266757th base of human chromosome 7. represents G or A, and the base located on the left of ">" of the allele may mean a major allele, and the base located on the right may indicate a minor allele.

In one embodiment, a marker selected from Table 1 is

A polynucleotide consisting of 5-100 consecutive DNA sequences including base 38298203 of human chromosome 2, wherein base 38298203 is G or C (rs1056836); A polynucleotide consisting of 5-100 consecutive DNA sequences including the 25617775th base of human chromosome 3, wherein the 25617775th base is A or G (rs3773439); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 33164735 of human chromosome 6, wherein base 33164735 is A or C (rs3117040); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 55266757 of human chromosome 7, wherein base 55266757 is G or A (rs2293348); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 35245907 of human chromosome 11, wherein base 35245907 is A or G (rs10128586); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 27350687 of human chromosome 16, wherein base 27350687 is G or A (rs3024530); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 32688183 of human chromosome 17, wherein base 32688183 is A or C (rs2282692); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 60881555 of human chromosome 18, wherein base 60881555 is G or A (rs17841945); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 52216154 of human chromosome 19, wherein base 52216154 is A or C (rs45475696); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 47551909 of human chromosome 21, wherein base 47551909 is G or A (rs117668143); And it may consist of one or more polynucleotides selected from the group consisting of these complementary polynucleotides, but is not limited thereto. The markers described above are only partially described as examples in Table 1, and may be selected in the same manner as described above for chromosomes at other locations.

The alleles of the present invention have the same number of chromosomes in each individual, among them, there are a major allele and a minor allele of the SNP, and the base of the polymorphic site of the polymorphic marker is the lower As the allele increases by one, the upper allele can decrease by one, and as the upper allele increases by one, the lower allele can decrease by one. However, the range in which sub-alleles and upper alleles can increase and decrease is i) major allele/major allele, ii) major allele/minor allele ), iii) can be within three types of minor allele / minor allele, and the allele can be reduced or increased within the range of the three types, but is not limited thereto .

In addition, in the present invention, the marker is a marker that can determine retinol sensitivity as the bases of the polymorphic site of the polymorphic marker of the individual increase one by one in the minor allele. Specifically, among two alleles, one or more minor alleles are possessed (1) major allele/minor allele, (2) minor allele ( Retinol-induced skin irritation in individuals with the minor allele/minor allele) compared to those with the major allele/major allele, who are normal individuals. It can be judged to have a high or low degree of skin characteristics.

More specifically, as the number of minor alleles among the markers shown in Table 1 increases one by one, the degree of change in skin irritation caused by retinol can be determined. For example, among the markers shown in Table 1, when the upper allele G is the upper allele G and the lower allele is A (rs117668143) at base 47551909 of chromosome 21 of the individual, compared to a person who has G / G, G / G In the case of having A or A / A, it can be determined that skin irritation caused by retinol increases, but is not limited thereto.

The bases are described only in Table 1 as an example, and although not specifically described, they can be interpreted and derived as described above.

In the present invention, the term "probe capable of detecting a marker for determining retinol sensitivity" refers to a composition capable of diagnosing the degree of skin irritation caused by retinol by specifically hybridizing with a polymorphic region of the gene as described above. And, the specific method of such gene analysis is not particularly limited, and may be by any gene detection method known in the art to which this invention belongs. In addition, the term may be used interchangeably with the term 'for determining the degree of skin irritation by retinol'.

In the present invention, the term "an agent capable of amplifying a marker for determining retinol sensitivity" refers to a composition capable of diagnosing the degree of skin irritation caused by retinol by confirming the polymorphic region of the gene as described above through amplification, and specifically It means a primer capable of specifically amplifying the polynucleotide of the marker for determining the retinol sensitivity. In addition, the term may be used interchangeably with the terms 'for diagnosis of retinol sensitivity', 'for diagnosis of skin irritation level by retinol', and 'for determining the degree of skin irritation by retinol'.

The primers used to amplify the polymorphic marker are prepared in the form of template-directed DNA under suitable conditions (eg, four different nucleoside triphosphates and a polymerizing agent such as DNA, RNA polymerase or reverse transcriptase) in an appropriate buffer and at an appropriate temperature. Refers to a single-stranded oligonucleotide that can serve as a starting point for synthesis. The appropriate length of the primer may vary depending on the purpose of use, but is usually 15 to 30 nucleotides. Short primer molecules generally require lower temperatures to form stable hybrids with the template. The primer sequence need not be completely complementary to the template, but must be sufficiently complementary to hybridize with the template.

In the present invention, the term "primer" is a base sequence having a short free 3' terminal hydroxyl group, which can form a base pair with a complementary template and is the starting point for copying the template strand. A short sequence that functions as a point. A primer can initiate DNA synthesis in the presence of a reagent for polymerization (i.e., DNA polymerase or reverse transcriptase) and four different nucleoside triphosphates in an appropriate buffer and temperature. By performing PCR amplification, the skin type can be predicted through the degree of production of the desired product. PCR conditions and lengths of sense and antisense primers can be modified based on those known in the art.

The probes or primers of the present invention can be chemically synthesized using the phosphoramidite solid support method, or other well-known methods. Such nucleic acid sequences can also be modified using a number of means known in the art. Non-limiting examples of such modifications include methylation, "capping", substitution of one or more homologues of a natural nucleotide, and modifications between nucleotides, such as uncharged linkages such as methyl phosphonates, phosphotriesters, phosphoroamidates, carbamates, etc.) or to charged linkages (eg phosphorothioates, phosphorodithioates, etc.).

Another aspect of the present invention provides a kit for determining retinol sensitivity comprising the composition for determining retinol sensitivity. The kit may be a RT-PCR kit or a DNA chip kit, but is not limited thereto.

The kit of the present invention can diagnose the skin type by confirming the SNP polymorphic marker, which is a marker for determining skin type, through amplification or by checking the expression level of the SNP polymorphic marker to the mRNA expression level. As a specific example, the kit for measuring the mRNA expression level of the skin type determination marker in the present invention may be a kit including essential elements necessary for performing RT-PCR. In addition to each primer pair specific for the gene of the skin type determination marker, the RT-PCR kit is a test tube or other suitable container, a reaction buffer (with varying pH and magnesium concentration), deoxynucleotides (dNTPs) ), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNAse inhibitors, DEPC-water, sterile water, and the like. It may also include a primer pair specific to a gene used as a quantitative control. Also, specifically, the kit of the present invention may be a skin type determination kit including essential elements necessary for performing DNA chip. A DNA chip kit is a DNA chip kit in which nucleic acid species are attached in a gridded array to a generally flat solid support plate, typically a glass surface no larger than a slide for a microscope, and nucleic acids are regularly arranged on the surface of the chip. It is a tool that enables mass-parallel analysis by multiple hybridization reactions between nucleic acids on the chip surface and complementary nucleic acids included in the solution treated on the surface of the chip.

Another aspect of the present invention provides a microarray for determining retinol sensitivity comprising the composition for determining retinol sensitivity.

The microarray may include DNA or RNA polynucleotides. The microarray is composed of a conventional microarray except that the polynucleotide of the present invention is included in the probe polynucleotide.

A method of preparing a microarray by immobilizing a probe polynucleotide on a substrate is well known in the art. The probe polynucleotide refers to a polynucleotide capable of hybridization, and refers to an oligonucleotide capable of sequence-specifically binding to a complementary strand of a nucleic acid. The probe of the present invention is an allele-specific probe, which has a polymorphic site in nucleic acid fragments derived from two members of the same species, and thus hybridizes to DNA fragments derived from one member but does not hybridize to fragments derived from other members. . In this case, hybridization conditions should be sufficiently stringent to hybridize to only one of the alleles, showing a significant difference in hybridization strength between alleles. This can lead to good hybridization differences between different allelic forms. The probe of the present invention can be used in a method for diagnosing a skin type by detecting an allele. The diagnostic methods include detection methods based on hybridization of nucleic acids, such as Southern blotting, and may be provided in a form pre-bound to a substrate of a DNA chip in a method using a DNA chip. The hybridization can usually be performed under stringent conditions, for example, a salt concentration of 1 M or less and a temperature of 25 °C or more. For example, conditions of 5x SSPE (750 mM NaCl, 50 mM Na Phosphate, 5 mM EDTA, pH 7.4) and 25-30° C. may be suitable for allele-specific probe hybridization.

The process of immobilizing the probe polynucleotide associated with the skin diagnosis of the present invention on a substrate can also be easily prepared using these conventional techniques. In addition, hybridization of nucleic acids on microarrays and detection of hybridization results are well known in the art. The detection is, for example, by labeling a nucleic acid sample with a labeling material capable of generating a detectable signal including a fluorescent material such as Cy3 and Cy5, followed by hybridization on a microarray and generation from the labeling material. The hybridization result can be detected by detecting a signal that

Another aspect of the present invention is (a) amplifying the polymorphic site of the single nucleotide polymorphism marker in DNA obtained from a sample isolated from an individual or hybridizing with a probe; and (b) identifying the base of the polymorphic site amplified or hybridized in step (a).

As used herein, the term "subject" refers to a subject for diagnosis of skin irritation caused by retinol. DNA may be obtained from samples such as hair, urine, blood, various bodily fluids, separated tissues, isolated cells, or saliva, but is not limited thereto.

As the method for obtaining genomic DNA in step (a), any method known to those skilled in the art may be used.

Any method known to those skilled in the art may be used for amplifying the polymorphic site of the single nucleotide polymorphism marker or hybridizing with a probe from the DNA obtained in step (a). For example, it can be obtained by amplifying a target nucleic acid through PCR and purifying it. Other ligase chain reaction (LCR) (Wu and Wallace, Genomics 4, 560 (1989), Landegren et al., Science 241, 1077 (1988)), transcription amplification (Kwoh et al., Proc. Natl. Acad. Sci. USA 86, 1173 (1989)) and self-maintained sequence cloning (Guatelli et al., Proc. Natl. Acad. Sci. USA 87, 1874 (1990)) and nucleic acid-based sequence amplification (NASBA) may be used.

Among the above methods, determining the base of the polymorphic site in step (b) includes sequencing analysis, microarray hybridization, allele specific PCR, and dynamic allele-specific hybridization. DASH), PCR extension analysis, SSCP, PCR-RFLP analysis or TaqMan technique, SNPlex platform (Applied Biosystems), mass spectrometry (eg Sequenom's MassARRAY system), mini-sequencing method, Bio-Plex systems (BioRad), CEQ and SNPstream systems (Beckman), Molecular Inversion Probe array technologies (eg, Affymetrix GeneChip), and BeadArray Technologies (eg, Illumina GoldenGate and Infinium assays). By these methods or other methods available to those skilled in the art, one or more alleles in a polymorphic marker, including microsatellite, SNP or other types of polymorphic markers, can be identified. Determining the base of such a polymorphic site can be performed specifically through an SNP chip.

The method additionally (c) when the base of the amplified or hybridized polymorphic site contains one or more bases that are minor alleles according to the single nucleotide polymorphism marker, the degree of skin irritation by retinol is high or It may be judged to be low, but is not limited thereto.

In the present invention, the term "SNP chip" refers to one of DNA microarrays capable of identifying each base of hundreds of thousands of SNPs at once.

The TaqMan method includes (1) designing and constructing primers and TaqMan probes to amplify a desired DNA fragment; (2) labeling probes of different alleles with FAM dye and VIC dye (Applied Biosystems); (3) performing PCR using the DNA as a template and using the primers and probes; (4) after the PCR reaction is completed, analyzing and confirming the TaqMan assay plate with a nucleic acid analyzer; and (5) determining the genotypes of the polynucleotides of step (1) from the analysis results.

In the above, sequencing analysis may use a conventional method for nucleotide sequence determination, and may be performed using an automated genetic analyzer. In addition, allele-specific PCR refers to a PCR method of amplifying a DNA fragment where the SNP is located with a primer set including a primer designed with the base where the SNP is located as the 3' end. The principle of the method is, for example, when a specific base is substituted from A to G, a primer containing the A as the 3' terminal base and a primer in the opposite direction capable of amplifying a DNA fragment of an appropriate size are designed to perform PCR. When performing the reaction, when the base at the SNP position is A, the amplification reaction is normally performed and a band at the desired position is observed. When the base is substituted with G, the primer can complementarily bind to the template DNA, but 3 ' This is because the amplification reaction is not performed properly because the terminal side does not make complementary bonds. DASH can be performed by a conventional method, and can be specifically performed by a method by Prince et al.

On the other hand, PCR extension analysis first amplifies a DNA fragment containing the base where the single nucleotide polymorphism is located with a primer pair, and then inactivates it by dephosphorylating all nucleotides added to the reaction, whereby a SNP-specific extension primer, A primer extension reaction is performed by adding a dNTP mixture, dideoxynucleotide, reaction buffer and DNA polymerase. At this time, the extension primer takes the base immediately adjacent to the 5' direction of the base where the SNP is located as the 3' end, and the dNTP mixture excludes nucleic acids having the same base as the dideoxynucleotide, and the dideoxynucleotide represents the SNP. It is selected from one of the base types. For example, when there is a substitution from A to G, when a mixture of dGTP, dCTP and TTP and ddATP are added to the reaction, the primer at the base where the substitution occurs is extended by DNA polymerase, and after a few bases, A The primer extension reaction is terminated by ddATP at the position where the base first appears. If the substitution does not occur, since the extension reaction is terminated at that position, the base type representing the SNP can be determined by comparing the lengths of the extended primers.

At this time, as a detection method, when the extension primer or dideoxynucleotide is fluorescently labeled, the SNP can be detected by detecting fluorescence using a genetic analyzer (eg, ABI Model 3700, etc.) used for general base sequence determination. In the case of using unlabeled extended primer and dideoxynucleotide, the SNP can be detected by measuring molecular weight using matrix assisted laser desorption ionization-time of flight (MALDI-TOF) technique.

A method according to an aspect of the present invention includes (a) inputting SNP information of a prediction target entity to a prediction terminal, and (b) a threshold stimulus score determined by the prediction terminal and a stimulus score calculated according to the input SNP information calculating stimulus information according to a comparison result of and outputting the calculated stimulus information, wherein the threshold stimulus score is determined by a first threshold stimulus score prediction model, the first threshold stimulus score prediction model, The learning processor consists of pairs of stimulation data including (i) a stimulation score predetermined according to the SNP information and (ii) the presence or absence of stimulation or the level of stimulation when a substance containing retinol is applied to an individual having the SNP information. It may be a method for predicting skin irritation information of a prescription containing retinol, which is a model that learns a set of first threshold stimulation learning data to determine a threshold stimulation score that causes skin irritation when a substance containing retinol is applied.

In another aspect of the present invention, the SNPs marker selection device further comprises selecting one or more SNPs related to skin irritation when retinol is applied from among the plurality of SNPs included in the SNP information, and according to the input SNP information The calculated stimulus score may be calculated using at least some of the one or more SNPs selected by the SNPs marker selection device.

In another aspect of the present invention, the one or more SNPs associated with the skin irritation may be any one or more selected from Table 1.

In another aspect of the present invention, the stimulation score may be calculated by summing the assignment scores of each of the one or more SNPs, and the assignment score is a major allele and a sub allele included in each SNP It may be calculated using a first value determined according to the number of (minor allele) and a second value indicating the degree to which each SNP affects skin irritation.

In another aspect of the present invention, the first value is a major allele-major allele, a major allele-minor allele and a minor allele-sub allele SNPs type (type) Different values may be assigned to each.

In another aspect of the present invention, the first value may have a higher value as the number of lower alleles among the SNPs types increases.

In another aspect of the present invention, the allocation score may be calculated by multiplying the first value and the second value.

In another aspect of the present invention, different threshold stimulation scores are determined according to the type of substance added to the retinol, the threshold stimulation score is determined by a second threshold stimulation score prediction model, and the second threshold stimulation score prediction The model is such that the learning processor determines (i) a stimulus score predetermined according to SNP information, (ii) prescription information of one or more of a plurality of prescriptions including a retinol prescription and a prescription in which additional substances are further included in retinol, and (iii) A set of second threshold stimulation learning data consisting of pairs of stimulation data including the presence or absence of stimulation or the level of stimulation when a substance according to each prescription is applied to an individual having the SNP information is learned, and the substance according to each prescription is applied. It may be a model for determining a threshold irritation score that causes skin irritation when

In another aspect of the present invention, the threshold stimulus score is determined by a third threshold stimulus score prediction model, wherein the third threshold stimulus score prediction model determines that the learning processor determines (i) a stimulus score previously determined according to SNP information , (ii) one or more of age information, gender information, lifestyle information, environmental information, and skin characteristic information, and (iii) irritation or irritation when a substance containing retinol is applied to an individual having the SNP information It may be a model that learns a third threshold stimulation learning data set consisting of a pair of stimulation data including a degree and determines a threshold stimulation score that causes skin irritation when a substance according to each prescription is applied.

In another aspect of the present invention, different threshold stimulation scores are determined according to the type of substance added to the retinol, the threshold stimulation score is determined by a fourth threshold stimulation score prediction model, and the fourth threshold stimulation score prediction The model is such that the learning processor generates (i) a stimulus score predetermined according to SNP information, (ii) prescription information of one or more of a plurality of prescriptions including a retinol prescription and a prescription in which additional substances are further included in retinol, (iii) One or more of age information, gender information, lifestyle information, environmental information, and skin characteristic information, and (iv) the presence or absence of irritation or the degree of irritation when a substance according to each prescription is applied to an individual having the SNP information It may be a model that learns a fourth critical stimulus learning data set consisting of pairs of stimulus data to determine a threshold stimulus score that causes skin irritation when a substance according to each prescription is applied.

In another aspect of the present invention, the prediction terminal selects and outputs one or more prescriptions among the plurality of prescriptions using a comparison result of a predetermined threshold stimulation score for each prescription and a stimulation score calculated according to input SNP information Further steps may be included.

The system according to one aspect of the present invention provides (i) a stimulus score determined in advance according to SNP information and (ii) stimulation including the presence or absence of stimulation or the degree of stimulation when a substance containing retinol is applied to an individual having the SNP information A server for generating a first threshold stimulation score prediction model for learning a set of first threshold stimulation learning data pairs of data to determine a threshold stimulation score that causes skin irritation when a substance containing retinol is applied, and prediction Receives SNP information of a target individual, calculates a stimulus score according to the input SNP information, calculates stimulus information according to a comparison result of the threshold stimulus score determined by the first threshold stimulus score prediction model and the stimulus score, Including a prediction terminal that outputs calculated stimulus information,

It may be a system for predicting skin irritation information of a prescription containing retinol.

In another aspect of the present invention, a SNPs marker selection device for selecting one or more SNPs related to skin irritation when retinol is applied from among the plurality of SNPs included in the SNP information is further included, and the prediction terminal selects the SNPs marker A stimulus score may be calculated using at least some of the one or more SNPs selected by the device.

In another aspect of the present invention, the stimulation score may be calculated by summing the assignment scores of each of the one or more SNPs, and the assignment score is a major allele and a sub allele included in each SNP It may be calculated using a first value determined according to the number of minor alleles and a second value indicating the degree to which each SNP affects skin irritation.

In another aspect of the present invention, the prediction terminal selects and outputs one or more prescriptions among the plurality of prescriptions using a comparison result of a predetermined threshold stimulation score for each prescription and a stimulation score calculated according to input SNP information A prescription selection unit may be included.

The computer program according to an aspect of the present invention may be a computer program stored in a computer readable recording medium to execute the above-described method.

A composition according to one aspect of the present invention includes ectoine, trehalose, sucralfate, glucosamine, 4-t-butylcyclohexanol and omega- It may be a composition for anti-irritation or anti-inflammatory using retinol containing at least one irritation reliever selected from the group consisting of 9 (omega-9) as an active ingredient.

In another aspect of the present invention, the irritation reliever may be characterized in that it contains 0.1 to 30% by weight based on the total weight of the composition.

In another aspect of the present invention, it may be characterized in that the retinol is contained in an amount of 2500 to 6000 IU.

In another aspect of the present invention, the composition may be personalized.

In another aspect of the present invention, the anti-irritation or anti-inflammatory action of the anti-stimulant may be for a subject containing one or more single nucleotide polymorphism (SNP) markers for diagnosis of retinol sensitivity selected from Table 1.

In another aspect of the present invention, the single nucleotide polymorphism marker for diagnosing retinol sensitivity may be one or more single nucleotide polymorphism markers present in a gene encoding one or more proteins selected from the group consisting of COL6A2, EGFR, IL4R, and ADIPOQ. .

In another aspect of the present invention, the single nucleotide polymorphism marker for diagnosing retinol sensitivity may be one or more selected from the group consisting of rs117668143, rs1110470, rs6970262, rs2293347, rs2241766 and rs9882205.

In another aspect of the present invention, the single nucleotide polymorphism marker for diagnosing retinol sensitivity is 5 to 100 consecutive DNA sequences including base 47551909 of human chromosome 21, which is G or A (rs117668143), base 47551909 A polynucleotide consisting of ;, A polynucleotide consisting of 5-100 consecutive DNA sequences including the 27336427th base, wherein the 27336427th base of human chromosome 16 is G or A (rs1110470), human No. 7 The 55259763rd base of chromosome is G or A (rs6970262), a polynucleotide composed of 5-100 consecutive DNA sequences including the 55259763rd base, the 55201223rd base of human chromosome 7 is G or A ( rs2293347), a polynucleotide consisting of 5-100 consecutive DNA sequences containing the 55201223rd base, the 186570892nd base of human chromosome 3 being C or A (rs2241766), the 5th base containing the 186570892nd base -A polynucleotide consisting of 100 consecutive DNA sequences, wherein the 186570398th base of human chromosome 3 is A or G (rs9882205), a polynucleotide consisting of 5-100 consecutive DNA sequences containing the 186570398th base It may consist of one or more polynucleotides selected from the group consisting of nucleotides and their complementary polynucleotides.

A cosmetic composition according to one aspect of the present invention may be a cosmetic composition comprising the above-described composition as an active ingredient.

A quasi-drug composition according to one aspect of the present invention may be a quasi-drug composition containing the above-described composition as an active ingredient.

The pharmaceutical composition according to one aspect of the present invention may be a pharmaceutical composition for relieving irritation or treating inflammation by retinol, including the above-described composition as an active ingredient.

An information providing method according to an aspect of the present invention includes the steps of (a) obtaining a biological sample from an individual, (b) at least one single selected from the group consisting of rs117668143, rs1110470, rs6970262, rs2293347, r2241766 and rs9882205 from the biological sample Stimulation relief or inflammation relief by retinol, including amplifying the polymorphic site of the polymorphism marker or hybridizing with the probe and (c) identifying the base of the amplified or hybridized polymorphic site in step (b) It may be an information providing method for selecting a customized stimulation reliever for the skin.

In another aspect of the present invention, the irritation reliever may be at least one selected from the group consisting of ectoin, trehalose, sucralfate, glucosamine, 4-t-butylcyclohexanol, and omega-9.

In another aspect of the present invention, the sample may be hair, urine, blood, various bodily fluids, isolated tissues, isolated cells, or saliva.

In another aspect of the present invention, the amplification and confirmation of the polymorphic site may be performed using a SNP chip.

Another aspect of the present invention provides a system for predicting skin irritation information of a prescription containing retinol. Referring to Figures 1 to 5, it will be described in detail.

The skin irritation information prediction system includes a prediction terminal 100 and a server 200, and may optionally further include a data providing server 300. Here, the prediction terminal 100 and the server 200 may be separate components or may be integrated into one configuration.

The prediction terminal 100 predicts stimulus information likely to appear in the prediction target object when a substance containing retinone is applied to the prediction target object.

Referring to FIG. 2, the prediction terminal 100 includes a communication unit 110, an input unit 120, a memory 130, a processor 140, an output unit 150, a control unit 160, a power supply unit 170, and an interface. It includes section 180.

The communication unit 110 is a component for communication with an external device, and data transmission and reception with the external device may be possible through the communication unit 110 .

The input unit 120 may receive a command or data to be used in a component (eg, processor) of the prediction terminal 100 from the outside of the server 100 (eg, a user). The input unit 120 may include, for example, a microphone, a mouse, a keyboard, a key (eg, a button), or a digital pen (eg, a stylus pen).

The memory 130 may store various data used in the prediction terminal 100 . The data stored in the memory 130 may be, for example, a predictive model generated by the server 200, threshold stimulation scores for each prescription, and may also include input data or output data for software and commands related thereto. there is.

In addition, both information input to the prediction terminal 100 and information generated by the prediction terminal 100 may be stored in the memory 130 .

The processor 140 may perform a data processing or arithmetic function, and as at least a part of the data processing or arithmetic function, stores commands or data received from other components in a volatile memory, and stores the commands or data stored in the volatile memory. can be processed, and the resulting data can be stored in non-volatile memory. The processor 140 may include a stimulus score calculator 141, a stimulus information calculator 142, and a prescription selector 143.

The stimulus score calculation unit 141 calculates stimulus scores according to a preset method. Specifically, the stimulus score may be calculated by summing the allocation scores of one or more SNPs selected by the SNPs marker selection device 210 to be described later. The allocation score is a first value determined according to the number of major alleles and minor alleles included in each SNP, and a second value, which is the degree to which each SNP affects skin irritation. can be computed using

The first value is a value determined according to the number of major alleles and minor alleles included in each SNP. As for the SNPs type, a total of three may exist for each SNP: major allele-major allele, major allele-minor allele, and sub-allele-sub allele, and the first value is each Each type of may have a different value. More specifically, the first value may have a higher value as the number of sub alleles increases, '1' for major allele-major allele, '2' for major allele-minor allele, and '2' for minor allele. - In the case of a minor allele, a value of '3' may be assigned, but is not particularly limited thereto.

The second value means the influence index that each SNP has an effect on skin irritation (more specifically, it means the influence index that each SNP's minor allele affects skin irritation). Since each selected SNP may have a different degree of effect on skin irritation when a substance is applied according to a retinol prescription, in the present invention, by calculating the second value, which is the influence index of each SNP, when any genetic information is input later Predicted skin irritation information can be calculated using the calculated weights. The second value may be a value previously determined through a number of experiments.

The stimulus information calculation unit 142 compares the threshold stimulus score determined in the prediction model generated by the server 200 to be described later with the stimulus score determined according to the SNP information of the predicted subject, and calculates stimulus information according to the comparison result. do. Here, "stimulus information" is a concept including information related to stimulation, such as stimulation grade, presence or absence of stimulation, and stimulation probability, and these may be digitized information, but are not particularly limited thereto.

The prescription selecting unit 143 calculates and selects one or more prescriptions suitable for being prescribed for the prediction target entity using the information calculated by the stimulus information calculation unit 142 .

The output unit 150 may output information processed or calculated by the prediction terminal 100 to the outside, and a display and a speaker may be included here.

For example, the controller 160 may execute software to control one or more other components (eg, hardware or software components) of the prediction terminal 100 connected to the processor. The control unit 160 controls the communication unit 110, the input unit 120, the memory 130, the processor 140, the output unit 150, the power supply unit 170, and the interface unit 180 of the prediction terminal 100. can do.

The power supply unit 170 supplies power to the prediction terminal 100 . The power supply unit 170 may receive power from an external power source and supply power to the prediction terminal 100 .

The interface unit 180 may display information output from the output unit 150 through an interface.

At this time, the interface unit 180 is not limited to a specific type or form.

When a skin irritation prediction command is input through the prediction terminal 100, the processor 140 uses a threshold stimulation score generated by the server 200 to be described later and stored in the memory 130 of the prediction terminal 100, Predicted skin irritation information is calculated, and the calculated information is output. In another aspect, a skin irritation prediction command may be input through an external input unit, the input command may be transmitted to the server 200, and the skin irritation prediction may be performed by the server 200.

In another aspect of the present invention, when a skin irritation prediction command is input through the prediction terminal 100, the command is transmitted to the server 200, and the server 200 uses a threshold stimulation score stored in the server 200 Predicted skin stimulation information may be calculated in , and the prediction terminal 100 may receive information calculated in the server 200 and output the received information.

On the other hand, the information of the prediction target object, which is the target of the prediction skin irritation information output through the prediction terminal 100, may be input in the form of genetic data (including SNP information), and in another example, the form of identification data of the prediction target entity. may be entered as

When genetic data of a prediction target object is input to the prediction terminal 100, the input genetic data is queried to the prediction model, and predicted skin brightness change information and/or stimulus information of the prediction target object may be calculated.

On the other hand, when the identification data of the prediction target entity is input to the prediction terminal 100, the input identification data is transmitted to the data providing server 300, and the data providing server 300 identifies the object corresponding to the transmitted identification data. The genetic data is transmitted to the prediction terminal 100 again. That is, genetic data of subjects/prediction target entities is stored in advance in the data providing server 300, and if there is a data provision request (genetic data provision request) from the prediction terminal 100 or the server 200 to be described later, it is transmitted. It is possible to transmit the genetic data of the individual corresponding to the identified identification data to the prediction terminal 100 or the server 200. That is, personal information can be protected through a configuration in which genetic data, which is personal information, is stored in a separate data providing server 300 and genetic data of an individual corresponding to the transmitted identification data is provided.

Meanwhile, referring to FIGS. 3 and 6 , the server 200 may include an SNPs marker selection device 210, a measurement device 220, a predictive model generating device 230, and a data processing device 240.

The SNPs marker selection device 210 is configured to select one or more SNPs that cause skin irritation when a substance containing retinol is applied from among a plurality of SNPs. Although described in detail in the following examples, for example, some or all of 56 SNPs that affect skin irritation may be selected by the SNPs marker selection device 210, but are not particularly limited thereto.

The measuring device 220 is configured to obtain information including skin measurement values by measuring the skin of a specific subject. The skin measurement values may include information related to skin conditions such as moisture level, skin brightness value, and skin irritation level, but are not limited to the above information as long as the information is related to the skin.

Meanwhile, the data processing device 240 is configured to process information measured by the measuring device 220 and data input from the outside. For example, the skin _brightness change value (S = S - S _O ) may be calculated, and stimulus data may be calculated by processing the survey result/skin image transmitted from the subject H and the interview result transmitted from the expert A in a predetermined method. Here, skin irritation may include erythema, skin peeling, burning sensation, itching, and the like, and is not particularly limited thereto, and is a concept collectively referring to abnormal reactions.

Also, the data processing device 240 may improve the performance of the predictive model by adding new information to the information stored in the existing memory.

When information having a predetermined format (form) is stored in the memory, cumbersome procedures such as additional information conversion and additional preprocessing can be omitted.

The data processing device 240 may play a role of converting various types of information into a standardized format for each type of information. For example, since information collected from subjects may include personal information, anonymization of information may be performed, and functions such as conversion into codes optimized for computer operations and assignment of control numbers may be performed. In addition, the data processing device 240 corrects errors for each measurement device 220 or standardizes measurement information values (eg, values may be standardized in a (measured value-standard)/standard deviation method) Thus, it is possible to ensure the consistency of information.

In addition, the data processing device 240 calculates the outliers of the information and the outliers of the information measured by the measurement device 220 in a predetermined method, and processes the information as noise when the outliers are out of a preset value range, and stores the information in a memory. It may be notified so that it is not stored or a warning signal is output so that information re-input/re-measurement can be performed.

For example, the data processing device 240 may process input information as noise so that it is not stored in memory or generate a warning signal when a standard deviation difference of 3 times or more compared to the menopause response of a male gender user occurs. It can be output so that information re-input/re-measurement can be performed.

The predictive model generating device 230 is configured to generate a model for predicting skin irritation information when a substance containing retinol is applied.

Referring to FIG. 3, the predictive model generating device 230 may include a communication unit 231, an input unit 232, a processor 233, a memory 234, a running processor 235, and a control unit 236, The prediction model generator 230 is also implemented in the form of a computing device capable of calculation, and includes the communication unit 110, the input unit 120, the memory 130, the processor 140, and the control unit 160 of the prediction terminal 100 described above. ) and a configuration having the same function may be applied.

Meanwhile, the learning processor 235 may perform data processing or arithmetic functions like the processor 140, but may further include a hardware structure specialized for AI model processing.

The memory 234 of the prediction model generating device 230 may include a subject integration database 234a and a prescription database 234b.

Information collected from subjects is stored in the subject integration database 234a to be used as learning data. Types of information stored in the subject integrated database 234a may include some or all of genetic information including SNP information, skin irritation information, gender information, age information, environmental information, lifestyle information, and skin characteristic information. . Here, the skin irritation information refers to the degree of skin irritation (or the presence or absence of stimulation, the probability of stimulation) caused by the application of a substance according to a prescription containing retinol alone or optionally additional substances, and the environmental information refers to height and weight information, lifestyle information may include the degree of sunlight exposure, use of UV blockers, eating habits information, smoking status, and drinking level, skin characteristic information may include skin color information, and gender information may include It may include male/female information, and the age information may include actual age information (age information specified as 15, 37, etc.), group age information (age information grouped into teens, 20s, 30s, etc.) ) and the like, but is not particularly limited thereto.

Information on a plurality of prescriptions including retinol is stored in the prescription database 234b. For example, information on a prescription containing only retinol can be stored as prescription 1, information on a prescription containing retinol and magnesium as prescription 2, information on a prescription containing retinol and zinc as prescription 3, Information about a prescription containing retinol and an irritating agent may be stored as prescription 4.

Hereinafter, with reference to FIGS. 4 to 11 , a process of generating a predictive model by the predictive model generator 230 and determining a threshold stimulus score by the generated predictive model will be described in detail.

Generation of the predictive model may be generated as the learning processor 235 learns the training data.

In addition, learning here is a concept of deriving an optimal correlation between a plurality of data to be learned by training a plurality of learning data in a preset artificial neural network (ANN) model. Here, the artificial neural network model is DNN (Deep Neural Network), CNN (Convolutional Neural Network), DCNN (Deep Convolutional Neural Network), RNN (Recurrent Neural Network), RBM (Restricted Boltzmann Machine), DBN (Deep Belief Network), It may be a model based on a Single Shot Detector (SSD) or a Multi-layer Perceptron (MLP), but is not limited thereto and various artificial neural network models may be applied to the present invention. In addition, in another aspect of the present invention, correlations between a plurality of data to be studied may be derived using various statistical techniques (linear regression model, random forest, lasso, ridge, elastic net, MDR, SVM, etc.) .

In one aspect of the present invention, referring to FIG. 6, the learning processor 235 determines the irritation score determined according to the SNP information of each individual - the presence or absence of skin irritation when a substance containing retinol is applied to an individual having the SNP information (That is, when a substance containing retinol is applied by learning the first threshold stimulation learning data consisting of pairs of stimulation (in the case of an individual experiencing stimulation, no stimulation in the case of an individual experiencing no stimulation), A predictive model that outputs (determines) a threshold irritation score at which skin irritation is induced may be generated.

Here, the stimulus score may be determined according to the number and type of SNPs included in the SNP information and selected by the SNPs selection device 210. More specifically, the stimulus score may be calculated using the first value and the second value, the first value is determined according to the number of upper alleles and lower alleles included in each SNP, and the second value is a value that each SNP has an effect on skin irritation, and may be a value previously determined through a preliminary experiment.

That is, the first value may have a higher value as the number of sub-alleles included in each SNP increases. In the case of major allele-major allele, '1', in case of major allele-minor allele, '2', minor allele- In the case of a minor allele, a value of '3' may be given, but is not particularly limited thereto.

The threshold stimulus score determined (predicted) in the first threshold stimulus score prediction model generated by the learning processor 235 may be transmitted to the prediction terminal 100 and stored in the memory 130 of the prediction terminal 100. . When genetic data including SNP information of a prediction target entity is queried through the input unit 120 of the prediction terminal 100, the stimulus information calculation unit 142 of the prediction terminal 100 calculates a stimulus score according to the queried SNP information. and calculate stimulus information using the comparison result data obtained by comparing with the threshold stimulus score determined in the first threshold stimulus score prediction model (eg, in the case of an individual having a stimulus score greater than the threshold stimulus score, the stimulus It is calculated as having a stimulus score, and it can be calculated as having no stimulus in the case of an individual having a stimulus score smaller than the threshold stimulus score). The calculated stimulus information may be output in the form of visible information to a system user through the output unit 150 .

Meanwhile, in FIG. 6, the genetic data of the prediction target entity is directly input into the prediction terminal 100, but as shown in FIG. 7, the prediction terminal 100 inputs the identification data of the prediction target entity, The identified identification data is transmitted to the data providing server 300, and the data providing server 300 transmits the genetic data of the individual corresponding to the transmitted identification data to the prediction terminal 100. It can also be included in the scope of the present invention there is.

According to one aspect of the present invention, prior to learning the first threshold stimulus learning data, grouping the first threshold stimulus learning data based on one or more information selected from gender, age, environment information, lifestyle information, and skin characteristic information (For example, when gender is the criterion, data obtained from a male individual and data obtained from a female individual are grouped respectively) to generate a first threshold stimulus score prediction model for each grouped data (ie, generation A first threshold stimulus score prediction model for each group may be generated). In this case, prior to calculating the stimulus score of the object, the stimulus score is calculated by determining which group the object belongs to according to one or more information selected from among gender, age, environmental information, lifestyle information, and skin characteristics, and the corresponding group The presence/absence of a stimulus may be predicted through the threshold stimulus score determined by the first threshold stimulus score prediction model. The selection of prediction models for each group according to gender, age, environmental information, lifestyle information, and skin characteristics and skin irritation prediction are the aforementioned skin brightness change prediction model and irritation prediction model described in the present specification, and the threshold irritation score prediction model described later. The same can be applied in

In one aspect of the present invention, referring to FIG. 8 , the learning processor 235 determines a stimulus score determined according to the SNP information of each individual - one or more prescription information among a plurality of prescriptions including a prescription including retinol - the SNP information By learning the second threshold stimulation learning data consisting of pairs of skin irritation when a substance according to each prescription is applied to an individual having a plurality of prescriptions, each of a plurality of prescriptions A prediction model outputting a threshold irritation score at which skin irritation is induced may be generated.

That is, when the learning processor 235 generates a second threshold stimulus score prediction model by learning the second threshold stimulus learning data, threshold stimulus scores for each of a plurality of prescriptions may be determined. The threshold stimulus scores determined in the second threshold stimulus score prediction model generated by the learning processor 235 may be transmitted to the prediction terminal 100 and stored in the memory 130 of the prediction terminal 100 . When genetic data including SNP information of a prediction target entity is queried through the input unit 120 of the prediction terminal 100, the stimulus information calculation unit 142 of the prediction terminal 100 calculates a stimulus score according to the queried SNP information. and calculate stimulation information for each prescription using the comparison result data obtained by comparing with the threshold stimulation score determined in the second threshold stimulation score prediction model (eg, higher than the threshold stimulation score according to prescription A). In the case of an object with a large stimulation score, stimulation is calculated when a substance according to prescription A is applied, and in the case of an object with a stimulation score smaller than the critical stimulation score according to prescription B, stimulation is applied when a substance according to prescription B is applied. can be computed without it). The calculated stimulus information may be output in the form of visible information to a system user through the output unit 150 .

Prescriptions containing additional substances in retinol are very diverse, and depending on the components of the additional substances, the degree of irritation that may appear may vary even when applied to the same object. The prescription selector 33 selects an optimized prescription using the value of the critical stimulation score determined differently according to the additional substance and provides the selected prescription to the user.

The prescription selection unit 143 may select prescription information obtained by calculating one or more prescriptions calculated to be non-stimulating among a plurality of prescriptions as appropriate to be prescribed to a corresponding individual, and output the selected prescription information through the output unit 150 .

Meanwhile, in FIG. 8, although the genetic data of the prediction target entity is directly input into the prediction terminal 100, the identification data of the prediction target entity is input to the prediction terminal 100, and the input identification data is sent to the data providing server. 300, and the data providing server 300 may also include an aspect of transmitting genetic data of an individual corresponding to the transmitted identification data to the prediction terminal 100.

In another aspect of the present invention, referring to FIG. 9 , the learning processor 235 provides stimulation score - one or more of age information/gender information/lifestyle information/environmental information/skin characteristic information-retinol to an individual having the SNP information. By learning the third threshold stimulus learning data consisting of pairs of skin irritation when a substance containing retinol is applied, a prediction model outputting a threshold stimulus score at which skin irritation is induced when a substance containing retinol is applied is generated. can do. Here, age information/gender information/lifestyle information/environmental information/skin characteristic information are additional variables that affect the stimulation score.

The threshold stimulus score determined (predicted) in the third threshold stimulus score prediction model generated by the learning processor 235 may be transmitted to the prediction terminal 100 and stored in the memory 130 of the prediction terminal 100. . When one or more information of genetic data including SNP information of a prediction target entity and age information/gender information/lifestyle information/environmental information/skin characteristic information is queried through the input unit 120 of the prediction terminal 100, the prediction The stimulus information calculator 142 of the terminal 100 calculates a stimulus score according to the input SNP information and age information/gender information/lifestyle information/environmental information/skin characteristic information, and calculates a stimulus score determined by a third threshold stimulus score prediction model. Stimulus information may be calculated through comparison result data obtained by comparing with a critical stimulus score. The calculated stimulus information may be output in the form of visible information to a system user through the output unit 150 .

Meanwhile, in FIG. 9, although the genetic data of the prediction target entity is directly input into the prediction terminal 100, the identification data of the prediction target entity is input to the prediction terminal 100, and the input identification data is sent to the data providing server. 300, and the data providing server 300 may also include an aspect of transmitting genetic data of an individual corresponding to the transmitted identification data to the prediction terminal 100.

In one aspect of the present invention, referring to FIG. 10 , the learning processor 235 calculates a stimulus score - one or more prescription information among a plurality of prescriptions including a prescription containing retinol - age information/gender information/lifestyle information/environmental information / Information on one or more of the skin characteristics information - Learning the fourth threshold stimulation learning data consisting of pairs of skin irritation when applying substances according to each prescription to an individual having the SNP information, and learning substances according to a plurality of prescriptions A predictive model outputting a threshold irritation score at which skin irritation is induced for each of a plurality of prescriptions when each is applied may be generated. Here, age information/gender information/lifestyle information/environmental information/skin characteristic information are additional variables that affect the stimulation score.

The threshold stimulus scores determined (predicted) in the fourth threshold stimulus score prediction model generated by the learning processor 235 may be transmitted to the prediction terminal 100 and stored in the memory 130 of the prediction terminal 100. . When one or more information of genetic data and age information/gender information/lifestyle information/environmental information/skin characteristic information including SNP information of a prediction target entity is queried through the input unit 120 of the prediction terminal 100, the prediction terminal The stimulus information calculation unit 142 of (100) calculates a stimulus score according to the queried SNP information/age information/gender information/lifestyle information/environmental information/skin characteristic information, and calculates a threshold determined in the fourth threshold stimulus score prediction model. Stimulation information for each prescription may be calculated using the comparison result data obtained by comparing the stimulation scores (eg, in the case of an individual having a stimulation score greater than a threshold stimulation score according to prescription A, according to prescription A) When the substance is applied, it is calculated as having irritation, and in the case of an individual having a stimulation score smaller than the threshold stimulation score according to prescription B, it can be calculated as having no stimulation when the substance according to prescription B is applied). The calculated stimulus information may be output in the form of visible information to a system user through the output unit 150 .

Meanwhile, in FIG. 10, although the genetic data of the prediction target entity is directly input into the prediction terminal 100, the identification data of the prediction target entity is input to the prediction terminal 100, and the input identification data is sent to the data providing server. 300, and the data providing server 300 may also include an aspect of transmitting genetic data of an individual corresponding to the transmitted identification data to the prediction terminal 100.

In one aspect of the present invention, referring to FIG. 6, the learning processor 235 determines the number of selected one or more SNPs included in genetic information of a specific individual and the stimulus score determined in advance according to the type of SNPs, and the specific individual A set of first threshold stimulation learning data consisting of a pair of stimulation with or without stimulation when retinol is applied is learned.

That is, the first threshold stimulus learning data is the stimulus score (predetermined according to the number of SNPs selected by the SNPs selection unit and the type of SNPs included in the SNP data included in the genetic information of an individual) - stimulus type/ It means data consisting of pairs of no (stimulus in the case of subjects who experienced stimulation such as erythema, stimulation in the case of subjects who experienced no stimulation), and the first threshold stimulation learning data set is a plurality of It means a concept including the first threshold stimulus learning data. That is, the first threshold stimulation learning data may mean data obtained by quantifying a correlation between a stimulation score according to application of retinol and presence/absence of stimulation.

In the present invention, a threshold stimulation score that causes skin irritation when retinol is applied is determined by learning data consisting of pairs of irritation score-stimulation presence/absence.

When the learning processor 235 generates a first threshold stimulus score prediction model by learning the first data set, a threshold stimulus score may be determined.

Thereafter, genetic information including SNP data of a specific individual is input through the input unit 120 . The stimulus score calculation unit 141 calculates stimulus scores according to the number of SNPs and SNPs types that match the previously selected SNPs with respect to the input genetic information. The stimulus score calculated by the stimulus score calculator 141 is transmitted to the stimulus information calculator 142, and the stimulus information calculator 142 converts the stimulus score calculated by the stimulus score calculator 141 to a threshold determined by the prediction model. By comparing with the stimulus score, comparison result data is generated. In addition, the stimulation information calculation unit 142 is configured to predict the presence or absence of stimulation when retinol is applied to the individual having the genetic information input through the input unit 120 using the comparison result data. For example, when comparison result data with a calculated stimulation score higher than the threshold stimulation score is generated, it is predicted that there will be stimulation or more when retinol is applied, and when comparison result data with the calculated stimulation score lower than the threshold stimulation score is generated, retinol is applied. It can be predicted that there will be no or little stimulation at the time.

According to an embodiment of the present invention, prior to learning a set of first threshold stimulus learning data, the first threshold stimulus learning data is based on one or more information selected from gender, age, environment information, lifestyle information, and skin characteristics. (For example, if gender is the criterion, data obtained from a male individual and data obtained from a female individual are grouped respectively) to generate a first prediction model for each grouped data (ie, generated A first predictive model for each group may be generated). In this case, prior to calculating the stimulus score of the object, the stimulus score is calculated by determining which group the object belongs to according to one or more information selected from among gender, age, environmental information, lifestyle information, and skin characteristics, and first prediction It is possible to predict the presence or absence of stimulation according to the application of retinol in the corresponding group of the model. The selection of prediction models for each group according to gender, age, environmental information, lifestyle information, and skin characteristics and prediction of skin irritation are the second threshold stimulus score prediction model, the third threshold stimulus score prediction model, and the fourth threshold stimulus described in the present specification. The same can be applied to the score prediction model.

The threshold stimulus score determined by the first threshold stimulus score prediction model may be transmitted to the prediction terminal 100 and stored in the memory 130 of the prediction terminal 100 . When genetic data including SNP information of a prediction target entity is queried through the input unit 120 of the prediction terminal 100, the stimulus information calculation unit 142 of the prediction terminal 100 calculates the threshold stimulus score stored in the memory 130 and , The stimulus scores calculated by the stimulus score calculation unit 141 may be compared to calculate predicted stimulus information, and the calculated predicted stimulus information information will be output in the form of visible information to the system user through the output unit 150. can

On the other hand, in another aspect of the present invention, as shown in FIG. 7, identification data of a prediction target entity is input to the prediction terminal 100, the input identification data is transmitted to the data providing server 300, and the data providing server 300 ) may transmit genetic data of an individual corresponding to the transmitted identification data to the prediction terminal 100.

In one aspect of the present invention, referring to FIG. 8 , the learning processor 235 provides a stimulation score - one or more prescription information among a plurality of prescriptions including a prescription containing retinol - any one of the above prescriptions to an individual having the SNP information. A second threshold stimulation score for determining a threshold stimulation score that induces skin irritation for each prescription by learning a set of second threshold stimulation learning data consisting of pairs of skin irritation when a substance according to the prescription of A predictive model can be created.

Many prescriptions are concepts that include retinol prescriptions and prescriptions that contain additional substances to retinol. That is, the second threshold stimulation learning data may mean data obtained by quantifying the correlation between stimulation scores and stimulation presence/absence when a substance according to any one of a plurality of prescriptions is applied to an individual having specific SNP data. .

That is, by adjusting the weight that affects the skin brightness change for each SNP in each prescription (specifically, the second value Adjust) A second skin brightness change prediction model may be generated.

The second skin brightness change prediction model generated by the learning processor 235 may be transmitted to the prediction terminal 100 and stored in the model storage unit 131 of the prediction terminal 100 . When genetic data including SNP information of a prediction target entity is queried through the input unit 120 of the prediction terminal 100, the skin brightness change information calculation unit 141 of the prediction terminal 100 generates a second skin brightness change prediction model. It is possible to calculate the predicted skin brightness change information for each prescription using the formula, and the calculated information can be output in the form of visible information to the system user through the output unit 150 .

In addition, the prescription selector 143 calculates one or more prescriptions suitable for prescription to the prediction target object by using the predicted skin brightness change information calculated by the skin brightness change information calculation unit 141 . For example, a prescription having a large value of the predicted skin brightness change information calculated by the skin brightness change information calculation unit 141 may be calculated as a prescription suitable for being prescribed to a prediction target object.

Meanwhile, in FIG. 10, the genetic data of the prediction target entity is directly input into the prediction terminal 100, but as shown in FIG. 7, the prediction terminal 100 inputs the identification data of the prediction target entity, and the input An aspect in which the identification data is transmitted to the data providing server 300 and the data providing server 300 transmits genetic data of an individual corresponding to the transmitted identification data to the prediction terminal 100 may also be included in the scope of the present invention. .

Hereinafter, a method for predicting skin irritation of a prescription containing retinol according to another embodiment of the present invention will be described in detail with reference to FIGS. 14 to 18 . The skin irritation prediction method according to an aspect of the present invention may be performed using the prediction model generated by the server 200 described above.

Referring to FIG. 14, subject phenotype data (stimulation score and presence/absence of irritation) and genotype data (SNP information) are obtained, and the device 210 for selecting SNPs markers using the obtained data affects skin irritation when retinol is applied. Select one or more SNPs markers. Next, the learning processor 235 of the server 200 learns the learning data (any one of the first to fourth threshold stimulus learning data) to derive a correlation between the phenotypic data and the genotype data, Create any one of the 4 threshold stimulus score prediction models. Next, the genetic data or identification data of the predicted object is input, the stimulus score according to the input genetic data is calculated, and the stimulus information is calculated by comparing it with the threshold stimulus score. Next, the prescription selection unit 143 calculates one or more prescriptions suitable for being prescribed to the prediction target object by using the calculated stimulus information.

14 to 17, the predictive model generating device 230 of the server 200 learns first to fourth threshold stimulus learning data to determine a threshold stimulus score that causes skin irritation when a substance containing retinol is applied. First to fourth threshold stimulus score prediction models are generated, and the determined threshold stimulus score is transmitted to the prediction terminal 100 .

A stimulus prediction command is input through the prediction terminal 100, and genetic data (which can be directly input or transmitted through a data providing server) and/or age/gender/lifestyle/environment of a prediction target object to be predicted. / Using one or more data of skin characteristic information, the irritation score of the prediction target object may be calculated.

The stimulus information calculation unit compares the calculated stimulus score with the determined threshold stimulus score, and calculates stimulus information using the comparison result data.

This information may be calculated for each of a plurality of prescriptions, and the prescription selector selects and outputs one or more prescriptions suitable for prescription to the prediction target entity using the calculated stimulus information.

The method according to an embodiment of the present invention described above may be implemented in the form of computer program instructions that can be executed through various computer means and recorded in a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program instructions recorded on the medium may be those specially designed and configured for the present invention or those known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

As one aspect for achieving the object of the present invention, the present invention provides a composition for anti-irritation or anti-inflammation by retinol containing an irritation reliever as an active ingredient.

In the present invention, the term "retinol" is a kind of vitamin A and is also referred to as pure vitamin. It is a substance that plays an important role in maintaining the original function of epidermal cells of the skin. However, skin irritation often occurs when retinol is used. The stimuli include acute allergic-like reactions, redness, itching, dryness, excessive keratin, acute/chronic pain, edema, inflammatory reactions, etc., and show great differences in degree and timing depending on the individual, and There are differences in the degree of stimulation.

The retinol may be contained in an amount of about 2500 to 6000 IU, but is not limited thereto. For example, it may be about 2500 to 6000 IU, about 3000 to 6000 IU, or about 3500 to 5500 IU.

The present invention found that the effect of retinol on the skin increases proportionally with the concentration up to about 6000 IU, and no significant difference occurs above 6000 IU (S.Kang et al., J.InvestigativeDermatology , 105, 549-556, 1995), it is intended to provide a composition that maximizes the effect on the skin by setting 5000 IU as a content that can increase the efficacy of retinol while minimizing skin irritation. However, since even a composition having a concentration of 2500 IU or more of retinol causes great irritation to the skin when used, various types of irritation relievers were examined to reduce irritation to the skin.

For the purpose of the present invention, the irritation reliever is ectoine, trehalose, sucralfate, glucosamine, 4-t-butylcyclohexanol and omega- It may be one or more selected from the group consisting of 9 (omega-9), but is not limited thereto.

The term 'ectoine' is a natural compound (C ₆ H ₁₀ N ₂ O ₂ ) found in several types of bacteria. It is found in high concentrations in halophilic microorganisms and is resistant to salt and temperature stress.

The term 'trehalose' is a kind of disaccharide formed by 1, 1-glycosidic linkage of glucose. Trehalose is known to have a sweet taste and high moisturizing ability.

The term 'sucralfate' is a drug used to treat gastric ulcer, gastroesophageal reflux disease, gastric inflammation, and the like, and to prevent stress ulcers. The salt portion of cralfate combines with fibroin on the stomach wall to form a film, and the film coats the stomach wall to protect the stomach from gastric acid, bile, etc., thereby alleviating stomach pain, and sucralfate functions as an antacid. can do.

The term 'glucosamine' is a compound in which hydroxyl groups at two sites in a D-glucose molecule are substituted by amino groups, and is an important functional monosaccharide. Glucosamine is present in almost all organisms including bacteria, yeast, filamentous fungi, plants and animals, and is a major component of glycoproteins and proteoglycans, as well as a major component of chitosan and chidin.

The term '4-t-butylcyclohexanol' refers to an inhibitor of transient receptor potential vanilloid-1 (TRPV1). TRPV1 is an ionic receptor that is activated by molecules from the vanilloid family, such as capsaicin in chili peppers.

The term 'omega-9' is an unsaturated fatty acid series having a carbon-carbon double bond at the omega-9 position, and is not classified as an essential fatty acid.

The irritation reliever of the present invention may be contained in about 0.1 to 30% by weight based on the total weight of the composition, but is not limited thereto. For example, about 0.1 to 30% by weight, about 1 to 30% by weight, about 1 to 25% by weight, about 1 to 20% by weight, about 1 to 15% by weight of the irritation reliever of the present invention based on the total weight of the composition. , about 1 to 10 weight percent, or about 1 to 5 weight percent.

For the purpose of the present invention, the irritation reliever imparts an effect capable of attenuating stimulation or inflammatory response caused by retinol.

In the present invention, the term “about” may be preceded by a specific numerical value. As used in this application, the term "about" includes not only the exact number that follows the term, but also a range that is or is close to that number. It can be determined whether the number is close to or nearly the specific number mentioned, given the context in which it is presented. As an example, the term “about” can refer to a range of -10% to +10% of a numerical value. As another example, the term "about" can refer to a range of -5% to +5% of a given numerical value. However, it is not limited thereto.

The composition is characterized in that it is personalized. Specifically, it is possible to provide a personalized irritation reliever to an individual having a single nucleotide polymorphism (SNP) marker for diagnosing specific retinol sensitivity.

For example, the single nucleotide polymorphism (SNP) marker for diagnosing retinol sensitivity may be any one or more selected from Table 1 or Table 3, but is not limited thereto.

The genetic polymorphic markers of the present invention are associated with retinol sensitivity, and when one or more minor alleles are possessed among two alleles, retinol sensitivity is associated with the major allele/ It can be said that there is significance compared to individuals with a major allele. That is, in the case of a major allele/minor allele and a minor allele/minor allele, the major allele/major allele ), it can be seen that the degree of sensitivity by retinol is high or low compared to the case of having skin characteristics. On the other hand, if you have the allele of the retinol sensitivity-related significant polymorphism marker, or if you have the major allele/major allele, you can have skin characteristics with high or low sensitivity by retinol. Since the effect can be measured, information can be provided in selecting a customized irritation reliever for irritation relief or inflammation relief by retinol.

The single nucleotide polymorphism marker may be one or more single nucleotide polymorphism markers selected from the single nucleotide polymorphism markers shown in Table 1 or Table 3. The single nucleotide polymorphism markers shown in Table 1 or Table 3 may determine the degree of correlation with the degree of retinol sensitivity.

The level of retinol sensitivity of the single nucleotide polymorphism markers of the present invention was determined by measuring the frequency of each marker. Such significance is characterized by a p-value, such as, but not limited to, a p-value of less than 0.05, less than 0.01, less than 0.001, less than 0.0001, less than 0.00001, less than 0.000001, less than 0.0000001, less than 0.00000001, or less than 0.000000001. Specifically, the p-value may be less than 0.01, more specifically, the p-value may be less than 0.001, and more specifically, less than 0.0001, but is not limited thereto.

The single nucleotide polymorphism (SNP) marker of the present invention may be any one or more selected from the markers shown in Table 1 or Table 3, but is not limited thereto. The single nucleotide polymorphism (SNP) markers may be one or more, and may be used in combination of a number capable of determining retinol sensitivity, such as two or more, three or more, four or more, but is not limited thereto.

The marker may be a SNP itself, or a polynucleotide composed of 5-100 consecutive DNA sequences including the SNP site, or a polynucleotide composed of a complementary sequence thereof, but is not limited thereto.

For example, the single nucleotide polymorphism marker for diagnosing retinol sensitivity may be one or more single nucleotide polymorphism markers present in a gene encoding one or more proteins selected from the group consisting of COL6A2, EGFR, IL4R, and ADIPOQ, and specifically, rs117668143 , rs1110470, rs6970262, rs2293347, may be one or more selected from the group consisting of r2241766 and rs9882205, but is not limited thereto.

For example, if the SNP ID is rs117668143, Chr.Position (GRCh ver. 37) is described as "21:47551909" and Allele is disclosed as G>A, this is the 47551909th base of human chromosome 21. represents G or A, and the base located on the left of ">" of the allele may mean a major allele, and the base located on the right may indicate a minor allele.

In one embodiment, the marker selected from Table 1 or Table 3 is 5-100 consecutive DNA sequences containing the 47551909th base of human chromosome 21, which is G or A (rs117668143), the 47551909th base. a polynucleotide comprising; A polynucleotide consisting of 5-100 consecutive DNA sequences including base 27336427 of human chromosome 16, wherein base 27336427 is G or A (rs1110470); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 55259763 of human chromosome 7, wherein base 55259763 is G or A (rs6970262); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 55201223 of human chromosome 7, wherein base 55201223 is G or A (rs2293347); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 186570892 of human chromosome 3, wherein base 186570892 is C or A (rs2241766); A polynucleotide consisting of 5-100 consecutive DNA sequences including base 186570398 of human chromosome 3, wherein base 186570398 is A or G (rs9882205); And it may consist of one or more polynucleotides selected from the group consisting of these complementary polynucleotides, but is not limited thereto. The markers described above are only partly described as examples in Table 1 or Table 3, and may be selected in the same manner as described above for chromosomes at other locations.

The retinol sensitivity gene may provide information for selecting a specific irritation reliever for each individual. As a reference example, in the case of an individual having the COL6A2 or EGFR gene, when glucosamine, sucralfate, or trihalose is treated as an irritant reliever, the skin barrier reaction caused by retinol can be alleviated, and in the case of an individual having the IL4R gene In some cases, the inflammatory reaction caused by retinol can be alleviated when ectoin is treated as a stimulus reliever, and in the case of individuals with the ADIPOQ gene, when butylcyclohexanol and omega-9 are treated together as irritation relievers, retinol However, it is possible to provide an optimal combination of stimulation relievers according to the genetic characteristics of each individual.

This suggests that it is possible to select a specific single nucleotide polymorphism (SNP) marker that has a significant correlation with retinol sensitivity and provide a personalized irritation reliever that can help relieve irritation or inflammation caused by retinol based on genetic information. it suggests

The composition of the present invention can be used as a cosmetic composition and can be formulated in various forms. The cosmetic composition according to the present invention is a solution, external ointment, cream, foam, nutrient lotion, softening lotion, pack, softening water, emulsion, makeup base, essence, soap, liquid cleanser, bath additive, sunscreen cream, sun oil, suspension, Emulsion, paste, gel, lotion, powder, soap, surfactant-containing cleansing, oil, powder foundation, emulsion foundation, wax foundation, may be prepared in a formulation selected from the group consisting of patches and sprays, but is limited thereto It is not.

In addition, the cosmetic composition of the present invention may further include one or more cosmetically acceptable carriers formulated in general skin cosmetics, and as typical ingredients, for example, oil, water, surfactants, moisturizers, lower alcohols, A thickener, a chelating agent, a colorant, a preservative, a flavoring agent, and the like may be suitably blended, but are not limited thereto.

Cosmetically acceptable carriers included in the cosmetic composition of the present invention vary depending on the formulation.

When the dosage form of the present invention is an ointment, paste, cream or gel, animal oil, vegetable oil, wax, paraffin, starch, tracanth, cellulose derivative, polyethylene glycol, silicone, bentonite, silica, talc, zinc oxide or Mixtures of these may be used.

When the formulation of the present invention is a powder or spray, lactose, talc, silica, aluminum hydroxide, calcium silicate, polyamide powder or a mixture thereof may be used as a carrier component, and in particular, in the case of a spray, chloro propellants such as fluorohydrocarbons, propane/butane or dimethyl ether.

When the formulation of the present invention is a solution or emulsion, a solvent, solubilizing agent or emulsifying agent is used as a carrier component, such as water, ethanol, isopropanol, ethyl carbonate, ethyl acetate, benzyl alcohol, benzyl benzoate, propylene glycol, 1,3-butyl glycol oil may be used, and in particular, cottonseed oil, peanut oil, corn germ oil, olive oil, castor oil and sesame oil, fatty acid esters of glycerol, polyethylene glycol or sorbitan may be used. there is.

In the case where the formulation of the present invention is a suspension, liquid diluents such as water, ethanol or propylene glycol, ethoxylated isostearyl alcohols, suspending agents such as polyoxyethylene sorbitol esters and polyoxyethylene sorbitan esters, Crystalline cellulose, aluminum metahydroxide, bentonite, agar or tracanth and the like may be used.

When the formulation of the present invention is a soap, alkali metal salts of fatty acids, fatty acid hemiester salts, fatty acid protein hydrolyzates, isethionates, lanolin derivatives, aliphatic alcohols, vegetable oils, glycerol, sugars, etc. may be used as carrier components. can

In another aspect, the composition provides a pharmaceutical composition for preventing or improving irritation or inflammation caused by retinol.

The pharmaceutical composition of the present invention can be used as a single formulation, or can be prepared and used as a combination formulation by further including a drug known to have a stimulation or anti-inflammatory effect. It can be prepared in a form or put into a multi-dose container.

The pharmaceutical composition may be administered in a pharmaceutically effective amount.

The pharmaceutical composition of the present invention can be administered in a pharmaceutically effective amount, and the term "pharmaceutically effective amount" is sufficient to treat or prevent a disease with a reasonable benefit / risk ratio applicable to medical treatment or prevention. It means the amount, and the effective dose level is the severity of the disease, the activity of the drug, the patient's age, weight, health, sex, the patient's sensitivity to the drug, the administration time of the composition of the present invention used, the route of administration and the excretion rate, the treatment period , It may be determined according to factors including drugs used in combination or simultaneous use with the composition of the present invention used, and other factors well known in the medical field. The pharmaceutical composition of the present invention may be administered alone or in combination with a known therapeutic agent for pterygium. It is important to administer the amount that can obtain the maximum effect with the minimum amount without side effects in consideration of all the above factors.

In another aspect, the composition provides a quasi-drug composition for relieving or improving irritation or inflammation caused by retinol.

In the present invention, the term "quasi-drugs" refers to items that are less active than pharmaceuticals among items used for the purpose of diagnosing, treating, improving, mitigating, treating or preventing human or animal diseases. For example, according to the Pharmaceutical Affairs Act of the Republic of Korea Quasi-drugs are products excluding items used for medicinal purposes, and include products used for the treatment or prevention of diseases in humans and animals, products with minor or no direct action on the human body, etc.

In one embodiment, the quasi-drug composition of the present invention may be prepared in a form selected from the group consisting of body cleanser, shampoo, conditioner, foam, soap, mask, ointment, cream, lotion, essence and spray, but is not limited thereto no.

As another aspect, the present invention provides a method comprising: (a) obtaining a biological sample from an individual; (b) amplifying a polymorphic site of one or more single nucleotide polymorphism markers selected from the group consisting of rs117668143, rs1110470, rs6970262, rs2293347, rs2241766 and rs9882205 from the biological sample or hybridizing with a probe; And (c) identifying the base of the amplified or hybridized polymorphic site in step (b), providing information for selecting a customized irritation reliever for irritation relief or inflammation relief by retinol. .

As used herein, the term "subject" refers to a subject for diagnosis of the degree of retinol sensitivity. DNA may be obtained from samples such as hair, urine, blood, various bodily fluids, separated tissues, isolated cells, or saliva, but is not limited thereto.

Among the above methods, determining the base of the polymorphic site in step (b) includes sequencing analysis, microarray hybridization, allele specific PCR, and dynamic allele-specific hybridization. , DASH), PCR extension analysis, SSCP, PCR-RFLP analysis or TaqMan technique, SNPlex platform (Applied Biosystems), mass spectrometry (eg, Sequenom's MassARRAY system), mini-sequencing methods, Bio- Plex systems (BioRad), CEQ and SNPstream systems (Beckman), Molecular Inversion Probe array technologies (eg Affymetrix GeneChip), and BeadArray Technologies (eg Illumina GoldenGate and Infinium assays). . By these methods or other methods available to those skilled in the art, one or more alleles in a polymorphic marker, including microsatellite, SNP or other types of polymorphic markers, can be identified. Determining the base of such a polymorphic site can be performed specifically through an SNP chip.

The method additionally (c) when the base of the amplified or hybridized polymorphic site includes one or more bases that are minor alleles according to the single nucleotide polymorphism marker, it is judged that the sensitivity by retinol is high It may, but is not limited thereto. In addition, (c) when the base of the amplified or hybridized polymorphic site includes one or more bases that are major alleles according to the single nucleotide polymorphism marker, it may be determined that the sensitivity by retinol is low. However, it is not limited thereto.

On the other hand, PCR extension analysis first amplifies a DNA fragment containing the base where the single nucleotide polymorphism is located with a primer pair, and then inactivates it by dephosphorylating all nucleotides added to the reaction, whereby a SNP-specific extension primer, A primer extension reaction is performed by adding a dNTP mixture, dideoxynucleotide, reaction buffer and DNA polymerase. At this time, the extension primer takes the base immediately adjacent to the 5' direction of the base where the SNP is located as the 3' end, and the dNTP mixture excludes nucleic acids having the same base as the dideoxynucleotide, and the dideoxynucleotide represents the SNP. It is selected from one of the base types. For example, when there is a substitution from A to G, when a mixture of dGTP, dCTP and dTTP and ddATP are added to the reaction, the primer at the base where the substitution occurs is extended by DNA polymerase, and after a few bases, A The primer extension reaction is terminated by ddATP at the position where the base first appears. If the substitution does not occur, since the extension reaction is terminated at that position, the base type representing the SNP can be determined by comparing the lengths of the extended primers.

In addition, by confirming the base of the amplified or hybridized polymorphic site in step (c), a personalized irritation reliever for irritation relief or inflammation relief by retinol can be selected.

The irritation reliever may be at least one selected from the group consisting of ectoin, trehalose, sucralfate, glucosamine, 4-t-butylcyclohexanol, and omega-9, but is not limited thereto.

Through the prediction method and system of the present invention, it is possible to provide information on the presence or absence of irritation when applying a substance according to a plurality of prescriptions including retinol.

In addition, it is possible to select a prescription suitable to be prescribed to the user from among a plurality of prescriptions based on the presence or absence of the predicted stimulus, and to provide product information matching the selected prescription.

In addition, it is possible to provide the most effective prescription and product information to individuals according to the information of genetic polymorphism markers observed in individuals, while taking into account the individual's environmental information / lifestyle information / skin characteristic information / age information / gender information It is possible to select and provide the optimal prescription.

In addition, in the process of predicting the presence or absence of stimulation, the accuracy of prediction is high because the result of machine learning is used.

In addition, information on the level of retinol sensitivity of an individual can be provided through the genetic polymorphic markers having association significance with the degree of retinol sensitivity of the present invention, and furthermore, the degree of retinol sensitivity can be determined according to the information of the genetic polymorphic markers observed in the individual. It may be possible to develop a custom ingredient or product that can provide relief.

1 is a schematic block diagram for explaining one aspect of a system for predicting skin irritation of a prescription containing retinol according to the present invention.

FIG. 2 is a schematic block diagram for explaining an aspect of a prediction terminal of the system of FIG. 1 .

FIG. 3 is a schematic block diagram for explaining an aspect of an apparatus for generating a predictive model of the system of FIG. 1 .

4 is a diagram for explaining data transmitted and received between a server of the system of FIG. 1, a prediction terminal, and a data providing server.

5 is a diagram for explaining how information is calculated in a prediction model according to data input to a prediction terminal and the calculated information is output in one aspect of the present invention.

6 is a diagram in which a first threshold stimulus score prediction model is generated by learning in one aspect of the present invention, a threshold stimulus score is determined in the generated prediction model, and stimulus information calculated according to data input to a prediction terminal is output. It is a drawing for explaining what it looks like.

FIG. 7 is a diagram for explaining an aspect different from that of FIG. 6 in which identification data of a prediction target entity is transmitted to a prediction terminal, genetic data corresponding to the identification data is received from a data providing server, and calculation is performed.

8 is a second threshold stimulus score prediction model generated by learning in one aspect of the present invention, a threshold stimulus score determined in the generated prediction model, and stimulus information and prescription information calculated according to data input to a prediction terminal It is a drawing for explaining the appearance of is output.

9 is a diagram in which a third threshold stimulus score prediction model is generated by learning in one aspect of the present invention, a threshold stimulus score is determined in the generated prediction model, and stimulus information calculated according to data input to a prediction terminal is output. It is a drawing for explaining what it looks like.

FIG. 10 is a diagram for explaining an aspect different from that of FIG. 9 in which identification data of a prediction target entity is transmitted to a prediction terminal, genetic data corresponding to the identification data is received from a data providing server, and calculation is performed.

11 shows a fourth threshold stimulus score prediction model generated by learning in one aspect of the present invention, a threshold stimulus score determined in the generated prediction model, and stimulus information and prescription information calculated according to data input to a prediction terminal. It is a drawing for explaining the appearance of is output.

12 is a schematic flowchart for explaining one aspect of a method for predicting skin irritation of a prescription containing retinol.

13 is a schematic flowchart for explaining an aspect of the present invention for selecting SNPs that affect skin irritation when a material containing retinol is applied.

14 to 17 are schematic flowcharts for explaining how stimulation information and/or prescription information are calculated by comparing a stimulation score determined according to genetic data of a prediction subject with a threshold stimulation score determined in each prediction model.

18 shows an eye cream application site on the face.

19 shows the results of evaluation of stimulation scores by time and individual stimulation scores of the irritation reliever of the present invention and the control group.

20 shows the degree of increase and decrease in redness and the degree of increase and decrease in TEWL between the irritation reliever of the present invention and the comparative group.

21 shows changes in stimulation threshold points before and after application of retinol.

22 shows the probability of irritation occurrence between the irritation reliever of the present invention and the control group.

23 shows the correlation between retinol sensitivity-associated significant polymorphic markers and irritation relievers.

24 confirms the suppression of AQP3 overexpression and FLG expression by EGFR.

25 shows the results of treating COL6A2 with glucosamine.

26 is a result confirming the decrease in IL-4 receptor expression in the group treated with glucosamine and/or ectoin, which are stimulation relievers, together with retinol.

27 shows the inhibition of mast cell activity according to the treatment concentration of retinol and/or ectoin.

28 is a result of confirming the degree of activation of TRPV1 by retinol.

29 is a result confirming that the activity of the receptor is reduced as a result of treating the irritation reliever 4-t-butylcyclohexanol and/or omega-9 together with retinol.

Hereinafter, the present invention will be described in more detail through examples. These examples are only for illustrating the present invention, and the scope of the present invention is not to be construed as being limited by these examples.

실시예 1: 레티놀 민감성 평가 및 유전자 채집Example 1: Retinol sensitivity evaluation and gene collection

In order to derive genetic polymorphic markers showing retinol sensitivity and association significance, healthy Korean subjects in their 20s to 50s were recruited. Using the Retinol Stavector (DURAE, Korea) formulation, creams made with three retinol concentrations (2500 IU, 3300 IU, and 5000 IU) were handed out, and instructions were given to use them sequentially from the lowest concentration as follows. ① Use a retinol product about the size of a grain of rice for each area under the eyes or nasolabial folds before going to bed, ② Use the first step for 3 days, then take a break for 4 days, then use the second step if there is no irritation, ③ After using step 2 for 3 days and taking a break for 4 days, use step 3 if there is no stimulation, ④ After all evaluations were completed, a questionnaire was conducted about the time of feeling the stimulation.

If irritation is felt during step-by-step use within the evaluation period, use was stopped immediately.

During the evaluation period, subjects were asked to use their usual sunscreen (which did not cause irritation).

The backbone composition of the cream used in the evaluation was based on the prescription used in the "Ohui Age Recovery Cream" product researched and developed by the company, and a small amount of base material was added for quality and formulation stability, and the prescription was found to be non-irritating to the skin. It is made of known materials. In addition, non-irritation was verified in a patch test conducted by an external company (48-hour skin patch attachment, stimulation reading through Frosch & Kligman stimulation measurement evaluation method) (Ekoderm Co., Ltd.). The test volunteers were 32 healthy adult volunteers (11 males and 21 females) who met the criteria for selection and exclusion of subjects through medical history, medical examination, examination, and, if necessary, facilitation by the researcher under the guidance of a dermatologist specialist. done.

Retinol Stavector added to the cream is composed of Water (and) Cellulose acetate butyrate, Lactic acid/Glycolic acid copolymer ¹ , and Polyglyceryl-10 Diisostearate ² , and is a polymer composite for the purpose of stabilizing active ingredients. The above components are known to have no or mild skin irritation, and have been included in a number of cosmetic compositions. Its safety has also been reported in the literature.

Subjects were notified of the ingredients of the formulation prior to the start of the experiment, and those who had allergies or experienced irritation to the ingredients were excluded from the evaluation.

Retinol sensitivity was determined by those who responded that the 'first stimulation time' was within 2 weeks and within 3 days of each stage of use in a stimulation survey conducted after using retinol cream. This is a phenotype in which the person who responded “After” was regarded as a control.

Among the above subjects, ① those who are pregnant, lactating, or planning to become pregnant within 6 months, ② those who have used external skin preparations containing steroids for more than 1 month for the treatment of skin diseases, ③ who have not passed 6 months since participating in the same study ④ If there are skin abnormalities such as moles, acne, erythema, telangiectasia, etc. at the test site, ⑤ If the same or similar cosmetics or drugs were used on the test site within 3 months of the start of the test, ⑥ Treatment on the test site ( Skin peeling, Botox, other skin care) or planned within 6 months, ⑦ Chronic wasting disease (asthma, diabetes, high blood pressure, etc.), ⑧ Atopic dermatitis, ⑨ Other tests at the discretion of the main tester Cases judged to be difficult were excluded from the subjects.

실시예 2: 유전자형 분석Example 2: Genotyping

For gene extraction from saliva for genetic analysis, human genomic DNA was extracted using the QIAamp mini prep kit (QIAGEN), and the quality was absorbance (OD 260/280) or 1.7, concentration 50ng/ul, 1x TAE 1% agarose It was confirmed through a band test through gel, and genetic analysis was performed only for cases that passed the quality.

Gene analysis was performed using Illumina's microarray genotyping chip, and specifically, the genes of the subjects were analyzed using the global screening array product of the same company.

Illumina's microarray genotyping chip gene analysis experiment was conducted according to the provided manual, and genomic DNA amplification, DNA fragmentation, precipitation, hybridization, and staining were performed using the provided reagents. , washing, coating, and scanning were performed.

The microarray genotyping chip where the experiment was completed was scanned using iScan Control Software (Illumina), and when the scan was completed, an idat file was automatically created and data quality control (sample call rate 98%, marker call) was performed using GenomeStudio (Illumina) program. rate 98%) and genetic information were confirmed.

In this experiment, only data that passed data quality control after genetic analysis were used.

실시예 3: 레티놀 민감성 연관유의성 유전자 다형성 마커 도출Example 3: Derivation of Retinol Sensitivity Linked Significant Genetic Polymorphism Markers

In order to derive genetic polymorphic markers with retinol sensitivity and association significance, linear regression analysis was performed using the genetic polymorphic markers of the analyzed subjects, and PLINK v 1.90 and SNP & Variation suite (Golden Helix, Inc., Bozeman, Montana) were used for analysis. , USA) program was used.

For quality control of the polymorphic markers to be analyzed, each polymorphic marker was used only if it exceeded the minor allele frequency or 0.01 and the Hardy-Weinberg equilibrium or 0.000001 standard.

The significance of genetic polymorphism markers associated with retinol sensitivity was evaluated through linear regression analysis F-statistics, and the criterion was set as P-value < 0.1. As a result, 56 polymorphic markers associated with retinol sensitivity were identified (Table 1).

Retinol Sensitivity Associated Genetic Polymorphism Markers (P < 0.1)

	SNP¹⁾ SNP ¹⁾	Gene¹⁾ Gene ¹⁾	Chr:Position¹⁾ Chr:Position ¹⁾	Allele²⁾ Allele ²⁾	MAF³⁾ MAF ³⁾	P-value⁴⁾ P-value ⁴⁾	Effect size (Odds ratio)⁵⁾ Effect size (Odds ratio) ⁵⁾
1One	rs117668143rs117668143	COL6A2COL6A2	21:4755190921:47551909	G>AG>A	0.04900.0490	0.002021405 0.002021405	12.789512.7895
22	rs3024530rs3024530	IL4RIL4R	16:2735068716:27350687	G>AG>A	0.41670.4167	0.002794311 0.002794311	2.33522.3352
33	rs1110470rs1110470	IL4RIL4R	16:2733642716:27336427	G>AG>A	0.27450.2745	0.003886849 0.003886849	2.31902.3190
44	rs2293348rs2293348	EGFREGFR	7:552667577:55266757	G>AG>A	0.08330.0833	0.007286955 0.007286955	0.19970.1997
55	rs8098848rs8098848	BCL2BCL2	18:6085779318:60857793	A>GA>G	0.44610.4461	0.008647738 0.008647738	0.45280.4528
66	rs3773439rs3773439	RARBRARB	3:256177753:25617775	A>GA>G	0.38240.3824	0.008873391 0.008873391	0.45530.4553
77	rs1286733rs1286733	RARBRARB	3:256133723:25613372	A>GA>G	0.28920.2892	0.010692819 0.010692819	0.44000.4400
88	rs59964722rs59964722	RARBRARB	3:249505183:24950518	A>GA>G	0.10780.1078	0.010859114 0.010859114	0.26610.2661
99	rs5744247rs5744247	IL18IL18	11:11202615611:112026156	G>CG>C	0.34800.3480	0.013555862 0.013555862	0.48820.4882
1010	rs2740762rs2740762	EGFREGFR	7:552613427:55261342	C>AC>A	0.06370.0637	0.015239039 0.015239039	4.68474.6847
1111	rs10510553rs10510553	RARBRARB	3:249667683:24966768	A>GA>G	0.22060.2206	0.015936993 0.015936993	2.26572.2657
1212	rs6804842rs6804842	RARBRARB	3:251064373:25106437	G>AG>A	0.30390.3039	0.017974267 0.017974267	2.15492.1549
1313	rs1604003rs1604003	RARBRARB	3:250686173:25068617	C>AC>A	0.12250.1225	0.021263964 0.021263964	0.35880.3588
1414	rs6550923rs6550923	RARBRARB	3:249244953:24924495	A>GA>G	0.36760.3676	0.026671030 0.026671030	0.51530.5153
1515	rs17099562rs17099562	MMP10MMP10	11:10264852711:102648527	G>AG>A	0.17650.1765	0.029043007 0.029043007	0.41600.4160
1616	rs73151296rs73151296	RARBRARB	3:253058133:25305813	A>GA>G	0.05880.0588	0.030197036 0.030197036	4.10534.1053
1717	rs4280597rs4280597	RARBRARB	3:250534823:25053482	A>GA>G	0.25490.2549	0.031500608 0.031500608	0.50550.5055
1818	rs1021701rs1021701	RARBRARB	3:250587573:25058757	A>GA>G	0.25490.2549	0.031500608 0.031500608	0.50550.5055
1919	rs6970262rs6970262	EGFREGFR	7:552597637:55259763	G>AG>A	0.10290.1029	0.033027227 0.033027227	2.90912.9091
2020	rs3117040rs3117040	RXRBRXRB	6:331647356:33164735	A>CA>C	0.03920.0392	0.034364163 0.034364163	0.14910.1491
2121	rs12454712rs12454712	BCL2BCL2	18:6084588418:60845884	A>GA>G	0.48040.4804	0.036234712 0.036234712	0.58010.5801
2222	rs321526rs321526	RARBRARB	3:252401883:25240188	C>AC>A	0.24510.2451	0.037815057 0.037815057	2.08242.0824
2323	rs73042351rs73042351	RARBRARB	3:252605683:25260568	A>GA>G	0.04410.0441	0.041955183 0.041955183	4.63754.6375
2424	rs1129055rs1129055	CD86CD86	3:1218383193:121838319	A>GA>G	0.37250.3725	0.045192702 0.045192702	1.78901.7890
2525	rs17841945rs17841945	BCL2BCL2	18:6088155518:60881555	G>AG>A	0.07840.0784	0.046397760 0.046397760	3.05563.0556
2626	rs996076rs996076	CD44CD44	11:3521079811:35210798	A>GA>G	0.12250.1225	0.048009912 0.048009912	2.43002.4300
2727	rs187238rs187238	IL18IL18	11:11203498811:112034988	C>GC>G	0.12250.1225	0.048009912 0.048009912	2.43002.4300
2828	rs10128586rs10128586	CD44CD44	11:3524590711:35245907	A>GA>G	0.22060.2206	0.049028270 0.049028270	0.50080.5008
2929	rs2295756rs2295756	CD44CD44	11:3524122911:35241229	G>AG>A	0.35290.3529	0.049913243 0.049913243	1.76801.7680
3030	rs322707rs322707	RARBRARB	3:253192603:25319260	A>GA>G	0.47060.4706	0.050717125 0.050717125	0.53680.5368
3131	rs7621283rs7621283	RARBRARB	3:250711073:25071107	A>GA>G	0.11270.1127	0.051193136 0.051193136	0.41800.4180
3232	rs640198rs640198	MMP13MMP13	11:10282509111:102825091	C>AC>A	0.44610.4461	0.052008514 0.052008514	1.71631.7163
3333	rs12054035rs12054035	RARBRARB	3:252692213:25269221	G>AG>A	0.08820.0882	0.052651336 0.052651336	2.80002.8000
3434	rs79807077rs79807077	RARBRARB	3:253116473:25311647	G>AG>A	0.05450.0545	0.053064612 0.053064612	3.64913.6491
3535	rs2282692rs2282692	CCL1CCL1	17:3268818317:32688183	A>CA>C	0.37750.3775	0.054884626 0.054884626	1.77171.7717
3636	rs6769702rs6769702	RARBRARB	3:249439953:24943995	A>GA>G	0.30390.3039	0.057040888 0.057040888	1.76691.7669
3737	rs9853652rs9853652	RARBRARB	3:253137093:25313709	G>AG>A	0.05390.0539	0.057999068 0.057999068	3.55563.5556
3838	rs1056837.1rs1056837.1	CYP1B1CYP1B1	2:382981502:38298150	G>AG>A	0.14710.1471	0.058129603 0.058129603	0.46300.4630
3939	rs1056836rs1056836	CYP1B1CYP1B1	2:382982032:38298203	G>CG>C	0.14710.1471	0.058129603 0.058129603	0.46300.4630
4040	rs6767543rs6767543	RARBRARB	3:255504233:25550423	A>GA>G	0.49510.4951	0.059296533 0.059296533	0.57650.5765
4141	rs4431992rs4431992	MMP10MMP10	11:10264539911:102645399	A>GA>G	0.43140.4314	0.060605946 0.060605946	1.73701.7370
4242	rs1580813rs1580813	RARBRARB	3:250615953:25061595	A>GA>G	0.24510.2451	0.062733334 0.062733334	0.55660.5566
4343	rs79768440rs79768440	RARBRARB	3:249850433:24985043	A>GA>G	0.17330.1733	0.066581940 0.066581940	1.96281.9628
4444	rs77767607rs77767607	ATF2ATF2	2:1759993962:175999396	C>AC>A	0.04900.0490	0.070545462 0.070545462	0.26110.2611
4545	rs4568101rs4568101	RARBRARB	3:249518583:24951858	A>CA>C	0.42160.4216	0.073593937 0.073593937	1.66061.6606
4646	rs45475696rs45475696	HAS1HAS1	19:5221615419:52216154	A>CA>C	0.18140.1814	0.075716602 0.075716602	0.52660.5266
4747	rs77728527rs77728527	RARBRARB	3:253642493:25364249	A>GA>G	0.03960.0396	0.077664104 0.077664104	3.97503.9750
4848	rs1153589rs1153589	RARBRARB	3:255543633:25554363	G>AG>A	0.50000.5000	0.080677724 0.080677724	1.67221.6722
4949	rs73149390rs73149390	RARBRARB	3:255817673:25581767	G>AG>A	0.07350.0735	0.082206956 0.082206956	2.70272.7027
5050	rs1865614rs1865614	RARBRARB	3:255825683:25582568	A>GA>G	0.07350.0735	0.082206956 0.082206956	2.70272.7027
5151	rs4681027rs4681027	RARBRARB	3:255843583:25584358	A>CA>C	0.07350.0735	0.082206956 0.082206956	2.70272.7027
5252	rs188922rs188922	RARBRARB	3:253320283:25332028	G>AG>A	0.03920.0392	0.083212998 0.083212998	3.87803.8780
5353	rs322695rs322695	RARBRARB	3:253495383:25349538	G>AG>A	0.03920.0392	0.083212998 0.083212998	3.87803.8780
5454	rs2681420rs2681420	CD86CD86	3:1218340573:121834057	G>AG>A	0.37130.3713	0.087063956 0.087063956	1.65791.6579
5555	rs1021702rs1021702	RARBRARB	3:250592273:25059227	A>GA>G	0.36270.3627	0.094102996 0.094102996	1.61381.6138
5656	rs4858694rs4858694	RARBRARB	3:250977363:25097736	G>AG>A	0.23530.2353	0.098931461 0.098931461	1.75491.7549

1) National Institutes of Health (NIH) ID, sequence check available on the website

2) (major allele) > (minor allele) meaning

3) minor allele frequency = (2mm + Mm)/2(MM + Mm + mm)

4) Statistical significance of phenotypic differences for three genotypes (M/M, M/m, m/m) (M: major allele, m: minor allele)

5) A number that indicates how many times the risk of having a case (possessing retinol sensitivity) is higher when you have a minor allele than when you do not have a minor allele

Retinol Sensitivity = In the stimulation survey conducted after using retinol cream, the case was a person who responded that the 'time of initial stimulation' was within 2 weeks and within 3 days of each stage of use, and did not feel any stimulation or the 'time of first stimulation' was 3 days after the 3rd week. The phenotype of the person who responded as a control

실시예 4: 레티놀 민감성 연관유의성 유전자 다형성 마커 발굴 및 예측 모델 수립Example 4: Retinol Sensitivity Linked Significance Genetic Polymorphism Marker Discovery and Prediction Model Establishment

Using the 'retinol sensitivity' phenotype and the retained genotype data, a genetic polymorphism marker showing association significance is derived, and a candidate gene is selected through a literature review related to skin sensitivity and retinol for candidate gene analysis, and a candidate gene is selected within the gene. The analyzed markers were located.

As a result of the analysis, a polygenic risk score (stimulus score) representing the risk of retinol sensitivity was obtained by linearly combining some of the markers that were significantly (P-value < 0.1) and the odds ratio of the markers as shown in the following formula. An equation was defined (stimulus score model).

Assuming that the stimulus score S is calculated using the combination of m SNPs, X (first value) represents the genotype for each SNP as the number of minor alleles (X = 0, 1, 2), and β (Second value) represents the effect size (odds ratio) of each SNP.

실시예 5: 레티놀 민감성 마커를 이용한 진단 모델 및 유효성 검증(1)Example 5: Diagnostic model and validation using retinol sensitive marker (1)

When establishing a stimulation score model using some of the markers of retinol sensitivity and association significance derived in Examples 3 and 4, the effect of the number of markers used on the performance of the predictive model was verified.

Specifically, after dividing all subjects by a ratio of 2:1 (training set: test set), logistic regression is used in the training set to derive a regression model (threshold stimulation score) that predicts the retinol sensitivity phenotype from the genotype combination of each marker. did The critical stimulation score determined as a result of learning was applied to the test set to confirm accuracy*, sensitivity**, and specificity*** for retinol sensitivity prediction.

* Accuracy: The ratio of predicting the presence or absence of stimulation by comparing the determined threshold stimulation score and the calculated stimulation score, and correctly judging a subject with retinol sensitivity as being sensitive and a subject without retinol sensitivity as not being sensitive

** Sensitivity: Proportion of subjects who are actually sensitive to retinol that are correctly predicted to have irritation

*** Specificity: Proportion of correctly judged non-irritant among subjects who are not actually retinol sensitive

The above process started with a stimulation score model established using a small number of randomly selected markers, and was repeatedly performed while gradually increasing the number of markers by adding random markers, and the results are shown in Table 2 below.

마커 수number of markers	마커 조합marker combinations	정확도accuracy	민감도responsiveness	특이도specificity
1One	rs4681027rs4681027	0.41180.4118	0.19050.1905	0.76920.7692
22	rs4681027, rs6804842rs4681027, rs6804842	0.47060.4706	0.28570.2857	0.76920.7692
55	rs4681027, rs6804842, rs77728527, rs1056836, rs187238rs4681027, rs6804842, rs77728527, rs1056836, rs187238	0.48480.4848	0.30000.3000	0.76920.7692
1010	rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470	0.60610.6061	0.45000.4500	0.84620.8462
1515	rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945	0.63640.6364	0.50000.5000	0.84620.8462
3030	rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945, rs1129055, rs4280597, rs1865614, rs4431992, rs1604003, rs1021702, rs3024530, rs73151296, rs2282692, rs79807077, rs12054035, rs117668143, rs9853652, rs6769702, rs77767607rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945, rs1129055, rs4280597, rs1865614, rs4431992, rs1604003, rs1021702, rs3024530, rs73151296, rs2282692, rs7 9807077, rs12054035, rs117668143, rs9853652, rs6769702, rs77767607	0.68750.6875	0.57890.5789	0.84620.8462
5050	rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945, rs1129055, rs4280597, rs1865614, rs4431992, rs1604003, rs1021702, rs3024530, rs73151296, rs2282692, rs79807077, rs12054035, rs117668143, rs9853652, rs6769702, rs77767607, rs322707, rs1021701, rs2295756, rs6970262, rs6550923, rs73149390, rs1056837.1, rs996076, rs4568101, rs7621283, rs2681420, rs6767543, rs3117040, rs4858694, rs1286733, rs79768440, rs45475696, rs10128586, rs188922, rs10510553rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945, rs1129055, rs4280597, rs1865614, rs4431992, rs1604003, rs1021702, rs3024530, rs73151296, rs2282692, rs7 9807077, rs12054035, rs117668143, rs9853652, rs6769702, rs77767607, rs322707, rs1021701, rs2295756, rs6970262, rs6550923, rs73149390, rs105683 7.1, rs996076, rs4568101, rs7621283, rs2681420, rs6767543, rs3117040, rs4858694, rs1286733, rs79768440, rs45475696, rs10128586, rs18892 2, rs10510553	0.71880.7188	0.57890.5789	0.92310.9231
5555	rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945, rs1129055, rs4280597, rs1865614, rs4431992, rs1604003, rs1021702, rs3024530, rs73151296, rs2282692, rs79807077, rs12054035, rs117668143, rs9853652, rs6769702, rs77767607, rs322707, rs1021701, rs2295756, rs6970262, rs6550923, rs73149390, rs1056837.1, rs996076, rs4568101, rs7621283, rs2681420, rs6767543, rs3117040, rs4858694, rs1286733, rs79768440, rs45475696, rs10128586, rs188922, rs10510553, rs12454712, rs73042351, rs321526, rs640198, rs3773439rs4681027, rs6804842, rs77728527, rs1056836, rs187238, rs2293348, rs1580813, rs2740762, rs5744247, rs1110470, rs59964722, rs1153589, rs8098848, rs322695, rs17841945, rs1129055, rs4280597, rs1865614, rs4431992, rs1604003, rs1021702, rs3024530, rs73151296, rs2282692, rs7 9807077, rs12054035, rs117668143, rs9853652, rs6769702, rs77767607, rs322707, rs1021701, rs2295756, rs6970262, rs6550923, rs73149390, rs105683 7.1, rs996076, rs4568101, rs7621283, rs2681420, rs6767543, rs3117040, rs4858694, rs1286733, rs79768440, rs45475696, rs10128586, rs18892 2, rs10510553, rs12454712, rs73042351, rs321526, rs640198, rs3773439	0.71880.7188	0.63160.6316	0.84620.8462

As shown in Table 2, it was confirmed that a pattern of increasing accuracy, sensitivity, and specificity appeared as the number of markers used in the stimulation score model increased. This suggests that establishing a stimulation score model using multiple markers of association significance can help increase the accuracy of retinol stimulation prediction.

In addition, it was confirmed through logistic regression that retinol sensitivity could be predicted based on a plurality of marker information. Based on the above data, it can be seen that retinol sensitivity can be predicted using various decision-making techniques such as random forest, lasso, ridge, elastic net, MDR, and SVM.

실시예 6: 레티놀 민감성 연관유의성 유전자 다형성 마커의 대표예Example 6: Representative examples of retinol-sensitive genetic polymorphism markers with significant linkage

Representative examples of SNP markers significantly associated with retinol sensitivity are shown in Table 3 below.

Retinol Sensitivity Associated Genetic Polymorphism Markers

	SNP¹⁾ SNP ¹⁾	Gene¹⁾ Gene ¹⁾	Chr:Position¹⁾ Chr:Position ¹⁾	Allele²⁾ Allele ²⁾	MAF³⁾ MAF ³⁾	P-value⁴⁾ P-value ⁴⁾	Effect size (Odds ratio)⁵⁾ Effect size (Odds ratio) ⁵⁾
1One	rs117668143rs117668143	COL6A2COL6A2	21:4755190921:47551909	G>AG>A	0.04900.0490	0.002021405 0.002021405	12.789512.7895
22	rs1110470rs1110470	IL4RIL4R	16:2733642716:27336427	G>AG>A	0.27450.2745	0.003886849 0.003886849	2.31902.3190
33	rs6970262rs6970262	EGFREGFR	7:552597637:55259763	G>AG>A	0.10290.1029	0.033027227 0.033027227	2.90912.9091
44	rs2293347rs2293347	EGFREGFR	7:552012237:55201223	G>AG>A	0.34310.3431	0.1685600304932580.168560030493258	1.494123750252351.49412375025235
55	rs2241766rs2241766	ADIPOQADIPOQ	3:1865708923:186570892	C>AC>A	0.29250.2925	0.0622598751392124 0.0622598751392124	1.861371.86137
66	rs9882205rs9882205	ADIPOQADIPOQ	3:1865703983:186570398	A>GA>G	0.40820.4082	0.8666232922722670.866623292272267	1.043918283459791.04391828345979

2) (major allele) > (minor allele) meaning

3) minor allele frequency = (2mm + Mm)/2(MM + Mm + mm)

실시예 7: 레티놀 민감성 연관 유의성 다형성 마커와 자극 완화제의 처리의 상관관계 확인 Example 7: Confirmation of correlation between retinol sensitivity-associated significant polymorphic markers and treatment of irritation relievers

Based on the retinol sensitivity-related significant polymorphic marker obtained through Example 6, a substance capable of alleviating irritation or inflammation caused by retinol was discovered and a customized irritation reliever was intended to be prescribed.

7-1: 다양한 자극 완화제의 처리7-1: Treatment of various irritation relievers

It was attempted to find out whether stimulation of retinol could be effectively alleviated by treatment with a stimulation reliever that controls (suppresses or enhances) the action of retinol on the gene and related mechanisms.

Specifically, ectoine 2%, trehalose 2%, sucralfate 2%, glucosamine 2%, 4-t-butylcyclohexanol (4-t- Butylcyclohexanol 1% or omega-9 (omega-9)) 1% was used, and dexpanthenol 2% (J Dermatolog Treat. 2002, Proksch) and alanyl glutamine (LG -AQ)) 2%, beta-Glucan 0.04% (Toxicol Lett, 2003, Kim) was used.

Retinol stimulation was evaluated in a total of two experiments with the following subjects.

i) Small-scale human evaluation: small-pilot study for 7 adults, subjective & objective index analysis

ii) Large-scale human evaluation: 91 adults, more than 190 adults

7-2: 소규모 인체 평가7-2: Small human evaluation

The small-scale human evaluation was conducted on 7 adults and was conducted in a single blind, half-face method. Specifically, as shown in FIG. 18, a control group, a cream containing retinol (5,000 IU), and a cream containing an irritation reliever and retinol (5,000 IU) were applied to the left and right sides of the eye cream application area of the face, respectively. The cream was used for 3 days, and self-questions and objective indicators were evaluated for 7 days. The evaluation items were 1) self-questionnaire and stimulation score based on it, 2) redness (color difference meter), 3) TEWL (tewameter), and 4) stimulation threshold (algometer) measurement values. The irritation indicates all of keratin, itching and pruritus, burning sensation, dryness, pain or irritation, and the like.

As a result, it was confirmed that the area to which the cream containing the irritation reliever and retinol of the present invention was applied significantly reduced irritation compared to the area to which the control group and the cream containing retinol were applied.

Specifically, as a result of evaluating the stimulation score by time and the stimulation score by individual based on the self-questionnaire, it was confirmed that stimulation was reduced by 58.3% or more compared to the control group (FIG. 19).

In addition, it was confirmed that redness decreased by 67.3% and the increase in TEWL decreased by 20% compared to the control group (FIG. 20). confirmed (FIG. 21). As the threshold value of the stimulus is negative, it indicates that the threshold point decreases, which indicates that the stimulus is more sensitive.

7-3: 대규모 인체 평가7-3: Large-scale human evaluation

A large-scale human evaluation calculated the probability (%) of occurrence of retinol stimulation in two independent experimental groups as follows.

i) 190 people or more, retinol 3,300 IU + control cream

ii) 91 subjects, retinol 3,300 IU + irritation reliever cream

The cream was used for 3 days and was evaluated based on self-questions for 7 days.

As a result, it was confirmed that the group applied with the cream containing the irritation reliever of the present invention and retinol had a 65.8% reduction in the probability of occurrence of irritation compared to the control group and the group applied with the cream containing retinol (FIG. 22).

실시예 8: 레티놀 민감성 연관 유의성 다형성 마커를 기반으로 한 자극 완화제의 처리 효과Example 8: Treatment effect of irritation relievers based on retinol sensitivity-associated significant polymorphic markers

The correlation between the retinol sensitivity-related significant polymorphic marker obtained in Example 6 and the treatment of the irritation reliever of the present invention was confirmed through an in-vitro experiment.

8-1: 레티놀 민감성 연관 유의성 다형성 마커와 자극 완화제의 상관관계 8-1: Correlation between retinol sensitivity-associated significant polymorphic markers and irritation relievers

For the genes in Table 3, it was confirmed that the probability of irritation significantly decreased when the irritation reliever of the present invention was prescribed compared to the control group (FIG. 23).

For example, in the case of rs110470 (G>A) among the genes in Table 3, when the allele is AG or GG, the irritation occurrence probability was significantly reduced when the irritation reliever of the present invention was prescribed compared to the control group prescription. From this, it can be seen that in the case of carrying the corresponding allele, it is effective to reduce retinol stimulation using the irritation reliever of the present invention.

In addition to the above genes, it was confirmed that rs11768143, rs2241766, rs9882205, rs2293347 or rs6970262 showed similar results. This suggests that the stimulation reliever of the present invention can be customized for individuals having genes closely related to stimulation.

참조예 1: 유전자(COL6A2, EGFR)분석 데이터 기반에 따른 자극 완화제의 자극 관련 유전자 발현 효과 확인Reference Example 1: Confirmation of stimulation-related gene expression effects of stimulation relievers based on gene (COL6A2, EGFR) analysis data

This study aimed to confirm stimulation-related gene expression effects in subjects with one or more minor alleles of the COL6A2 and EGFR genes.

When the COL6A2 and EGFR genes have a risk allele (minor allele), the basement membrane is weakened and the skin barrier is weakened (Lynn Williams, et al., The FEBS Journal, 2021 ; Cristina Wolf et al., Scientific Reports 6 (39780) , 2016), it was confirmed that AQP3 expression increased and FLG expression decreased, and structural abnormalities of skin tissue and barrier were induced when retinol treatment. In addition, it was confirmed whether stimulation of the gene by retinol had a mitigating effect according to the treatment of the stimulation reliever of the present invention.

Specifically, after treating fibroblasts with retinol and a candidate stimulant for 24 hr, the expression level of mRNA was analyzed.

As a result, it was confirmed that the side effects (overexpression of AQP3 by EGFR) induced during retinol treatment were suppressed by 11% by trehalose (100ppm) among various irritation relievers of the present invention, and skin barrier destruction (inhibition of FLG expression) by retinol was reduced by glucosamine It was confirmed that it was reduced by sucralfate and (FIG. 24).

In addition, when treated with glucosamine (100 ppm), it was confirmed that COL6A2 was overexpressed 1.5-fold or 1.7-fold compared to the untreated group (FIG. 25).

참조예 2: 유전자(IL4R)분석 데이터 기반에 따른 자극 완화제의 자극 관련 유전자 발현 효과 확인Reference Example 2: Confirmation of stimulation-related gene expression effects of stimulation relievers based on gene (IL4R) analysis data

The purpose of this study was to confirm the stimulation-related gene expression effect of anti-stimulants in subjects with one or more minor alleles of the IL4R gene.

Retinol treatment increases IL-4R expression in mast cells, increases mast cell degranulation, increases histamine secretion, and mediates inflammatory responses by retinol (Andrea Chiricozzi et al., Immunotargets Ther. 29; 9: 151-156, 2020; Yosuke Kurashima et al., Immunity 40(4), 2014), it was confirmed whether stimulation of the IL4R gene with retinol had an alleviating effect according to treatment with the stimulation reliever of the present invention.

Specifically, IL-4R expression and degree of degranulation were measured when retinol and a stimulant were treated together in mast cells.

As a result, it was confirmed that the IL-4 receptor overexpression of mast cells by retinol increased by about 1.7 times. However, it was confirmed that the expression of the IL-4 receptor decreased in the group treated with glucosamine or ectoin, which are stimulation relievers, together with retinol (FIG. 26).

In addition, as a result of treatment with various concentrations of retinol and/or ectoin in relation to the release of β-hexosaminidase, which is an indicator of mast cell degranulation, mast cell activation was most effective when ectoin 100ppm was treated in the retinol 200ppm treatment group. It was confirmed that it can suppress (FIG. 27).

참조예 3: 유전자(ADIPOQ)분석 데이터 기반에 따른 자극 완화제의 자극 관련 유전자 발현 효과 확인Reference Example 3: Confirmation of stimulation-related gene expression effect of irritation reliever based on gene (ADIPOQ) analysis data

The purpose of this study was to confirm the stimulation-related gene expression effect of anti-stimulants in subjects with one or more minor alleles of the ADIPOQ gene.

When retinol is treated, a neurogenic inflammatory response is mediated due to an increase in TRPV1 activity, which in turn induces an acute/chronic inflammatory response (Shijin Yin et al., J Clin Invest. 123(9):3941-51, 2013; Eun Ju Kim et al., J Invest Dermatol.

Specifically, after treating the TRPV1 overexpressing cell line with retinol and a stimulant, the generation of flux during TRPV1 activation and Ca2+, which is an activity index, were confirmed. The irritation relievers were treated in the combinations and concentrations shown in Table 4 below.

조합 Combination	상세 Detail

Combination 1Combination 1	4-t-Butylcyclohexanol 25uM+Omega-9 5uM4-t-Butylcyclohexanol 25uM+Omega-9 5uM

Combination 2Combination 2	4-t-Butylcyclohexanol 50uM+Omega-9 10uM4-t-Butylcyclohexanol 50uM+Omega-9 10uM

Combination 3Combination 3	4-t-Butylcyclohexanol 100uM+Omega-9 20uM4-t-Butylcyclohexanol 100uM+Omega-9 20uM

As a result, it was confirmed that TRPV1 was activated by retinol, and it was confirmed that the activation of TRPV1 by retinol was significantly lowered in the group treated with butylcyclohexanol and omega-9 as irritation relievers (FIG. 28).

In addition, in order to qualitatively confirm this, Ca2+ influx generated during TRPV1 activation was observed using a fluorescence microscope. To this end, cells were previously treated with Fluo-4, a detection molecule that generates fluorescence when combined with Ca2+ in cells, and then treated with retinol and irritation reliever components. In the group treated with the condition corresponding to Combination 2, it was confirmed that Ca2+ influx strongly generated by retinol was inhibited (FIG. 29).

From the above description, those skilled in the art to which the present invention pertains will be able to understand that the present invention may be embodied in other specific forms without changing its technical spirit or essential features. In this regard, the embodiments described above should be understood as illustrative in all respects and not limiting. The scope of the present invention should be construed as including all changes or modifications derived from the meaning and scope of the claims to be described later and equivalent concepts rather than the detailed description above are included in the scope of the present invention.

Claims

(a) inputting SNP information of a prediction target entity into a prediction terminal; and

(b) calculating, by the prediction terminal, stimulus information according to a comparison result between a predetermined threshold stimulus score and a stimulus score calculated according to input SNP information, and outputting the calculated stimulus information;

The threshold stimulus score is determined by a first threshold stimulus score prediction model;

The first threshold stimulus score prediction model,

The learning processor consists of pairs of stimulation data including (i) a stimulation score predetermined according to the SNP information and (ii) the presence or absence of stimulation or the level of stimulation when a substance containing retinol is applied to an individual having the SNP information. A model for learning a set of first threshold stimulus learning data to determine a threshold stimulus score that causes skin irritation when a substance containing retinol is applied,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 1,

The SNPs marker selection device selects one or more SNPs related to skin irritation when retinol is applied from among the plurality of SNPs included in the SNP information; further comprising,

Stimulus scores calculated according to the input SNP information are calculated using at least some of the one or more SNPs selected by the SNPs marker selection device,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 2,

One or more SNPs associated with the skin irritation are any one or more selected from Table 1,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 2,

The stimulus score is

It can be calculated by summing the allocation scores of each of the one or more SNPs,

The assigned score is,

A first value determined according to the number of major alleles and minor alleles included in each SNP; and

A second value, which is the degree to which each SNP affects skin irritation, which is calculated using

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 4,

The first value is,

Major allele - major allele, major allele - minor allele and minor allele - different values are given for each SNPs type of the minor allele,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 5,

The first value has a higher value as the number of lower alleles increases among the SNPs types.

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 4,

The allocation score is calculated by multiplying the first value and the second value,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 1,

Different threshold stimulation scores are determined according to the type of substance added to the retinol,

The threshold stimulus score is determined by a second threshold stimulus score prediction model;

The second threshold stimulus score prediction model,

The learning processor determines (i) a stimulation score predetermined according to the SNP information, (ii) one or more prescription information among a plurality of prescriptions including a retinol prescription and a prescription in which an additional substance is further included in retinol, and (iii) the SNP information By learning a set of second threshold stimulation learning data consisting of pairs of stimulation data including the presence or absence of stimulation or the degree of stimulation when a substance according to each prescription is applied to an object having A model for determining the threshold stimulus score that triggers the stimulus,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 1,

The threshold stimulus score is determined by a third threshold stimulus score prediction model;

The third threshold stimulus score prediction model,

The learning processor comprises (i) a stimulation score predetermined according to SNP information, (ii) one or more information of age information, gender information, lifestyle information, environmental information, and skin characteristic information, and (iii) having the SNP information By learning a set of third threshold stimulus learning data consisting of pairs of stimulus data including the presence or absence of irritation or the degree of irritation when a substance containing retinol is applied to an object, skin irritation is reduced when a substance according to each prescription is applied. A model for determining each triggering threshold stimulus score,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 1,

Different threshold stimulation scores are determined according to the type of substance added to the retinol,

The threshold stimulus score is determined by a fourth threshold stimulus score prediction model;

The fourth threshold stimulus score prediction model,

(i) a stimulus score determined in advance according to SNP information, (ii) one or more prescription information among a plurality of prescriptions including a retinol prescription and a prescription in which an additional substance is further included in retinol, (iii) age information, One or more of gender information, lifestyle information, environmental information, and skin characteristic information, and (iv) stimulation data including the presence or absence of stimulation or the degree of stimulation when a substance according to each prescription is applied to an individual having the SNP information A model for learning a set of paired fourth threshold stimulation learning data to determine a threshold stimulation score that causes skin irritation when a substance according to each prescription is applied,

A method for predicting skin irritation information of prescriptions containing retinol.
According to claim 8 or 10,

Selecting and outputting, by the prediction terminal, one or more prescriptions among the plurality of prescriptions using a comparison result of a predetermined threshold stimulation score for each prescription and a stimulation score calculated according to input SNP information,

A method for predicting skin irritation information of prescriptions containing retinol.
A first threshold stimulus consisting of a pair of (i) a stimulation score determined in advance according to SNP information and (ii) stimulation data including the presence or absence of stimulation or the level of stimulation when a substance containing retinol is applied to an individual having the SNP information. a server that learns a set of learning data to generate a first threshold irritation score prediction model for determining a threshold irritation score that causes skin irritation when a substance containing retinol is applied; and

Receives SNP information of a prediction target entity, calculates a stimulus score according to the input SNP information, calculates stimulus information according to a comparison result of the threshold stimulus score determined by the first threshold stimulus score prediction model and the stimulus score, , a prediction terminal that outputs the calculated stimulus information; including,

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 12,

Among the plurality of SNPs included in the SNP information, a SNPs marker selection device for selecting one or more SNPs related to skin irritation when retinol is applied; further comprising,

The prediction terminal calculates a stimulus score using at least some of the one or more SNPs selected by the SNPs marker selection device.

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 13,

One or more SNPs associated with the skin irritation are any one or more selected from Table 1,

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 13,

The stimulus score is

It can be calculated by summing the allocation scores of each of the one or more SNPs,

The assigned score is,

A first value determined according to the number of major alleles and minor alleles included in each SNP; and

A second value, which is the degree to which each SNP affects skin irritation, which is calculated using

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 15,

The first value is,

Major allele - major allele, major allele - minor allele and minor allele - different values are given for each SNPs type of the minor allele,

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 16,

The first value has a higher value as the number of lower alleles increases among the SNPs types.

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 15,

The allocation score is calculated by multiplying the first value and the second value,

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 12,

Different threshold stimulation scores are determined according to the type of substance added to the retinol,

The threshold stimulus score is determined by a second threshold stimulus score prediction model;

The second threshold stimulus score prediction model,

The learning processor determines (i) a stimulation score predetermined according to the SNP information, (ii) one or more prescription information among a plurality of prescriptions including a retinol prescription and a prescription in which an additional substance is further included in retinol, and (iii) the SNP information By learning a set of second threshold stimulation learning data consisting of pairs of stimulation data including the presence or absence of stimulation or the degree of stimulation when a substance according to each prescription is applied to an object having A model for determining the threshold stimulus score that triggers the stimulus,

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 12,

The threshold stimulus score is determined by a third threshold stimulus score prediction model;

The third threshold stimulus score prediction model,

The learning processor comprises (i) a stimulation score predetermined according to SNP information, (ii) one or more information of age information, gender information, lifestyle information, environmental information, and skin characteristic information, and (iii) having the SNP information By learning a set of third threshold stimulus learning data consisting of pairs of stimulus data including the presence or absence of irritation or the degree of irritation when a substance containing retinol is applied to an object, skin irritation is reduced when a substance according to each prescription is applied. A model for determining each triggering threshold stimulus score,

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 12,

Different threshold stimulation scores are determined according to the type of substance added to the retinol,

The threshold stimulus score is determined by a fourth threshold stimulus score prediction model;

The fourth threshold stimulus score prediction model,

(i) a stimulus score determined in advance according to SNP information, (ii) one or more prescription information among a plurality of prescriptions including a retinol prescription and a prescription in which an additional substance is further included in retinol, (iii) age information, One or more of gender information, lifestyle information, environmental information, and skin characteristic information, and (iv) stimulation data including the presence or absence of stimulation or the degree of stimulation when a substance according to each prescription is applied to an individual having the SNP information A model for learning a set of paired fourth threshold stimulation learning data to determine a threshold stimulation score that causes skin irritation when a substance according to each prescription is applied,

A skin irritation information prediction system for prescriptions containing retinol.
According to claim 19 or 21,

The prediction terminal includes a prescription selection unit that selects and outputs one or more prescriptions among the plurality of prescriptions using a comparison result of a predetermined threshold stimulation score for each prescription and a stimulation score calculated according to input SNP information,

A skin irritation information prediction system for prescriptions containing retinol.
A computer program stored in a computer readable recording medium to execute the method according to any one of claims 1 to 10.
Group consisting of ectoine, trehalose, sucralfate, glucosamine, 4-t-butylcyclohexanol and omega-9 A composition for anti-irritation or anti-inflammatory by retinol comprising at least one irritation reliever selected from as an active ingredient.
According to claim 24,

The irritation reliever is characterized in that it contains 0.1 to 30% by weight based on the total weight of the composition, the composition.
The method of claim 24,

Characterized in that it contains the retinol in an amount of 2500 to 6000 IU, the composition.
According to claim 24,

The composition is a composition that is personalized.
According to claim 24,

The anti-irritant or anti-inflammatory action of the irritation reliever is for a subject comprising a single nucleotide polymorphism (SNP) marker for diagnosis of any one or more retinol sensitivity selected from Table 1 or Table 3, Composition.
According to claim 28,

The single nucleotide polymorphism marker for diagnosing retinol sensitivity is one or more single nucleotide polymorphism markers present in a gene encoding one or more proteins selected from the group consisting of COL6A2, EGFR, IL4R, and ADIPOQ, composition.
According to claim 28,

The single nucleotide polymorphism marker for diagnosing retinol sensitivity is at least one selected from the group consisting of rs117668143, rs1110470, rs6970262, rs2293347, rs2241766 and rs9882205, the composition.
According to claim 28,

The single nucleotide polymorphism marker for diagnosing retinol sensitivity is 5 to 100 consecutive DNA sequences containing base 47551909, wherein base 47551909 of human chromosome 21 is G or A (rs117668143) A polynucleotide consisting of;

A polynucleotide consisting of 5-100 consecutive DNA sequences including base 27336427 of human chromosome 16, wherein base 27336427 is G or A (rs1110470);

A polynucleotide consisting of 5-100 consecutive DNA sequences including base 55259763 of human chromosome 7, wherein base 55259763 is G or A (rs6970262);

A polynucleotide consisting of 5-100 consecutive DNA sequences including base 55201223 of human chromosome 7, wherein base 55201223 is G or A (rs2293347);

A polynucleotide consisting of 5-100 consecutive DNA sequences including base 186570892 of human chromosome 3, wherein base 186570892 is C or A (rs2241766);

A polynucleotide consisting of 5-100 consecutive DNA sequences including base 186570398 of human chromosome 3, wherein base 186570398 is A or G (rs9882205); and at least one polynucleotide selected from the group consisting of complementary polynucleotides thereof.
A cosmetic composition comprising the composition of any one of claims 24 to 31 as an active ingredient.
A quasi-drug composition comprising the composition of any one of claims 24 to 31 as an active ingredient.
A pharmaceutical composition for relieving irritation or treating inflammation by retinol, comprising the composition of any one of claims 24 to 31 as an active ingredient.
(a) obtaining a biological sample from the subject;

(b) amplifying a polymorphic site of one or more single nucleotide polymorphism markers selected from the group consisting of rs117668143, rs1110470, rs6970262, rs2293347, r2241766 and rs9882205 from the biological sample or hybridizing with a probe; and

(c) A method for providing information for selecting a customized irritation reliever for irritation relief or inflammation relief by retinol, comprising the step of confirming the base of the polymorphic site amplified or hybridized in step (b).
The method of claim 35,

The irritation reliever is at least one selected from the group consisting of ectoin, trehalose, sucralfate, glucosamine, 4-t-butylcyclohexanol and omega-9, information providing method.
The method of claim 35,

Wherein the sample is hair, urine, blood, various body fluids, separated tissue, separated cells or saliva.
The method of claim 35,

Amplification and identification of the polymorphic site is to use a SNP chip, information providing method.