Personalized skin analysis and skin care

Abstract

The present invention provides a method of providing a consumer with skin analysis and personalized skin care information based on the analysis at a retail point, the method comprising: (i) receiving, at the retail point, a skin microbiome sample collected in a non-invasive manner from a skin surface of the consumer, (ii) extracting DNA from the skin microbiome sample, and analyzing the extracted DNA using a portable qPCR thermocycler configured to amplify and detect nucleic acids associated with a group of microorganisms in the sample, (iii) uploading analysis data from the thermocycler to a machine learning platform, and (iv) providing, at the retail point, a spectrum of skin microbiome of the consumer and a personalized skin care protocol for the consumer, which is generated from the analysis data using the machine learning platform.

Description

Technical Field

[0001] The present invention relates to a method for providing skin analysis and personalized skin care information based on such analysis to consumers. Background Art

[0002] The deluge of information on the Internet and in social media teaches consumers to pay attention to their beauty needs and spurs a growing demand for personalized skin care solutions that address their unique concerns.

[0003] Attempts have been made to develop personalized skin care solutions for consumers, for example by measuring visible skin parameters (such as gloss, spots, wrinkles, roughness and irregular pigmentation), and using the data thus obtained to inform product recommendations or designs.

[0004] While the numerical values of visual assessments are unproblematic, the measured phenotypic characteristics are typically the end products of the underlying mechanisms responsible for healthy skin and its appearance. To effectively personalize skin care, an in-depth understanding of these underlying mechanisms is needed. This requires an understanding of the skin microbiome and how to maintain its delicate balance. Skin microbiome dysbiosis (ecological imbalance) is associated with a number of skin conditions, pathological (such as atopic dermatitis, acne vulgaris, psoriasis or lichen planus), or non-pathological (such as sensitive skin, oily skin or dry skin).

[0005] Skin microbiome test kits have been developed for consumer use, which typically involve using a sterilized swab to collect a skin microbiome sample from the skin surface by wiping the swab across the skin several times. The sample is then sent to a laboratory for DNA extraction and sequencing analysis to determine which microorganisms are present. Thus, there can be a significant time lag between sample collection and analysis, often several days to weeks.

[0006] An object of the present invention is to provide skin analysis and personalized skin care information based on such analysis to consumers at the point of sale. Summary of the Invention

[0007] The present invention provides a method for providing skin analysis and personalized skin care information based on such analysis to consumers at the point of sale, the method comprising:

[0008] (i) at the point of sale, receiving a skin microbiome sample collected non-invasively from the skin surface of a consumer,

[0009] (ii) extracting DNA from the sample and analyzing the extracted DNA using a portable qPCR thermal cycler configured to amplify and detect nucleic acids associated with the microbiota in the sample,

[0010] (iii) Upload the analytical data from the thermal cycler to a machine learning platform, and

[0011] (iv) Provide, at the retail point, a profile of the consumer's skin microbiome and a personalized skin care regimen for the consumer, which is generated using the machine learning platform from the obtained analytical data. DETAILED DESCRIPTION

[0012] As used herein, "skin care" refers to the cosmetic quality of regulating and / or improving the skin. These qualities are to be regulated and / or improved in the context of health topics as well as topics of skin diseases or disorders (such as atopic dermatitis, acne vulgaris, psoriasis or lichen planus) that occur.

[0013] Examples of skin care benefits within the scope of the present invention include providing a smoother, flatter texture; improving the elasticity or resilence of the skin; improving the firmness of the skin; reducing the oily, shiny and / or dull appearance of the skin; improving the hydration state or moisture retention of the skin, improving the appearance of fine lines and / or wrinkles; improving skin exfoliation or desquamation; plumping the skin; improving skin barrier properties; improving skin color; reducing the appearance of redness or skin spots, and improving the brightness, gloss or translucency of the skin.

[0014] In step (i) of the method of the present invention, a skin microbiome sample is collected non-invasively from the skin surface of a consumer. Typically, this involves using a sterile cotton-tipped swab and rolling it over the skin surface with moderate pressure and a circular motion.

[0015] The skin surface of the consumer is preferably the facial skin surface, such as one or more of the forehead, periorbital, cheek, perioral, chin and nose skin surfaces.

[0016] In step (ii) of the method of the present invention, DNA is extracted from the sample and the extracted DNA is analyzed using a portable qPCR thermal cycler.

[0017] During DNA extraction, efficient lysis of the microbial cell wall is important for obtaining optimal yields of DNA from the skin microbiome sample. Cell lysis methods include physical (heat), mechanical (sonication, bead beating), chemical (pH, detergents), and enzymatic lysis of the microbial cell wall, often combining different methods. Mechanical lysis methods, such as bead beating, can increase nucleic acid yields by effectively lysing not only Gram-negative bacteria but also Gram-positive bacteria, which have thick cell walls. The sample is placed in a tube containing grinding beads, and high-energy mixing is applied. The sample is then typically centrifuged, and the lysate is recovered above the beads. Filter-based methods, such as the Biomeme M1 Sample Prep Cartridge TM (Biomeme Inc., Philadelphia, USA), can also be used, where nucleic acids are bound to a silica membrane within a perforated tool attached to a syringe. The sample is pumped through the membrane along a sealed filter cartridge chamber containing lysis buffer, wash buffer, and elution buffer. The advantage of the M1 extraction process is that it does not require centrifugation.

[0018] A thermal cycler (also known as a thermocycler or PCR machine) amplifies DNA by regulating the temperature in a cyclic program that includes steps of DNA denaturation, primer annealing, and extension.

[0019] In qPCR (also known as quantitative PCR or real-time PCR), fluorescent labeling enables real-time monitoring of DNA amplification by monitoring fluorescence. Fluorescence is measured after each cycle, and the intensity of the fluorescence signal reflects the instantaneous amount of DNA amplicons in the sample at that particular moment. In the initial cycles, the fluorescence is too low to be distinguishable from the background. However, the point at which the fluorescence intensity rises above the detectable level corresponds proportionally to the initial number of template DNA molecules in the sample. This point is called the quantification cycle and allows determination of the absolute quantity of target DNA in the sample according to a calibration curve plotted from a series of diluted standard samples (usually ten-fold dilutions) with known concentrations or copy numbers. qPCR can also provide semi-quantitative results without using standards but using a control as a reference material. In this case, the observed results can be expressed as a multiple higher or lower than the reference control.

[0020] A portable qPCR thermal cycler suitable for the present invention generally includes a housing, an amplification (or PCR) module, and a detection module. The amplification module is configured to receive an input sample and define a reaction volume. The amplification module includes a heater such that the amplification module can perform polymerase chain reaction (PCR) on the input sample. The detection module is configured to receive the output from the amplification module and reagents formulated to generate a signal indicating the presence of target amplicons in the input sample. The amplification module and the detection module are integrated within the housing.

[0021] The portable qPCR thermocycler preferably used in the present invention has a size that can be held in the operator's single hand.

[0022] The weight of the portable qPCR thermocycler preferably used in the present invention does not exceed 3.5 kg, more preferably does not exceed 3 kg, for example 0.4 to 2.5 kg.

[0023] The portable qPCR thermocycler suitable for the present invention is commercially available, such as Franklin TM (Biomeme Inc., Philadelphia, USA), which weighs less than 1 kg, can test biological samples without centrifugation, using cryopreserved reagents, or mains power. The device can multiplex and detect up to three targets in each sample, where nine samples can be tested in a single run and results are given in less than one hour. Other commercially available portable qPCR thermocyclers that can be used in the present invention include the Mic qPCR cycler (Bio Molecular Systems Pty Ltd., Upper Coomera, AU) and the Liberty16 system (Ubiquitome Ltd, Auckland, New Zealand).

[0024] In step (ii) of the method of the present invention, the portable qPCR thermocycler is configured to amplify and detect nucleic acids associated with the microbiota of the sample.

[0025] The microbiota is suitably composed of 5 to 15, preferably 8 to 10 different skin microorganisms.

[0026] For optimal skin health characterization, the microbiota includes at least 5, more preferably at least 6, most preferably at least 7 skin microorganisms representing the following genera / species: (i) Acinetobacter spp., (ii) Corynebacterium spp., (iii) Cutibacterium acnes, (iv) Lactobacillus spp., (v) Staphylococcus aureus, (vi) Staphylococcus epidermidis, (vii) Staphylococcus hominis, (viii) Staphylococcus capitis, and (ix) Streptococcus spp.

[0027] Ideally, the microbiome of the microorganism consists of 9 different skin microorganisms, representing each of the following genera / species: (i) Acinetobacter spp., (ii) Corynebacterium spp., (iii) Cutibacterium acnes, (iv) Lactobacillus iners, (v) Lactobacillus crispatus, (vi) Staphylococcus aureus, (vii) Staphylococcus epidermidis, (viii) Staphylococcus hominis, and (ix) Streptococcus spp.

[0028] In step (iii) of the method of the present invention, the analysis data from the thermal cycler is uploaded to the machine learning platform.

[0029] Generally, the electronic circuit in the housing of the portable qPCR thermal cycler (such as the above) is suitable for transmitting the analysis data to the machine learning platform through a wired or wireless communication interface such as USB or Transmit the analysis data to the machine learning platform.

[0030] The machine learning platform uses one or more algorithms to generate a profile of the consumer's skin microbiome and a personalized skin care protocol for the consumer based on the transmitted analysis data. The algorithm can be stored and implemented on a computing device carried at the retail point (such as a smartphone, tablet, laptop, desktop computer or workstation), or the algorithm can be provided by a remote server, and the analysis data is transmitted to it via a cloud service or a network service. The algorithm can be based on a trained machine learning model, such as an anomaly detection model or a convolutional neural network.

[0031] Additional analysis data on the consumer's skin properties can also be used to improve the personalization of the protocol. The machine learning platform can, for example, obtain skin imaging data taken by a mobile device with a camera function (such as the consumer's own smartphone or tablet), and use one or more computer vision algorithms to analyze properties such as dryness, aging, acne, oiliness and pore enlargement, melasma, and dark spots and dullness. The properties can be scored and then normalized to a coefficient after comparison with a reference dataset of other users.

[0032] In step (iv) of the method of the present invention, at the retail location, a profile of the consumer's skin microbiome and a personalized skin care protocol for the consumer are provided, which are generated from the obtained analytical data using the machine learning platform.

[0033] Preferably, step (iv) is performed within 90 minutes, more preferably within 60 minutes, of receiving the skin microbiome sample in step (i).

[0034] For example, if a particular member of the group of microorganisms is identified in the sample at a level deviating from the normal reference level, which is established for these microorganisms in a healthy skin microbiome, the profile may indicate a dysbiosis in the consumer's skin microbiome. The profile may also include a general classification of the consumer's skin microbiome based on the relative abundances of the particular members of the group of microorganisms identified in the sample, such as "rich in Cutibacterium acnes", "rich in Lactobacillus", or "rich in Staphylococcus". The profile may also include an indication of the risk of skin conditions, which is associated with the signature microbiome profile. Advantageously, this can be before the manifestation of the skin condition phenotype, enabling preventive intervention.

[0035] The personalized skin care protocol may, for example, recommend the topical administration of a cosmetic composition, which is designed to move the consumer's skin microbiome profile towards a healthy balance, depending on the consumer's skin microbiome profile.

[0036] Thus, the topical cosmetic composition for use in the present invention may comprise one or more microbiome-balancing active ingredients in a cosmetically acceptable vehicle.

[0037] Suitable microbiome-balancing active ingredients for use in the present invention include prebiotics that can selectively enhance the growth and / or activity of target skin microorganisms such as Staphylococcus epidermidis. Examples of prebiotics for S. epidermidis include pimelic acid (and / or its anhydride), sucrose, lactose, ribose, maltose, mannose, sugar isomers, and glycerol and mixtures thereof.

[0038] Alternatively, the microbiome-balancing ingredient can selectively reduce the growth and / or activity of target skin microorganisms such as Cutibacterium acnes in acne-prone skin. An example of such an ingredient is a blend of thymol and terpineol.

[0039] Mixtures of any of the above materials can also be used.

[0040] The topical cosmetic composition for the present invention may additionally comprise one or more skin care actives designed to target specific skin attributes of the consumer based on the above image analysis. Examples of such skin care actives include vitamins, minerals and / or antioxidants, emollients, skin brighteners, sunscreens, anti-irritants, exfoliating agents, and mixtures thereof.

[0041] The term "cosmetically acceptable" means that the vehicle is suitable for topical application to the skin, has good aesthetic properties, is compatible with any other ingredients, and does not give rise to any safety or toxicity concerns.

[0042] The vehicle may comprise an aqueous phase, an oil phase, an alcohol, a silicone phase, or mixtures thereof, and may be in the form of an emulsion. The emulsion may have a range of consistencies, including thin lotions (also suitable for spray or aerosol delivery), cream lotions, light creams, and heavy creams.

[0043] The topical cosmetic composition for the present invention may also be formulated in a single-phase carrier such as water and / or one or more water-miscible organic liquids.

[0044] The topical cosmetic composition for the present invention may also be formulated in solid form, such as a gel or a stick.

[0045] Combinations of any of the above product forms may also be used.

Claims

1. A method for providing skin analysis and personalized skin care information based on said analysis to a consumer at a retail point, the method comprising: (i) receiving at the retail point a skin microbiome sample collected non-invasively from the skin surface of the consumer, (ii) extracting DNA from the skin microbiome sample and analyzing the extracted DNA using a portable qPCR thermocycler configured to amplify and detect nucleic acids associated with the microbiota of the sample, (iii) uploading the analysis data from the thermocycler to a machine learning platform, and (iv) at the retail point, providing a profile of the consumer's skin microbiome and a personalized skin care protocol for the consumer, the protocol being generated from the analysis data using the machine learning platform, wherein the portable PCT thermocycler is capable of multiplex detecting up to three targets in each sample, wherein nine samples can be tested in a single run, and wherein the microbiota consists of nine different skin microorganisms representing each of the following genera / species: (i) Acinetobacter spp., (ii) Corynebacterium spp., (iii) Cutibacterium acnes, (iv) Lactobacillus iners, (v) Lactobacillus crispatus, (vi) Staphylococcus aureus, (vii) Staphylococcus epidermidis, (viii) Staphylococcus hominis, and (ix) Streptococcus spp.).

2. The method according to claim 1, wherein the portable qPCR thermocycler weighs from 0.4 to 2.5 kg.

3. The method according to any one of the preceding claims, wherein step (iv) is carried out within 90 minutes of receiving the skin microbiome sample in step (i).