CEATEC 2025 featured the usual lineup of AI demos, service robots, and experimental interfaces. But inside Hall 4, a quieter, lab-style booth stood out for a very different reason. There, the RNA Co-creation Consortium demonstrated that RNA extracted from facial sebum can provide insights into the skin’s condition and support better day-to-day cosmetic choices.
The booth’s theme, “RNA-Tech Driven Society – A new standard of living redefined by RNA-Tech,” reflected this ambition. The consortium unveiled an ecosystem—one part lab science, one part smartphone interface, and one part retail experience—built around the idea that your skin’s RNA is a valuable source of information, and that this signal can be translated into an easy, consumer-friendly experience.
Most people choose skincare through guesswork, but this technology replaces guesswork with real biological insight. By analyzing RNA in skin oil—or inferring it through a selfie—the system can understand what your skin actually needs at that moment. That means fewer wasted products, better results, and a routine that adapts to stress, weather, and lifestyle changes. It is an early look at how biotech and AI could make skincare simpler, more personalized, and more reliable for everyone.
A Cross-Industry Approach to Rethinking Skin Data
The RNA Co-creation Consortium was founded in March 2024 by Kao Corporation and istyle Inc., the company behind the influential Japanese @cosme beauty platform. Since then, partners from multiple industries—including KOSÉ, MatsukiyoCocokara, Kirin, Perfect Corp., and Healthcare Systems—have joined. Each brings a different piece of the puzzle: Kao contributes biological R&D and wet-lab expertise; istyle brings its consumer reach and app infrastructure; and others add perspectives on cosmetics, wellness, and retail.
The consortium’s mission is to create new standards for how people choose beauty and health products. Behind the marketing language lies a clear scientific foundation. Over the past several years, Kao researchers have established that RNA is present in human sebum, which can be collected easily using everyday oil blotting films. More importantly, these RNA molecules remain intact enough for gene-expression analysis. Unlike DNA, which remains constant, RNA fluctuates in response to physical and environmental factors, such as diet, exercise, stress, and UV exposure, as well as broader lifestyle factors.
This led to Sebum RNA Monitoring, Kao’s pipeline for extracting RNA from sebum and analyzing its expression patterns across thousands of genes. When researchers compared hundreds of profiles, distinct clusters appeared. Two of the most robust were labeled C1 and C2. C1 is enriched for keratinization-related genes related to barrier function, while C2 is associated with immune-response genes. These categories do not replace classic skin-type labels—dry, oily, combination—but they provide a more biologically grounded lens into how the skin is behaving internally.
This is the foundation upon which the consortium wants to build a new user experience. RNA becomes the objective signal. The consortium’s companies build services around it. And consumers gain access to diagnostics that feel both personalized and scientifically grounded.
How Sebum RNA Monitoring Works
Visual display boards at the booth walked visitors through Kao’s full sebum RNA workflow. The process begins with sebum collection using a simple oil blotting film pressed onto the skin. In the lab, the RNA is extracted, refined, and passed into a comprehensive analysis pipeline. The system measures gene expression across thousands of RNA species, producing a snapshot of biological activity. Because RNA fluctuates with daily conditions, it reflects the skin’s condition at that moment rather than a fixed classification.
Kao has noted in research communications that sebum RNA monitoring shows potential to help infer conditions such as pediatric atopic dermatitis or Parkinson’s disease. However, these ideas remain strictly experimental and are not intended for medical diagnosis.
At CEATEC, however, the emphasis remained on everyday skincare, and the consortium wanted visitors to experience the complete journey: from laboratory workflow to a system that, through creative use of AI, no longer requires any RNA sampling.
From Lab Science to a Smartphone App
The star of the booth was the @cosme app’s “Skin Care Timing Diagnosis” feature—presented at CEATEC under the friendlier tagline “Diagnoses on When to Pamper Your Skin.” The technological trick is clever: the team used a large dataset of users who had both sebum RNA profiles and facial photos. With enough examples, an image-analysis AI can learn to infer RNA-driven skin types from photos alone.
This allowed the consortium to bring RNA science to everyday users without requiring a blotting sheet or a lab visit. You take a selfie.
Visitors at CEATEC were invited to try the experience. After entering age information, the system captured three bare-faced selfies with slightly different backgrounds to normalize lighting. In about ten seconds, the app returned a detailed report. The screen showed a photo overlaid with bright green and orange lines, revealing the system’s assessment of texture, spots, and tone. On the right, a looping RNA icon displayed the result: C1 or C2.
During my own demo, the system classified me as C2, and the staff explained that C2 corresponds to higher activity of immune-related genes. The interface framed this as a “skin mode” that can shift depending on lifestyle and environmental factors.
Below the classification, the app revealed a metric it calls skin age. In my case, it displayed 40 years—slightly younger than the age we had entered. Then came the core of the experience: a set of recommendations identifying where improvements would have the most impact today. Instead of diagnosing flaws, the app organizes its analysis around two concepts: the Smooth Phase, where texture-focused care is most effective, and the Glowing Phase, where radiance-related improvements have the biggest payoff.
The system placed me in the Glowing Phase, flagging dullness, a yellowish tone, and luminosity as targets where appropriate care could yield immediate benefits. Interactive graphs compared my values with those of others in my age group, and different filters revealed pores, wrinkles, oiliness, and additional variables.
The experience feels calm and positive—more like an intelligent camera lens that understands what your skin is ready to respond to.
Beyond Skin: Tracing Daily Biological Signals
The demo continued beyond the cosmetic layer. Another screen displayed a “circulation bias” indicator, which staff described as reflecting factors such as hydration, overall skin support, and circulation rather than a clinically measured physiological value. When asked about my score, they casually suggested hydrating or choosing a nutrient-rich beverage—a subtle nod to Kirin’s involvement and a reminder that beauty, health, and lifestyle increasingly overlap.
A separate view presented an “immune score,” meant to illustrate how strongly the current analysis aligns with the immune-active C2 pattern. It is not a medical reading, but it reinforces how internal skin biology can be expressed in a consumer-friendly interface.
The Final Step: Product Discovery Through RNA Analysis
The final station demonstrated how the RNA results can help guide retail recommendations. Products from consortium partners were laid out on a long white counter, grouped by C1 and C2 skin behavior types, with additional labels for the Smooth Phase and Glowing Phase.
The staff explained that this approach reduces misalignment between customer expectations and product results. If people with similar RNA-driven skin behavior tend to respond similarly to specific formulations, the shopping journey becomes less random. Retailers benefit through fewer returns and better targeting; consumers benefit through higher product satisfaction.
In the context of CEATEC, this was a refreshing shift from hardware-driven demos toward biology-driven UX. It merges biotech, AI, and retail design into one loop: understand the skin, guide the user, and connect them to products without overwhelming them.
This demo suggests that RNA collected from skin sebum, paired with a large photo database, could make cosmetic recommendations more precise and better matched to each person’s needs. Over time, it may also support more sustainable product choices.
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