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Dermaself has adapted its AI skin-analysis platform for remote cosmetic efficacy studies run by testing laboratories. The company says the system can measure more than 60 visible skin parameters from volunteer photos and compare results over time; laboratories remain responsible for study design, expert review and conclusions.
Milan-based beauty technology company Dermaself has adapted its AI skin-analysis platform for remote cosmetic efficacy studies, allowing testing laboratories to measure volunteers’ skin from photos taken at home. The development could let laboratories collect image-based measurements at more locations and across larger groups, while the laboratory—not the AI—continues to oversee the protocol and conclusions.
Dermaself’s platform analyses a selfie for more than 60 visible skin parameters and can compare measurements at set points during a study. The company says its patent-pending colour normalisation adjusts for differences in lighting and colour between images. It reports repeatability of 0.92–0.93 on repeated measurements of the same skin; the source does not specify the metric or testing conditions behind that figure.
In the proposed workflow, the testing laboratory defines the protocol, including endpoints and photo checkpoints. Volunteers take a baseline image and repeat the capture at intervals, such as after two, four and eight weeks. The platform compares each image with that person’s baseline and produces results for individual volunteers and the cohort. The laboratory’s experts then prepare the study report and conclusions.
Dermaself says a study setup can be ready in five days and that remote studies can include as many as 10,000 volunteers. These are company-stated capabilities, not independently verified results from a completed study described in the source. The system is intended to automate repeated image scoring, not replace expert graders or make decisions about product claims.
How At-Home Measurement Could Expand Studies
Remote image collection could reduce two practical constraints in cosmetic testing: testing-site capacity and participants’ need to travel for each assessment. If laboratories can recruit and retain volunteers who would not attend repeated in-person visits, they may be able to study more people or include participants across a wider area. That could make some study designs easier to run, though the source provides no completed-study data showing actual changes in cost, recruitment or completion rates.
Consistent scoring also matters when a study compares images across weeks. Dermaself says the AI applies the same criteria to each image, potentially reducing variation associated with manual grading. However, image-based measures are only one part of an efficacy study: laboratory experts still interpret the data, and brands and their regulatory teams decide whether evidence supports a particular product claim.
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From Routine Advice to Study Measurement
Dermaself already offers AI skin analysis for brand and retailer websites, stores and events. Its system also reads product ingredient lists to recommend routines from a company’s own catalogue. The company says its underlying skin taxonomy was developed with Derming, an independent research institute in Monza, and validated on more than 100,000 clinical images reviewed by board-certified dermatologists.
The remote-study service applies that image-measurement technology to a different task: tracking skin parameters against a volunteer’s own baseline under a laboratory-designed protocol. Brands can ask a testing laboratory they already work with about using the platform; according to the source, Dermaself supplies the technology to laboratories, while the laboratory manages the study, participants and reporting.
““The AI does not replace expert graders.””
— Dermaself
Evidence, Privacy and Study Results
The source does not identify a completed remote study, participating laboratory, client brand or results from volunteers using the platform. It is also unclear how the reported 0.92–0.93 repeatability was calculated, which parameters it covers, or how performance varies with phone models, lighting and photo quality in real-world use.
Dermaself says faces are irreversibly anonymised before analysis using patent-pending 3D anonymisation, and that data-protection terms are agreed with the laboratory before each study. The source does not provide technical details, independent validation of the anonymisation process, or the specific retention and access rules. Whether study measurements support a product claim remains for the laboratory and the brand’s regulatory team to decide.
Laboratories Will Determine Adoption
The next step is for testing laboratories to decide whether to add remote image capture and AI measurement to studies they design for brands. Brands interested in using the service can ask their existing testing partner whether it offers the approach; they do not necessarily need to contract with Dermaself directly.
Evidence from actual studies will help clarify the platform’s practical performance, including participant adherence, image consistency, privacy safeguards and how AI measurements fit into expert review. The source gives no launch schedule, named laboratory partners or dates for published study results.
Key Questions
What does Dermaself’s remote study platform do?
It analyses volunteers’ photos to measure more than 60 visible skin parameters and compare results with each volunteer’s baseline at study checkpoints.Does the AI replace dermatologists or laboratory graders?
No. Dermaself says the platform automates repeated image scoring. The testing laboratory remains responsible for study design, expert evaluation and conclusions.Can a brand keep its current testing laboratory?
According to Dermaself, yes. The company provides the platform to testing laboratories, so a brand can ask its existing partner whether it can run a study with remote image capture.Does an AI measurement prove a cosmetic product claim?
No. The platform supplies image-based measurements, but whether those results support a specific claim is a decision for the laboratory and the brand’s regulatory team.Source: rss
