In a world that increasingly demands personalization from brands, DNA profiling is proving a handy tool. For some years, health and wellness startups have claimed they can mine data from a customer’s DNA to provide unique recommendations tailored to that individual. Genetic testing is now being applied to everything from medicine to fitness to food and nutrition, and of course, the current obsession with skincare.

A new wave of skincare-focused tech startups is taking a multi-pronged approach to individualization. This means combining advanced DNA analysis with 3D imaging and artificial intelligence to create, in the words of Sindhya Valloppillil, some of the most “hyper-customized, made-to-order, bespoke” products yet. Valloppillil, the cofounder and CEO of skincare tech startup SkinGenie, is describing her company’s latest project, Kode, a beauty brand that customizes skincare products according to data from each customer’s DNA. Kode has not been released to the market yet, but when it is, Valloppillil claims, SkinGenie will be the first company to offer a made-to-order DNA-based skincare option.

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Some of the earliest major players in the DNA-based skincare space, such as London’s GeneU and Swedish company Allél, use a simple DNA test to curate anti-aging serums and recommendations for customers out of a fixed product range. But SkinGenie, which has won a number of awards since its January 2018 launch, including Johnson & Johnson Innovation’s Digital Beauty QuickFire Challenge, will likely be hailed as a breakthrough by beauty editors who have been disappointed by other DNA-based products for their failure to be entirely customizable.

Valloppillil says the SkinGenie customization analysis differs from that of other startups because it’s informed by a more comprehensive, detailed collection of data. SkinGenie and its parent biotech company LifeNome use a deep learning algorithm that distills data from more than 2,400 genomic and dermatology studies, 140 genetic variants and 95 genetic biomarkers to create a risk score that determines an individual’s predisposition to more than 30 skin traits, to reveal which nutrients the skin needs. The company aims to help consumers decide which combination of skincare ingredients will work best for them, based in part on their genetic makeup, even if certain signs of aging haven’t appeared yet. For example, a customer may need a more effective moisturizer because they’re more susceptible to dry skin, or a fragrance-free cream due to sensitivity.

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Many board-certified dermatologists have responded to DNA-based skincare brands’ claims over the years with a heavy dose of skepticism, arguing that there are no strong, evidence-based clinical studies that prove a connection between various genetic biomarkers and the effects of formulas or ingredients. There is currently no FDA approval process surrounding DNA assessments that aren’t directly related to disease, so the business remains highly unregulated.

Then again, there are plenty of naysayers in the skincare industry in general. There’s also always new research being conducted—Valloppillil says that as part of the award prize “we are doing a clinical study with Johnson & Johnson on the efficacy of our AI & DNA-based diagnostics and personalization technology for skin and hair care.”

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There are a number of reasons why the industry will likely continue to grow, even if some dermatologists remain unconvinced. Barriers to entry for DNA testing have been lowered with the rise of direct-to-consumer companies like AncestryDNA and 23andMe, meaning consumers no longer have to shell out hundreds of dollars for an analysis. SkinGenie is compatible with most of these mainstream tests, which more than 12 million people in the United States have already taken, according to MIT Technology Review, making its assessment considerably more accessible.

Even without the DNA component, SkinGenie offers an alluring app for skincare buffs looking to simplify their lives: one that harnesses artificial intelligence to help sift through thousands of skincare products online so that the customer doesn’t have to.

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And it’s not the only brand to do so. Another newcomer, Proven, is planning to debut what its founders say will be an accessible skincare range in July. The range was developed using a deep learning algorithm that combines user reviews of more than 100,000 products with scientific research that details how ingredients specifically relate to skin health. Switzerland-based company iDDNA uses an AI algorithm to measure how skincare needs to change with a person’s changing environment and lifestyle and tweaks its curated batch of products based on its assessment.

“Now we’re seeing so many indie brands popping up, many of them started by influencers or celebrities, people who have no industry experience or credibility—they’re not scientists and they’re not dermatologists. They’re outsourcing their development, and many of them have the same product, they’re just different names and different packaging,” Valloppillil tells JWT Intelligence. “How do you even begin to find and discover the right products? Most people do not want to spend an hour looking for the right face mask, or the right eye cream.”


SkinGenie’s AI-powered, shoppable app uses a lifestyle survey and the optional DNA test results to curate a list of products that already exist. For now, the app only features products stocked among Sephora’s brand lineup, but SkinGenie plans to partner with other retailers to broaden its users’ options. Retailers have the potential to directly benefit from these hyper-customization tools too. Many are already working with Modiface, which helps customers test out makeup colors using augmented reality. SkinGenie’s products for enterprises take things a stage further with its DNA and AI-based personalization services, plus state-of-the-art 3D skin imaging technology that determines environmental-based signs of aging.

As for the future of the industry, MIT Technology Review says around one in 25 Americans already has access to their personal genetic data; with continued advancements in AI and new startups innovating on existing business models, it’s likely to continue to evolve.

“This is here to stay,” Valloppillil says.“And I think the more science and technology you can apply, to make the process more efficient and effective, the more it’s going to stick.”

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