Personalised nutrition player DayTwo gains €10.6 million investment

By Nathan Gray contact

- Last updated on GMT

iStock / MarianVejcik
iStock / MarianVejcik

Related tags: Obesity, Nutrition

Microbiome app developer DayTwo has secured €12 million (€10.6m) investment from Seventure Partners’ Health for Life Capital fund, as part of a series A round of fundraising.

Israel-based DayTwo offers a personalised nutrition recommendation service through an app, with information based on machine-learning algorithms that integrate personalised gut microbiome data.

The company exclusively licensed technology developed by Professors Eran Segal and Eran Elinav from the Weizmann Institute of Science in Israel. The machine-learning technology is based on a five-year research project that was published in Cell​, and covered by NutraIngredients in 2015​.

“What we’ve been doing since then is building a product, an application that will be a consumer-based product,”​ Lihi Segal, CEO and co-founder of DayTwo told NutraIngredients-USA in an interview last year​.

The $12m investment by Seventure Partners comes in syndication with Johnson & Johnson as well as historical investors, and will be used by DayTwo to commercialise its product internationally, and to develop new products tailored for other user segments.

Earlier this year, DayTwo announced a collaboration with Johnson & Johnson​ – which will see the company’s partner on personalised clinical nutrition for diabetes. The firm also said it plans to open up its nutrition recommendation platform to new partners.

“What we’re doing right now is claiming to balance your blood sugar levels, and it’s in the area of wellness and general health. Where we’re taking this is into a more clinical, medical outcome,”​ CEO Lihi Segal told us at the time.

Series A investment

According to the firm, the first stage of the new commercialisation stage will be to target highly-motivated consumers, giving them insight into how to manage the food choices that are best for them.

“DayTwo is a great example of how technology and life sciences can intersect, in the fast growing area of healthcare IT is now expanding into the microbiome and personalised nutrition space,” ​commented Isabelle de Cremoux, CEO and Managing Partner of Seventure.

“DayTwo brings the latest progress of microbiome science to users’ fingertips. Its proprietary analysis of stool samples is turned into actionable nutrition advice to manage their well-being and health,” ​she said. “The field of nutrition advice largely relies on general recipes based questionable heuristics. DayTwo brings a strong scientific grounding to this advice, and makes it personal by connecting it directly to each individual’s gut physiology.”

de Cremoux added that the new investment ‘rounds out’ Seventure’s microbiome portfolio, which  already includes Enterome, LNC, Maat Pharma, TargEDys, Eligo Bioscience, BiomX and Vedanta. However, she noted that the firm anticipates making additional investments from the Health for Life Capital in the coming months.

Machine-learning: Stepping into the fight against obesity?

Since their research in Cell in 2015, Weizmann Institute researchers Segal and Elinav have continued working on machine-learning and the microbiome. Last year, the pair led a study published in Nature​ that suggested rapid post-diet weight gain – often referred to as yo-yo dieting – could be a result of obesogenic gut bacteria which remain even after weight loss​.

"We've shown in obese mice that following successful dieting and weight loss, the microbiome retains a 'memory' of previous obesity,"​ said Elinav at the time.

"This persistent microbiome accelerated the regaining of weight when the mice were put back on a high-calorie diet or ate regular food in excessive amounts," ​Segal explained.

Based on their initial observations, the team developed machine-learning algorithm based on hundreds of individualised microbiome parameters. This algorithm was found to successfully and accurately predict the rate of weight regain after dieting in mice.

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