DayTwo, a Tel Aviv, Israel and San Francisco, California-based developer of a microbiome-health management platform, completed a $12.0m Series A round of financing.
Backers included Johnson & Johnson Innovation – JJDC, Inc. (JJDC), Seventure Partners’ Health for Life Capital fund, Mayo Clinic, co-founder Marius Nacht, and other private investors.
The company, which has raised $17.0m in total funding, intends to use the funds to expand its product, engineering, and data science teams in Tel Aviv, Israel and San Francisco, California, and deepen its clinical research with the Mayo Clinic and other gut-microbiome clinical research partners.
Led by Chief Executive Officer Lihi Segal, DayTwo has developed a method to accurately predict an individual’s glycemic response to specific foods and food combinations using an individual’s microbiome and other clinical factors. Day Two can bring a personalized diet and nutrition plan to individuals, based on accurately predicting their own glycemic response.
The personalized nutrition offering is based on the original research led by Professors Eran Segal and Eran Elinav from the Weizmann Institute of Science in Israel, and published in the scientific journal Cell. Segal and Elinav found that by profiling an individual’s gut microbiome and leveraging machine learning, they can accurately predict an individual’s post-meal blood sugar response for unique foods and food combinations.
For consumers, DayTwo offers a cloud-based diet and nutrition planner, which enables individuals to get personalized scores for specific foods and food combinations based on their own gut-microbiome profile and other personal parameters.
For clinicians and health practitioners, DayTwo brings actionable insights for diet and nutrition to the care plans and meal plans of their patients and provides an additional path for clinicians and their patients to stay connected.
For nutrition, microbiome, weight-management, and meal planning businesses, DayTwo offers an API to access the DayTwo platform-as-a-service to provide predictive glycemic response scores for specific foods and food combinations.