Project Description

T2D & Me helps people with type 2 diabetes improve their health outcomes by providing voice based personalized treatment and nutrition guidance based on the individual’s microbiome analysis.


Our digital therapeutics target people living with type 2 diabetes and the pharma companies developing precision therapies for this population. The bacteria in our gut plays a critical part in regulating the body's metabolism, making it a key to diabetes management and possibly for reversing the disease progression. However, taking their microbiome into account is out of reach for most patients. Our voice-based biofeedback to the patient will help them make good dietary and supplement choices, enabling them to improve their health outcomes by caring for their gut microbiome, effectively addressing an unmet need.

Targeting the microbiome can unlock better tolerance to drugs. Although metformin is a first in line treatment for type 2 diabetes, forty percent of the 18 million treated patients in the US do not benefit from the metformin treatment, often due to Gastro-intestinal (GI) intolerance. Together with GI microbiome modulators, nutrition changes to modify the microbiome might allow greater use of drugs like metformin in T2D patients and improve treatment of the disease.


Our solution combines the analysis of the microbiome with current voice activation technology to provide the patient with personalized nutrition guidance. Nutrition advice is based on the individual’s microbiome so she can make the right food choices for her body.

The solution will be available across the different voice platforms including Amazon Echo and Google Home. We provide personalized nutrition and treatment advice in a simple question/answer format, avoiding currently unrealistic complex natural language dialogue.

Our use of voice technology is a better fit than using mobile apps for microbiome based nutrition guidance. Voice bots can provide immediate feedback on demand to the patient without requiring the opening of an app or other delaying steps.

While we initially use third party microbiome sequencing, our solution is an excellent fit for the emergence of smart toilets that daily analyze the individual’s microbiome from human waste. Smart toilets may potentially also use DNA analysis to automatically track ingredients consumed in food, providing additional information for biofeedback without tedious manual documentation of food intake.

Sustainability and Feasibility

Type 2 diabetes is a $174 billion dollar problem just in the US, affecting at least 18 million Americans and growing at an epidemic rate, providing a substantial market size.

Our revenue model is based on using the collected data from patients in an online platform to support development of novel treatments, delivery of precision medicine, and pharmacovigilance.

We believe supporting development of better treatments while respecting the privacy of the patient is a win-win business model that benefits all stakeholders. Patients will benefit by new therapies, targeted treatments and improved drug safety. This is a scalable business model similar to what is used by companies such as PatientsLikeMe and 23andMe, which also provide a data based product to consumers while tapping into medical research for their business model.

As software our product is feasible to distribute widely. A bottleneck for massive scaling is the capacity for third party microbiome analysis, but we expect by that time DNA sequencers will drop in price and size to become household items.

Our team has worked together for many years delivering products to market in the technology and digital health space. Terje has significant experience designing and developing AI, health and social products. Juliet has extensive cross functional experience across technology, health and law. We work with partners that have expertise in the fields we don’t cover.


Terje Norderhaug: Degree in Computer Science with a minor in Medical Ethics and graduate studies in Systems Design from University of Oslo, Norway; Post-graduate coursework in Predictive Analytics (Data Science) from UCSD; Software developer and entrepreneur experienced in bringing products to market; Founded pioneering social web platform company; Founded computer vision (AI) startup; NSF I-Corps advisor of translational startups;

Juliet Oberding, JD: Practiced law over 25 years with focus on Intellectual Property, Business and Litigation. Experienced in regulatory issues related to digital health and digital therapeutics; NSF I-Corps advisor of translational startups; Stanford MedicineX ePatient scholar;

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