Smart Patch May Reduce Diabetes Risk

It may seem that all health and medical tech R&D in the world right now is focused on COVID-19, but groups dedicated to other specific diseases and medical conditions are still hard at work. Major chronic diseases threaten the health, quality of life, and finances of tens of millions of people worldwide. The prevalence of type 2 diabetes (T2D) continues to grow throughout the world, according to the World Health Organization (WHO). Diabetes is not only a “first world” disease. The most recent WHO diabetes report noted that approximately 422 million people worldwide have diabetes and 1.6 million people die from the disease each year. The greatest growth in the past three decades has occurred in low- and middle-income countries. An Australian collaboration between RMIT University , Griffith University , manufacturer Romar Engineering , and Melbourne-based startup Nutromics announced that they are developing a smart patch to combat the growth of diabetes and other chronic diseases. The wearable patch is intended help people reduce their risk of lifestyle-related chronic diseases — especially diabetes — by delivering precision data to guide people in creating personalized diets to suit their specific bodies and activities. According to Professor Sharath Sriram, Research Co-Director of RMIT’s  Functional Materials and Microsystems Research Group , the smart patch will combine complex sensors capable of monitoring health at the molecular level. The technology targets precise biomarkers that drive lifestyle-related diseases, Sriram said in an RMIT release. The research team’s work is supported by the Innovative Manufacturing Cooperative Research Centre (IMCRC), a group that champions Suatralian manufacturing innovation. IMRC funding and in-kind contributions from the various entities in the group currently total $6.9 million Australian (approximately $4.5 million U.S.).

Note that this project has a high level of uncertainty. At this point, the group has not created a functioning prototype, and the information that they have released is vague about the biomarkers that will be tracked or how the sensors will measure them. Then there’s also the question of how this raw data will be interpreted into actionable information, and what the basis will be for that transformation. All the same, it is an ambitious effort that has the potential to have an impact on the concept of personalized health based on the quantified self.