The National Research Foundation (NRF) Singapore will set up a national Health Technologies Consortium (HealthTEC) to facilitate companies to translate research outcomes into products and services that can improve the health and wellness of individuals. The aim is to create novel and personalised healthcare solutions built on the latest science and technologies
The consortium will do this by bringing researchers and companies together to leverage deep tech and big data to develop and eventually provide advanced health and wellness solutions that will benefit Singaporeans. This national consortium will be led by the Institute for Health Innovation & Technology (iHealthtech) at the National University of Singapore (NUS). NRF will set aside funding of $1.5 million over three years to support the activities of the consortium.
The HealthTEC Steering Committee includes members from NRF, Enterprise Singapore, NUS and Nanyang Technological University (NTU), whereas its Technology Management Committee will comprise leading experts from IHLs and the industry.
HealthTEC’s Focus Areas
From lab-on-chips to wearables to smart sensors, health technologies have a strong potential to produce disruptive innovations that can improve the health and wellness of individuals by empowering them with personalised and actionable data and insights.
It is differentiated from medical technologies that typically require clinical trials to prove clinical claims, and stringent approval from regulatory authorities before being made available or administered to patients.
Some examples of health technologies include wearables that track posture and assess sports performance, sensors to monitor comfort and fatigue levels in drivers, or mobile applications that help users to track their caloric intake when they take photos of the food they eat.
HealthTEC will focus on two areas to develop health and wellness solutions: Health sensing technologies and Health analytics and artificial intelligence.
Health sensing technologies refer to innovations to that track and collect health-related data. These could include tactile sensors to detect standing, walking or sitting pressure; imaging technologies to detect fatigue; or molecular diagnostics to collect vital signs of individuals such as glucose level.
Health analytics and artificial intelligence uses predictive modelling and machine learning technologies to make sense of collected data, with the aim of providing insights and suggesting actions that individuals can take, so as to improve their own health and wellness.
