ADVANCED DIAGNOSTICS & PERSONALISED MEDICINE
Kavli INsD's long-term goal is to democratise and personalise healthcare with ultrasensitive, cost-effective, user-friendly and mobile-connected diagnostic technologies. To do this, our researchers are transforming disease detection by harnessing the mighty power of miniscule nanomaterials. These nanomaterials react with chemicals produced by diseases in the body and cause visible colour changes in urine tests, and tests similar to home pregnancy kits. Recognising the ubiquitous power of the mobile-connected modern world, they are co-developing smartphone platforms which capture and record data from the tests to track the spread and treatment of infectious diseases across communities.
ENGINEERING & EXPLORING THE BIO-MATERIAL INTERFACE
Our researchers at the Kavli design biomaterials that influence the behaviour of cells at the interface of living and non-living matter by tweaking the surface chemistry and texture. These materials have emerging applications in medical implants, vaccines, cell supports, and as instructive three-dimensional environments for tissue regeneration. The team studies the cell-material interface to rationally design materials such as nanoneedles and 3D tissue-engineering scaffolds that cause cells to respond with desirable behaviours. Kavli researchers experiment at the interface between biology and materials science and frequently push the limits of what existing technologies and methods are capable of.
BIOELECTRONICS & REGENERATIVE ENGINEERING
Kavli researchers have a growing portfolio of cutting-edge biomaterials designed to repair tissues, enhance regeneration and deliver drugs to targeted areas of the body. They are advancing novel manufacturing strategies, such as 3D-printing, remote stimulation and cell patterning, to build scaffolds for cells that recreate the complexity of real tissues. Our researchers are also developing new materials for bioelectronic applications and soft robotics.
DIGITAL MEDICINE & BIG DATA
Working with collaborators, our researchers are harnessing the computational power of machine learning and artificial intelligence to enhance understanding of molecules, materials, and processes. Not only can computer simulations verify laboratory observations, but they also prove useful in predicting experimental outcomes, and provide complementary data to experiments. Our researchers work with experts in computer modelling and big data to help screen molecules and systems far faster than is possible by physical experiments, and train computers to help interpret experimental data.
Our work in this area focuses on:
Advanced Diagnostics & Personalised Medicine (Molly Stevens)
Engineering & Exploring the Bio-Material Interface (Molly Stevens)
Bioelectronics & Regenerative Engineering (Molly Stevens)
Digital Medicine & Big Data (Molly Stevens)
