Inflammatory bowel disease (IBD) is an umbrella term for progressive immune disorders causing chronic inflammation within the gastrointestinal tract with no cure. Conventional treatments focus on dampening inflammation using immunosuppressive medications such as corticosteroids, immunomodulators, biological and small molecule therapies. Treatment with these drugs however carry significant risks including an increased risk of infection, skin cancer and lymphoma. Non-response or loss of response to treatment over time are also common. It is widely agreed that the ability to timely and accurately monitor inflammation patterns and ideally, also predict disease relapses and flare-ups in patients will significantly improve the efficacy of therapeutic interventions, help managing of treatment regimes more easily and allow treatments to be delivered in a 'closed-loop approach'.

We have recently conceived a revolutionary engineering solution termed 'AutoGut', a novel implantable biosensor device that will measure real-time levels of intestinal inflammation to inform accurate diagnosis and allow closed-loop treatment. This innovative device is expected to deliver a paradigm shift in IBD therapies, eliminating the need for any 'guesswork' in treatment approaches by providing individualised patterns of inflammation during disease progression and self-regulated treatment.

School

Biomedical Engineering

Research Area

Sensors | Electrochemistry | Aptamers | Nanoparticles | Inflammatory bowel disease | Cytokines

This is an industry-funded and driven project that has strong translational potential. The candidate will work within a diverse team with access to world-class equipment for fabrication and characterisation of sensors. This project will mostly suit a student undertaking electrical or chemical engineering.

The project undertaken by the student will involve tackling one of the most fundamental and crucial challenges in developing a robust implantable sensor - that is of high stability and selectivity. Present sensors are found to exhibit significant signal loss over time and with continuous measurements. The selected student will work on methods to minimise or even eliminate sensor degradation and test stability both ex vivo and in vivo.

Associate Professor in Bionics and Neuromodulation
View Profile
Empty profile image
Research Assistant

  

Send Email