When a 7 year old Perth girl with persistent, undiagnosable tummy problems – thought to be IBS – came to Nobel Laureate Professor Barry Marshall for help, his team thought  “Are we really going to subject a 7-year old to a colonoscopy?” Their answer “to come up with a better way,” led them to create Noisy Guts – the world’s first AI Technology model to accurately (91%) detect IBS. 

Associate Director for UWA’s Marshall Centre for Infectious Disease – Dr Josephine Muir – is no stranger to breakthrough research. She helped shape the research agenda for Nobel Laureate in Physiology or Medicine, Professor Barry Marshall. 

So, when her team was confronted with a challenge for a better solution to diagnose Irritable Bowel Syndrome (IBS), Dr Muir jumped right in.

About IBS

“IBS is a chronic and debilitating gut disorder which affects up to 1 in 5 Australians,” explained Dr Muir.

“Despite the size of the problem, there is currently no test which can positively diagnose IBS. Most GPs diagnose IBS through a process of exclusion – often using a symptom based questionnaire that’s lengthy and unreliable – and then refer patients for a colonoscopy to rule out all other conditions.”

“This process is of course costly, uncomfortable, carries risks and lengthy. It takes on average 4 years and more than $5,000 out-of-pocket to achieve an elusive IBS diagnosis.”

Developing Noisy Guts – from blue sky idea to prototype 

In trying to find a non-invasive and accurate diagnostic test for this intrusive disease, Dr Muir with her colleague and co-founder, Dr Mary Webberley, was inspired by a blue-sky idea by Professor Barry Marshall. 

“In 2014, Professor Marshall attended a pitchfest where one of the finalists showcased an acoustic sensing technology that could detect the tiny sounds of munching termites,” said Dr Muir. 

“The idea percolated and we thought, what if we could apply this same technology to the human gut?”

That was the beginning of Noisy Guts – a wearable acoustic belt which listens, records and analyses patients’ gut noises, which has been tested to diagnose IBS with 91% accuracy! 

“Noisy Guts use artificial intelligence to decode gut noises that non-invasively and accurately diagnose and monitor common gut disorders,” explained Dr Muir.

“Using machine learning, we’ve correlated sound features related to the motility and activity cycles of the gut to specific gut disorders associated with four different symptoms.”

“We then turn this technology into two products – a diagnostic test for IBS and a fitbit that helps monitor gut symptoms. We are the first in the world to generate a model of bowel sound generation.” 

The response to Noisy Guts’ patented, published and piloted prototype has been overwhelming in all sectors.

 

Winning the WAITTA INCITE Awards 2019

Noisy Guts received an initial $1 Million philanthropic funding and has recently won two Awards from the State’s most prestigious Technology event – the WAITTA INCITE Awards – in the categories of Research & Innovation Project of the Year and Most Innovative Enabler in Healthcare. 

The award wins have also caught the interest of a private equity investor, which, if successful, will allow Dr Muir and her team to undertake the development and clinical trial needed to register a regulatory compliant device with the Therapeutic Goods Administration. 

This is the ultimate step in translating their research into a market-ready product.

 

Next steps

“Noisy Guts is changing the landscape of medical diagnosis and treatment when it comes to IBS, with the potential to remove the millennia old practice of listening to gut noises via stethoscopes,” said Dr Muir. 

“Many of us strongly believe in the ability of Noisy Guts to revolutionise the way we detect and manage IBS.” 

“I’ve left my full time role at UWA to establish Noisy Guts Pty Ltd, and together with Dr Webberley, I am determined to raise the $1.5 Million funding required to share our technology and help millions globally who suffer from IBS and gut issues.” 

Further information on Noisy Guts: http://www.noisyguts.net