New research from the University of Canterbury using AI technology could help health professionals provide more effective cancer treatment strategies and save lives.
For the last four years, Associate Professor Alex Gavryushkin from Te Whare Wānanga o Waitaha | University of Canterbury (UC) Biomathematics Research Centre has been developing algorithms to analyse biological data in relation to complex genetic diseases, such as cancer and gout, to help develop treatment strategies based on genetics.
“The classic approach to medicine looks at lots of people with a particular condition to see what treatment works for them. However, there are many diseases, including cancer, which are extremely different from person to person despite identical symptoms, and the same drugs and therapies don’t work,” Associate Professor Gavryushkin says.
“Genomics is the answer to that. We develop and train our algorithms on genomic as well as clinical data to link the individual’s condition to what is known in biology, medicine and clinical trials to come up with actionable recommendations, such as different drug combinations.”
Associate Professor Gavryushkin says the technology would enable health professionals to provide more effective cancer treatment strategies, minimising the chance of treatment-resistant cells to develop, while also making quality care more accessible.
“The worst thing that can happen after treatment is when a population of cells that are resistant to treatment develop. Our work looks at how to prioritise and plan therapeutic approaches in a way that minimises the chance of developing treatment-resistant genotypes by steering the evolution of cancer away from them,” he said.
“If this succeeds, it is effectively providing a precision medicine assistant to the oncologist. We want to make these tools available globally, especially in places where doctors may not have specialised training in genetics, or time to go through all the recent literature. With modern AI technologies, these barriers can be eliminated.”
Associate Professor Gavryushkin is also applying the algorithms to gout, another complex genetic disease. He is specifically looking at big data approaches to indigenous populations, including Māori and Pacifica. Both research projects are in collaboration with other researchers, and industry and clinical experts in Aotearoa New Zealand, Switzerland, Spain and USA.
“The power of algorithms over the last 20 years has been remarkable, yet there are still areas where it is unbelievable that algorithms are not being used.”
“I’m very passionate about using these technologies to make cancer treatment and gout treatment equitable. They come at relatively low cost compared to how deployable they are and how widely the benefits can be applied – so the impact on people’s lives could be significant.”
He said the next stage will focus on engaging with patients, their oncologists, and pathologists – the researchers are looking for participants and clinical collaborators.
Funding to date has been from the Ministry of Business, Innovation and Employment (MBIE) Endeavour Fund, and the Rutherford Discovery Fellowship.