Researchers are using artificial intelligence (AI) in patients with advanced bowel cancer to develop more targeted treatments and improve outcomes.
The team from the University of Leeds were able to use AI-enhanced algorithms to look at the levels of two proteins, known as AREG and EREG, in a patient.
These proteins are produced by some colorectal cancers and identifying the amount some patients have can help doctors determine the best possible treatments.
This is particular for a treatment which inhibits a different protein involved in cancer cell growth, known as EGFR.
The AI allowed researchers to demonstrate that patients with high levels of these proteins would benefit more from this treatment, while those with low levels would not.
The scientists examined samples from a previous trial funded by Cancer Research UK with the findings being timely as it coincides with Bowel Cancer Awareness Month.
The study’s lead author, Christopher Williams, said: “As more treatment options become available for advanced colorectal cancer, it is becoming increasingly difficult for patients and their doctors to choose the treatment that’s right for them.
“This test will help patients navigate this decision-making process more easily.”
AI is making waves in terms of developing new cancer treatments, as Health Tech World recently reported; with a new collaboration between Intelligent OMICS, Arctoris and Medicines Discovery Catapult.
The deal is set to apply AI to help discover new disease drivers and candidate drugs to treat lung cancer.
Machine learning was also used to predict the risk of nephrotoxicity in testicular cancer patients – the most common form of cancer in young men.
The University of Leeds collaborated with researchers at Roche Diagnostics for the study, which contributed to its funding, alongside Innovate UK and Yorkshire Cancer Research. It is also part of a programme of work being conducted by the National Pathology Imaging Co-operative.
The report’s senior author, Kandavel Shanmugam, said: “As increasing numbers of complex tests are developed to target the right cancer treatments to the right patients, developing streamlined methods for delivering test results will be essential to improve cancer care.
“By using artificial intelligence to semi-automate the test process, we anticipate it may be easier for results to be delivered to patients faster to better influence treatment decisions.”