Immunotherapy is a powerful new way to treat cancer, harnessing the body’s natural defences to find and kill cancer cells.
By applying machine learning, researchers at the Cheriton School of Computer Science are working to strengthen this mechanism, making it possible to develop personalized cancer-fighting drugs.
“Every patient is different, and every cancer is different — so cancer treatment shouldn’t be the same for all,” says Ming Li, a University Professor at the Cheriton School of Computer Science. “Treatment should be tailored to the patient, and that’s what our machine-learning model allows us to do.”
Immunotherapy is quickly becoming a fourth option in cancer treatment, alongside surgery, chemotherapy and radiotherapy, says Professor Li, who holds the Canada Research Chair in Bioinformatics. He says AI tools make it possible to target the disease in a more precise and even personalized way.
Cancer is a disease of uncontrolled cell growth and regulation, caused by mutations to the genes that control cell division, growth and differentiation. The body’s immune system protects against cancer through T-cells. By applying machine learning, Professor Li’s team identifies specific treatments to enhance those T-cells in individual patients.
Ming Li is a University Professor at the Cheriton School of Computer Science. He is known for his fundamental contributions to Kolmogorov complexity, bioinformatics, machine learning theory, and analysis of algorithms.
- Read the full article on the Globe and Mail: AI-assisted interventions
- Please also see Using machine learning to develop personalized cancer vaccines and Fighting cancer with code
