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۲ݮƵ teams win big in new ‘Omics’ cancer competition

Teams from ۲ݮƵ took honours in four of five research grants in the first-ever competition, earning a share of $1.5 million in funding in projects that combine AI, genomics and cancer
Published: 5 November 2020

Earlier today, a Quebec based consortium of research institutes (Génome Québec, Oncopole and IVADO) announced the winners of their first-ever “Omics Data Against Cancer” competition, and ۲ݮƵ research teams were dominant. In fact, of the five selected teams no less than four of them included professors from ۲ݮƵ.

The new competition is intended to leverage the use of artificial intelligence (AI) in the ‘Omic’ sciences (which refers to the biological sciences that end with -omics, such as genomics, transcriptomics, proteomics, or metabolomics) to achieve breakthroughs in cancer research.

“The results of this competition speak for themselves: ۲ݮƵ is defining the cutting edge of science,” said Martha Crago, Vice-Principal, Research and Innovation. “I congratulate each of the winning teams and commend them for pushing the envelope of our collective knowledge in the fight against cancer.”

The winning teams shared in a $1.5 million pool of funds to support their endeavours over the next two years. The following are the ۲ݮƵ-based projects:

  • Dr. Amin Emad (۲ݮƵ University, Mila) and Dr. Morag Park (Rosalind and Morris Goodman Cancer Research Centre) are developing artificial intelligence models to predict response to drug combinations in poor-outcome cancer patients.
  • Dr. Ian Watson, Dr. Hamed Najafabadi (۲ݮƵ University, Goodman Cancer Research Centre) and Dr. John Stagg (Université de Montréal, CHUM Research Centre) are developing “MELANO-PREDICT,” a clinically applicable algorithm for predicting checkpoint inhibitor response in melanoma.
  • Dr. Jacques Drouin (Université de Montréal, Montréal Clinical Research Institute) and Professor Marc Bellemare (۲ݮƵ University, Mila) are collaborating on decoding the cancer epigenome with novel artificial intelligence discovery tools.
  • Professor Mathieu Blanchette (۲ݮƵ University, School of Computer Science) and his team are working on deciphering mechanisms of epigenetic alterations in cancer using 3D-genomics-informed deep learning.

More details on the winning projects from the Goodman Cancer Research Centre can be found here. For complete results of the competition, visit the Genome Quebec .

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