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Drs. R. David Andrew and Neil Renwick awarded funding from the CRCC

Drs. R. David Andrew and Neil Renwick awarded funding from the CRCC

This story was originally published in the Queen's Gazette

Two research projects, in the Faculty of Health Sciences have received funding from the New Frontiers in Research Fund’s (NFRF) 2020 Exploration competition, a program that encourages scholars to take risks, and that fosters discoveries and innovations that could have significant impacts on our world. The NFRF is an initiative created by the Canada Research Coordinating Committee. Its Exploration competition supports research that defies current paradigms, bridges disciplines, or tackles fundamental problems from new perspectives.

Drs. R. David Andrew and Neil Renwick are the FHS researchers leading the projects. They will receive $500,000 ($250,000 per project) from the fund to advance interdisciplinary projects with multiple partners and collaborators. Nationally, the NFRF competition will provide $14.5 million in grants to researchers across Canada, funding 117 projects.

R. David Andrew (Biomedical and Molecular Sciences) is investigating the molecular mechanisms that lead to electrical failure and constriction of blood vessels, a process called spreading depolarization, caused by brain injury. By identifying these mechanisms, the research collaborators will challenge previous knowledge about brain injury therapy and treatments, and propose a method that may prevent loss of brain cells by blocking spreading depolarization, effectively reducing brain damage.

Tumours that arise throughout the body called neuroendocrine neoplasms (NENs) cause metastatic disease in up to 50 per cent of patients, giving those diagnosed months to years to survive. However, the molecular basis of highly variable clinical outcomes is poorly understood. Neil Renwick (Pathology and Molecular Medicine), Kathrin Tyryshkin (School of Computing) and collaborators have proposed a radical new way to investigate NENs. The researchers propose using graph neural network models, typically used in computer science, to investigate the gene networks that drive or mediate tumor aggressiveness. The understanding of these molecular social networks may improve accurate knowledge of tumour behaviour and even treatment response, improving NEN clinical outcomes.

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