Supporting Faster Discovery of New Medicines

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Ontario Investing in Genomics Research and Open Science

Ontario is investing in medical research and open science to help speed up the development of new treatments for diseases and conditions such as cancer, diabetes, obesity and rare diseases.

Reza Moridi, Minister of Research, Innovation and Science, was joined by Kirsty Duncan, Minister of Science, to announce support for the Structural Genomics Consortium (SGC) at the Children’s Hospital of Eastern Ontario (CHEO) Research Institute in Ottawa today.

The SGC is a public-private partnership based on the principle of open science — making research data open and accessible to researchers everywhere, to speed up the discovery of new medicines. The SGC also helps Ontario attract pharmaceutical investment, build a stronger commercialization pipeline for new treatments and create and retain high quality jobs.

Supporting research and innovation is part of our plan to create jobs, grow our economy and help people in their everyday lives.

Quick Facts

  • Ontario is investing $5 million over five years in Phase IV of the SGC’s scientific program. This funding will support the SGC-Ontario Target Discovery Network, an initiative that is expected to lead to 15 new potential drug targets.
  • Ontario has invested more than $52 million in the SGC since the consortium was launched.
  • CARE for RARE, a multi-country project led by researchers at CHEO and focused on finding treatments for rare diseases, is an SGC collaborator.
  • The SGC was created in 2004 by the Wellcome Trust in the United Kingdom. The Chief Executive Officer of SGC is Aled Edwards, a world-leading expert in proteomics and structural genomics research, and a professor at the University of Toronto.
  • Genomics is the study of the entire set of genes found in living things, including humans, plants, animals and even viruses to better understand how they work and what happens when certain genes interact with each other and the environment. Structural genomics aims to identify the three-dimensional structure of proteins, knowledge which could be used to manipulate genes and DNA.

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