Addressing gaps in drug development with an open drug discovery network
The Government of Canada has made a $49 million investment through its Strategic Innovation Fund (SIF) to support the work of Conscience, a Toronto-based not-for-profit and pan-Canadian collaboration that will prioritize open science drug discovery and development of treatments.
The award was a collaborative win, representing the close work of the Structural Genomics Consortium (SGC), the Viral Interruptions Medicines Initiative (VIMI) and U of T’s Office of Institutional Strategic Initiatives, who together crafted the SIF proposal for an open science drug discovery network (now Conscience) to address tensions in the pharmaceuticals market.
Traditionally, the pharmaceutical industry avoids investing in the development of drugs for diseases with relatively small patient populations or rare conditions. If a drug is developed for these small populations, it is often cost prohibitive for patients. This model limits both research progress and access to life-saving medications, particularly in areas of traditional market failures such as antivirals for pandemic preparedness, medicines for antimicrobial resistance and for rare and pediatric diseases.
Partnering with and pooling resources from non-profits, academia, including researchers at U of T, and industry, Conscience will address both these limitations by focusing on an open science model that emphasizes a collaborative approach and sharing of data with partners and the public. This model will eliminate the silo effect of the current proprietary research and development process, where different groups compete separately to develop drugs for the same conditions, amplifying the costs, and failing to capture potential synergies between research groups.
A large part of the experimental work will take place at U of T, where the SGC’s labs at Temerty Faculty of Medicine will test AI predictions as part of the CACHE challenge. This initiative enables researchers from anywhere in the world to compete using their AI algorithms to predict structures of small molecules or “hits” that could bind a target protein linked to a disease. The first of these competitions focused on a protein linked to Parkinson’s disease. Other CACHE challenges are pursuing hits for targets linked to diseases like COVID-19 and cancer.
In addition to the $49 million SIF award, Conscience has secured $57 million in funding from industry, grants and philanthropic support that will allow a rollout of the project over five years.