Accelerator Grants in Genomic Medicine 2020: “Moving Genomics to Populations”
The McLaughlin Centre is pleased to announce its 10th research funding competition. The competition will be based on invited grant applications passing an initial letter of intent stage. Both steps will go through committee peer-review adjudicated by the Director.
- Letter of Intent (LOI) Deadline: December 6, 2019
- LOI Decision: January 10, 2020
- Application Deadline: March 6, 2020
- Application Decision: April 17, 2020
- Funding Start: May 1st, 2020
- LOI form at: www.mclaughlin.utoronto.ca
Letters of Intent up to two pages long should outline (i) background and rationale, (ii) objectives and activities, (iii) relevance to the McLaughlin Centre mission, (iv) planned deliverables and (v) a brief budget summary. Full grant applications will be a maximum of 10 pages including references.
Priority will be given to applications demonstrating promise for near-term deliverables, potential to seed larger grants, and those involving two or more institutions from the University of Toronto Faculties (and their Departments and Institutes) and the hospitals/research institutes fully affiliated with the University of Toronto (TAHSN).
Successful grants will be awarded for one year with up to $100,000 from the McLaughlin Centre. A requirement is that the McLaughlin Centre investment be equally matched with other funds necessary for the completion of the project
Note: Considering the current funding opportunities in Toronto, if your project involves cancer please contact us in advance
The emphasis in this Call will be Moving Genomics to Populations:
- Building clinical cohort resources (e.g. DNA, RNA), including pilot genome-wide datasets (e.g. whole genome sequence, epigenome, microbiome), and clinical phenotypes, are appropriate;
- Building databases and computational tools to collect and analyze whole genome datasets for health and administrative database linkage. Small leveraged grants are emphasized;
- Development of statistical and computational approaches used in genetic risk score analyses for research and disease prediction modeling. Team-based or linked training grants are emphasized.
Pre-submission enquiries are welcomed to encourage potential applicants to understand the intended scope including matching funds.