Client:Â Health Canada
Listing of the client in no way affirms the client's support, sponsorship, or validation in any form of Risk Sciences International or the RSI staff member(s) who conducted this project during their stay with RSI or prior to joining the company. This case study is displayed for informative purposes only to demonstrate the capacity of RSI staff members. This case study reveals no proprietary information or information deemed sensitive.
Validation and Optimization of the Computational Tool for the Microbial Risk Assessment Framework (MRAF)
To support more consistent and quantitative assessments of new micro-organisms under the Canadian Environmental Protection Act, Health Canada's New Substances Program (NSP) sought to refine the tools and processes within its Microbial Risk Assessment Framework (MRAF). The NSP had previously collaborated with RSI to review and modernize the MRAF and develop a supporting computational tool. However, further work was required to validate the tool and ensure it aligned with current program needs and regulatory expectations.
RSI was engaged to validate and optimize the computational tool, with particular focus on integrating new input types, verifying technical fixes, and refining outputs to support robust and efficient risk assessments. Key tasks included assessing the feasibility of incorporating alternative quantity units and additional modelling features, reviewing updates made by the client, and simplifying processes for estimating disease burden metrics such as disability-adjusted life years (DALYs). RSI also provided recommendations on how the tool could better account for genetic modifications, include guiding content for users, and support interpretation of environmental risk scores.
Beyond tool optimization, RSI was tasked with reviewing the revised MRAF to ensure alignment with the tool’s outputs and risk characterization approaches. Feedback included how to integrate computational results into supporting documents used for regulatory decisions and how to streamline these templates to reduce unnecessary content. Where time permitted, the project also explored global sensitivity analysis and the potential for incorporating stochastic modelling approaches. These enhancements aimed to strengthen NSP’s ability to conduct timely, science-based assessments of microbial risks.
Experts related to this case study
More RSI Case Studies
RSI presents a very small selection of case studies to highlight some of its key work.