Principal Investigator
Jacques Corbeil
Université Laval – CHU de Québec-Université Laval and an affiliate member of MILA
Co-chercheur
Teodor Veres
National Research Council of Canada
Project of $343,268 over 1 year
- Supported by CQDM through:
Ministère de l’Économie, de l’Innovation et de l’Énergie du Québec (MEIE) - And by co-funding partners:
– Linearis Labs Inc.
– Canada Biomedical Research Fund (CBRF)
The project in detail:
Challenge
The goal of the project is to bridge the gap between generative artificial intelligence in drug discovery and laboratory capabilities to monitor relevant metabolites in health and disease states, in order to improve the efficacy and reduce the toxicity of newly developed drugs.
Solution
The solution lies in organ-on-a-chip (OOC) systems, which offer a powerful platform for biomedical research by recreating functional units of human organs for in vitro testing. OOCs provide key advantages over conventional in vivo preclinical models. They offer physiologically realistic models, high-throughput processing capabilities that enable the use of AI algorithms, lower costs compared to in vivo studies, and real-time quantitative evaluation using metabolomics, proteomics, and imaging. These organ-on-a-chip systems are easy to handle and highly faithful, allowing for better mimicry of human organs. OOCs represent a promising alternative to complement in vivo modelling in preclinical drug and toxicity screening.
Expected Achievements /Impacts
Research teams from the Medical Devices Research Centre at the NRC and the CHU de Québec–Université Laval will accelerate the drug development process and gain better insights into drug toxicity, through an advanced microfluidic-based device designed and built by NRC. The OOCs will be manufactured in Québec and distributed exclusively by Linearis, a Québec-based company, for the benefit of patients. A testing platform will be established and made available to pharmaceutical companies and startups worldwide to test their compounds and facilitate access to funding, supported by robust results that go beyond the limitations of in vivo models.
