A University of Waterloo research team is leveraging machine learning to accelerate the traditionally slow and costly process of drug development. Led by Dr. Helen Chen, alongside PhD candidate Bing Hu and applied mathematician Dr. Anita Layton, the team has developed a model that analyzes complex, often incomplete pharmaceutical data to predict drug properties, interactions, and how medications behave in the body in terms of efficacy and safety.
By integrating domain knowledge from biology and medicine into their models, they are improving both accuracy and efficiency compared to traditional approaches. The work supports the advancement of personalized medicine and aims to reduce trial-and-error in early-stage research.
The team is also collaborating with partners such as the Princess Margaret Cancer Centre and Yonsei University to expand the model’s applications and enhance global research efforts.
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