Drug development is an arduous process that costs billions of dollars and can last for years or decades. Now, an interdisciplinary team of researchers at the University of Waterloo are using machine learning to dramatically increase the speed of drug development.

​“We have a lot of existing data across a broad spectrum of medical domains, but it’s extremely complex, and often not as complete or extensive as we would like,” explains Dr. Helen Chen, professor of practice in Public Health Science​s​.​​​ ​

​​Chen teamed up with Bing Hu, a PhD candidate in Computer Science, to build a machine learning model that can analyze and synthesize large amounts of pharmaceutical research data and predict a drug’s properties and interac​t​i​​​​​o​​​n​s​​​.

​The research team’s collaborative work isn’t limited to campus. They’re also collaborating with medical researchers at the Princess Margaret Cancer Centre to best understand how to use their new tech strate​g​i​​​​cally.

“AI is powerful and exciting, but we need to focus on using it to build tools that will actually benefit people,” Hu says. “That development needs to be a collaborative process where you work with experts to create the tools they need to make the next world-changing breakthrough.”