Developing new drugs to treat illnesses has typically been a slow and expensive process. However, a team of researchers at the University of Waterloo uses machine learning to speed up the development time.
The Waterloo research team has created "Imagand," a generative artificial intelligence model that assesses existing information about potential drugs and then suggests their potential properties. Trained on and tested against existing drug data, Imagand successfully predicts important properties of different drugs that have already been independently verified in lab studies, demonstrating the AI's accuracy.
"There's an enormous pool of possible chemicals and proteins to investigate when developing a new drug, which makes it very expensive to do drug discovery because you have to test millions of molecules with thousands of different targets," said Bing Hu, a PhD candidate in Computer Science and the lead author on the research. "We are figuring out ways that AI can make that faster and cheaper."
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