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.
Traditionally, bringing a successful drug candidate to market can cost between US$2 billion and US$3 billion and take over a decade to complete. Generative AI is posed to transform drug discovery by harnessing large amounts of drug data across diverse areas.
Read the full article from Waterloo News to learn more.