The Future of Drug Discovery: AI-Powered Predictions and Virtual Patient Models
In this video interview, Michel van Harten, MD, CEO, myTomorrows, highlights the potential of artificial intelligence in digital twin technology.
In a recent video interview with Applied Clinical Trials, Michel van Harten, MD, CEO, myTomorrows, discussed the integration of artificial intelligence (AI) in clinical trials, highlighting its potential to reduce costs, accelerate timelines, and improve inclusion. Looking forward, advancements with AI are expected to speed up drug discovery, predict drug efficacy, and develop digital twins for personalized treatment simulations, potentially reducing trial risks and costs.
ACT: Looking forward, what are some other ways that you see AI having an impact on drug discovery?
van Harten: In general, it will speed up drug discovery, which is usually a process that lasts for four years and costs billions of dollars. AI is helping, I think, scientists to go through huge datasets to identify promising drug compounds faster than ever before, and it will probably also predict which ones are likely to work, and also in which patient populations they will work, also with the level of precision we've never had before.
I think another thing that is very interesting is that we're also seeing major progress in something called digital twin technology, so that's a virtual replica of a real patient, and these models can simulate how a specific person might respond to a drug or treatment before they even ever tried it, so in the future, this could mean fewer risks and also fewer people needed for early trials.
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