AI Drug Discovery: Hype vs. Reality
So How Is AI Drug Discovery Doing, Really?
A new paper from experts in the field argues that despite the hype, AI has yet to demonstrate meaningful clinical impact in drug discovery. The authors call for a shift from modeling readily available data to tackling the hard problems that could actually improve Phase II success rates. They highlight the challenges of noisy, heterogeneous data and the risk of benchmarks that reward illusion over progress.
The focus of AI in drug discovery must shift from doing what can be done - such as modelling data that is readily available, but that is unlikely to move the needle - to doing what should be done, even if this requires, for example, substantial data generation.