Scaling structure-based drug design with machine learning
"In the next 5–10 years future innovation will be a clever blend of FEP and artificial intelligence"
AI will not replace drug discovery scientists, but drug discovery scientists who use AI will replace those who don’t
Comment during EFMC meeting 2018
As progressing a drug molecule from concept to commercialization is a lengthy and costly process, there is a demand for the application of novel technologies to speed up and de-risk the discovery pipeline. Artificial intelligence (AI) and machine learning (ML) approaches are of interest as they offer the ability to expand the chemical ‘search space’ for novel compounds, enable accelerated calculations of complex properties and provide insights into inherently noisy and incomplete information.
Matthew Habgood, Principal Computational Chemistry Developer at Cresset, and I discuss whether and how AI and ML can accelerate delivery of a final drug candidate, while also examining why the above statement isn’t necessarily true.
Read the full article, 'How the AI revolution can accelerate early drug discovery' as published in Drug Target Review.