Machine learning in drug development - Edison Group

Biotech buzzwords do not come much bigger than those of artificial intelligence (AI) and machine learning (ML). With the promise of expediting routes to market and reducing costs, such platforms may very well find themselves cemented as critical components in future drug development toolboxes. The application of ML approaches in the pharma industry has now matured to a stage where the first purely ML generated candidates have entered clinical trials. However, we are still a way off from using solely ML to uncover completely new disease mechanisms of action or targets, which many would consider as the holy grail of applications. Leading the charge towards this ambition are focused biotechs leveraging ML that are not only applying their platforms to bolster internal pipelines but striking deals with big pharma, which are likely to be the main clients, utilising ML to boost their own portfolios. The pharma industry continues to evolve and, based on current macro pressures, we are likely to see different approaches to increase efficiency and expedite drug discovery.