The traditional drug discovery process is notoriously slow and expensive, often taking over a decade and billions of dollars to bring a new drug to market. Machine learning is changing this landscape by dramatically accelerating the identification of promising drug candidates.

AI algorithms can analyze vast chemical libraries, predict how molecules will interact with biological targets, and identify potential side effects before any lab experiments begin. This computational approach can screen millions of compounds in days, a task that would take years using traditional methods.

Recent breakthroughs include AI-designed drugs entering clinical trials and machine learning models that predict protein structures, opening new avenues for drug development. As these technologies mature, we can expect faster development of treatments for currently untreatable diseases.