AI Cannot Replace Drug Researchers

The pharmaceutical industry has always been a high-stakes gamble. For every drug that reaches pharmacy shelves, thousands of molecular candidates fall by the wayside, casualties of a discovery process that devours billions of pounds and stretches across decades. The traditional odds are brutally unfavourable: roughly one in 5,000 compounds that enter preclinical testing eventually wins regulatory approval, and the journey typically consumes 10 to 15 years and costs upwards of £2 billion. Now, artificial intelligence promises to rewrite these economics entirely, and the early evidence suggests it might actually deliver. In laboratories from Boston to Shanghai, scientists are watching algorithms design antibodies from scratch, predict protein structures with atomic precision, and compress drug discovery timelines from years into months. These aren't incremental improvements but fundamental shifts in how pharmaceutical science operates, driven by machine learning systems that can process