AI steps into science labs to speed up drug research

OpenAI’s newest AI model, named after DNA pioneer Rosalind Franklin, isn’t built to write poems or plan dinner menus. Instead, it’s trained to dig through mountains of scientific data to help researchers find new medicines faster. Drug development usually takes over a decade, but this tool could cut that time by improving how scientists pick targets and design experiments. The model has been tested on tough science topics like protein folding and gene editing, showing it can spot relevant studies from libraries full of research papers. It’s not the first AI built for science—Google’s AlphaFold already helped win a Nobel Prize in Chemistry for predicting protein shapes. Similar tools from other companies also aim to speed up medical breakthroughs, but not everyone is convinced. Some worry about risks like data bias or even the misuse of AI to engineer dangerous substances.To prevent problems, OpenAI added safeguards and partnered with labs, drugmakers, and tech firms to keep research on track. One big pharma company, Amgen, says combining their expertise with AI could lead to better, faster treatments for patients. Still, questions remain: Can AI be trusted to handle complex biology without errors? Will shortcuts in research lead to overlooked dangers? The answers might decide whether this technology truly transforms medicine or just adds another layer of uncertainty.