LLMs could rewrite how AIs predict reactions and plan syntheses

A new large language model (LLM) named Chemma could redefine AI’s contributions to organic chemistry, offering a faster, smarter approach to reaction prediction and synthesis planning . However, some chemists remain wary, warning that scientists should not ‘unthinkingly’ become dependent on them.

Despite major advances in synthesis – from drug discovery to renewable materials – designing and building new molecules remains a slow, labour-intensive process. Molecular complexity and a vast chemical space make systematic exploration difficult. ‘Designing efficient, selective reactions [is] heavily dependent on expert intuition and trial-and-error,’ says Yanyan Xu at Shanghai Jiao Tong University. A major bottleneck is the need to experimentally test countless conditions to find those that work.