Researchers at the University of Pennsylvania have developed an AI model, AMP-Diffusion, that successfully designs new antibiotic candidates from scratch. Some of these candidates have even been found to match the effectiveness of FDA-approved drugs in animal tests without side effects. While AI has already been used to identify potential antibiotics from existing data, this work marks a shift: using generative AI to create new drug candidates entirely from scratch. The model behind this work, AMP-Diffusion, builds on a type of generative AI known as a diffusion model—technology more commonly used to generate realistic images. Unlike traditional models that attempt to build biological sequences from scratch, AMP-Diffusion incorporates ESM-2, a protein language model developed by Meta and trained on millions of natural sequences.