Expanding Our Search for Antibiotics: Encrypted Biology, Ancient Datasets and AI
As seen in Technology Networks

Antimicrobial resistance is one of the most urgent problems facing humanity. Every year, bacterial infections kill five million people globally. By 2050, that number could double. The question isn’t whether we need new antibiotics,  it’s where do we find them?

At the Innovations in Disease Modeling 2025 event, César de la Fuente, Presidential Associate Professor at the University of Pennsylvania, laid out his answer. His lab is using AI to treat biology as an information source. Scanning ancient genomes, extinct organisms and the human proteome itself for antibiotic candidates that evolution has quietly hidden in plain sight.

If AI can accelerate antibiotic discovery by scanning woolly mammoth DNA in the time it would take a traditional lab to run a single experiment, the implications stretch well beyond AMR. Technology Networks covers the full story, from the AI models his team built from scratch to the thorny legal questions.