The scientist using AI to hunt for antibiotics just about everywhere | MIT Technology Review
Summary
César de la Fuente is leveraging AI to discover new antibiotics by exploring genetic sequences from various organisms, including extinct species, to combat antimicrobial resistance.
Why It Matters
Antimicrobial resistance is a growing global health crisis, leading to millions of deaths annually. De la Fuente's innovative approach using AI to identify new antibiotic candidates could significantly impact public health and drug development, addressing a critical gap in current antibiotic discovery efforts.
Key Takeaways
- Antimicrobial resistance is responsible for over 4 million deaths per year and is projected to worsen.
- César de la Fuente's team uses AI to search for antibiotic peptides in genetic sequences from various organisms, including extinct species.
- The approach aims to create novel antimicrobial compounds that could combat drug-resistant infections.
- De la Fuente has amassed a library of over a million genetic recipes for potential antibiotic candidates.
- His work represents a significant advancement in the intersection of AI and drug discovery.
When he was just a teenager trying to decide what to do with his life, César de la Fuente compiled a list of the world’s biggest problems. He ranked them inversely by how much money governments were spending to solve them. Antimicrobial resistance topped the list. Twenty years on, the problem has not gone away. If anything, it’s gotten worse. Infections caused by bacteria, fungi, and viruses that have evolved ways to evade treatments are now associated with more than 4 million deaths per year, and a recent analysis, published in the Lancet, predicts that number could surge past 8 million by 2050. In a July 2025 essay in Physical Review Letters, de la Fuente, now a bioengineer and computational biologist, and synthetic biologist James Collins warned of a looming “postantibiotic” era in which infections from drug-resistant strains of common bacteria like Escherichia coli or Staphylococcus aureus, which can often still be treated by our current arsenal of medications, become fatal. “The antibiotic discovery pipeline remains perilously thin,” they wrote, “impeded by high development costs, lengthy timelines, and low returns on investment.” But de la Fuente is using artificial intelligence to bring about a different future. His team at the University of Pennsylvania is training AI tools to search genomes far and deep for peptides with antibiotic properties. His vision is to assemble those peptides—molecules made of up to 50 amino acids linked together—into various configurati...