Diagram of AI-driven antibiotic discovery

Antibiotic identified by AI

Computational approaches are emerging as powerful tools for the discovery of antibiotics. A study now uses machine learning to discover abaucin, a potent antibiotic that targets the bacterial pathogen Acinetobacter baumannii. Learn more
Image of acinetobacter baumannii

Using AI, scientists find a drug that could combat drug-resistant infections

The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings. Learn more
Group of high school students posing for a group photo with MIT President Emerita Susan Hockfield

How to help high schoolers prepare for the rise of artificial intelligence

A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds. Learn more

Generative AI Imagines New Protein Structures

“FrameDiff” is a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy. Learn more

Artificial intelligence model finds potential drug molecules a thousand times faster

The entirety of the known universe is teeming with an infinite number of molecules. But what fraction of these molecules have potential drug-like traits that can be used to develop life-saving drug treatments? Millions? Billions? Trillions? The answer: novemdecillion, or 10^60. This gargantuan number prolongs the drug development process for fast-spreading diseases like Covid-19 because it is far beyond what existing drug design models can compute. To put it into perspective, the Milky Way has about 100 billion, or 10^11, stars. Learn more