Photo of Leila Pirhaji

Biotechnology & medicine

Leila Pirhaji

She developed an AI-based system that can identify more small molecules in a patient’s body, faster than ever before.

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Leila Pirhaji built an AI-based tool for measuring tiny molecules in the body called metabolites, and her work could help us better detect and treat diseases. “There are 100,000 metabolites in the body,” she says. “They are involved in our metabolism and are downstream from DNA, so they show the effects of both our genes and lifestyle.” Such metabolites include everything from blood sugars and cholesterol to obscure molecules that appear in significant numbers only when someone is sick.

The problem is that measuring and identifying metabolites is expensive and time consuming, and fewer than 5% of metabolites in a patient can be identified using common technologies.

So Pirhaji developed a platform that uses machine learning to do it much more quickly. First she built a huge database of all known information about existing metabolites and how they interact with various proteins and other molecules. Then her team collected tissue and blood samples from patients with known diseases, and measured the metabolites.

Her platform was able to analyze the data, understand the complex connections between diseases and metabolites, and use this information to discover new drugs. When she tested it in a mouse with Huntington’s disease during her PhD at MIT, her team learned new mechanisms for the disease and found new potential ways of treating it. 

As CEO of ReviveMed, Pirhaji is focusing on liver, immune, inflammatory, and other diseases. Using her platform, the startup partners with major pharmaceutical companies to match existing medicines to new treatments and find  new targets for future drugs.