Alumni Excellence Award Recipient: Ram Samudrala, Ph.D. ’97

Gazing into the night skies as a boy in Bangalore, India, Ram Samudrala, PhD ’97 pondered the mysteries of the universe. Since then, his curiosity hasn't ceased. It was that same sense of wonder that led him to create a pioneering technique to predict disease treatments – a method that could also lead to the development of new drugs.

In 2010, Samudrala invented a digital platform called CANDO (Computational Analysis of Novel Drug Opportunities) whose function was radical in scope: analyze how every drug interacts with every protein in the body (including drug targets, enzymes, transporters and binding partners).

Traditional drug discovery focuses on single targets: one protein and one disease. Samudrala, a professor of computational biology and bioinformatics at the University at Buffalo, says that this longstanding approach is fundamentally limited. “When you swallow a pill, it doesn’t hit just one target,” he says. “It interacts with potentially thousands of proteins. That’s why drugs have side effects. We don’t really understand the full picture.”

CANDO earned Samudrala an NIH Director’s Pioneer Award, one of the agency’s most prestigious prizes. Since then, CANDO has led to dozens of publications, multiple patents and several startups focused on cancer, addiction, aging and infectious disease. CANDO, Samudrala explains, generates a system-wide “signature” and uses that signature to predict treatments for many diseases at once. But for Samudrala, drug discovery is still only a stepping stone.

“Drugs are how we get funding,” he says. “Understanding life is the real goal.”

That understanding could lay within systems biology, which seeks to understand not only what individual drug molecules look like, but also how the millions of them interact inside living organisms. Proteins don’t operate in isolation. They collide with drugs, metabolites, DNA, RNA, environmental chemicals and each other – across cells, tissues and organs.

That realization led Samudrala to translational bioinformatics: using computational models to understand how small molecules, especially drugs, affect the entire biological system.

The long-term vision is ambitious: full-scale computational models of humans that could simulate how an individual body responds to drugs, environmental chemicals or disease.

In such a future, clinical trials could be performed on virtual populations. Treatments could be personalized before a patient ever takes a pill.

“We’re not there yet,” Samudrala says. “But that’s where this is going.”

His career has spanned atoms to organisms, telescopes to supercomputers, and seemingly abstract tools that now shape medicine. His early work helped lay the groundwork for later advances recognized by the 2024 Nobel Prize in Chemistry.

These days, as when he was a boy, Samudrala still looks up.

An award-winning amateur astrophotographer, he captures deep-space images from his backyard, nebulae spanning distances so vast they defy human comprehension. One of his most famous images, the Flying Bat and Squid Nebulae, required more than 130 hours of exposures. The same impulse connects his hobbies and his science: a desire to see the full picture.

“At every scale, from quantum particles to galaxies, from atoms to organisms, the question is the same: how does complexity emerge?” he says. “From a scientist’s point of view, it’s a great time to be alive.”