Supercharging Drug Discovery

The CANDO platform (short for Computational Analysis of Novel Drug Opportunities) is a game-changer for drug discovery, making it many times faster and less expensive without sacrificing safety or efficacy.

One of the first projects supported by Empire AI—a $500 million consortium of public and private universities in New York State that is establishing one of the world’s most powerful academic supercomputing centers—CANDO is capable of identifying potential new drugs for almost any disorder. As a result, it has already prompted several biotech startups, which are using the platform to develop treatments for everything from non-small cell lung cancer to aging.

UB researchers Ram Samudrala and Zackary M. Falls, the brains behind the platform, explain what CANDO is, how it works and what it can do.

Samudrala: CANDO simulates how thousands of compounds interact with the human body at once—like running millions of experiments in seconds. Most drug discovery methods focus narrowly—one drug, one protein, one disease. CANDO looks at the big picture: how every drug interacts with every protein in the body and how these complex patterns relate to health and disease. This “systems-level” view helps us understand not just what works, but why it works and what else might work even better.

Samudrala: Traditional drug discovery can take over a decade to produce results. We wanted a smarter, faster way—so we created a platform that looks at how compounds affect the body as a whole, not just one protein. It was born out of the need for a system that leverages the power of computation to explore the vast universe of chemical and biological interactions.

Samudrala: AI is at the heart of CANDO. We use machine learning to analyze huge datasets of drug-protein interactions, predict new uses for existing drugs and design new ones with optimal properties. Think of AI in CANDO as the engine that sifts through the noise to find hidden patterns and connections that no human could easily spot. 

Falls: The evolution of CANDO will integrate patient-level clinical and biological data. This will push CANDO toward precision medicine in a way that we will be able to tailor treatments or identify side effects that are unique to subgroups of people based on specific mutations, expression levels or other personalized features. The ability to assess if a newly designed drug would work better or worse for any given cohort of patients and identify potential side effects and toxicity prior to the drug entering clinical trials will save time, money and patient lives.