Bringing Big Data to Drug Discovery

twoXAR, Co-Founded by MIT Sloan Alumnus, Uses Machine Learning to Identify Drug Candidates in Minutes

September 28, 2016

Many biopharmaceutical firms talk about the potential of big data to change the drug discovery process, but a Palo Alto, Calif.-based startup co-founded by an MIT Sloan alumnus is doing it—and has completed scientific research studies to prove it.

Founded in 2014, twoXAR (pronounced “two czar”) analyzes large biomedical datasets to find needles in a haystack: the handful of drug candidates out of a drug library of thousands, if not millions, that would most effectively treat a specific disease.

“Leveraging our technology, we should be able to shave years off of the standard drug development process that sometimes takes 15 years and costs billions of dollars,” said Andrew M. Radin, twoXAR co-founder and chief business officer. The company recently completed a preclinical study of candidate drugs to treat rheumatoid arthritis and has since started research on a type of liver cancer known as hepatocellular carcinoma, or HCC, in collaboration with Stanford University.

Read the full article at the MIT Sloan News website