ReviveMed, a Massachusetts Institute of Technology (MIT) spinout, is using artificial intelligence (AI) to unlock the power of metabolomics to discover new therapies to treat diseases. Metabolomics is the large-scale study of small molecules like glucose or cholesterol produced by cellular activity. ReviveMed’s platform could help pharmaceutical companies redesign existing drugs or develop new drugs to help patients suffering from disease.
The Cambridge, MA-based company recently raised funding to help further develop its AI solution, closing an oversubscribed seed round of $1.5 million. Rivas Capital led the round, which also included participation from several institutional investors including TechU, Team Builder Ventures, and WorldQuant Ventures. The funding will go toward obtaining additional metabolomics data for patients.
“If you want genomic sequencing or RNA data, there are lots of databases available,” Leila Pirhaji, founder and CEO of ReviveMed, told MD+DI. “However, that’s not the case for metabolomics data. We’re actually spending some of our funding [from the seed round] to collect data from patients and controls.”
Pirhaji, who formed ReviveMed while in in the midst of obtaining her PhD, said the company will first target non-alcohol fatty liver disease, which currently impacts more than 30% of people in the U.S. and 10% of those in the U.K. If left untreated, the disease can lead to cirrhosis and liver failure. The prevalence of non-alcohol fatty liver disease is expected to increase, driven by rising levels of obesity and representing a significant area of unmet need in global healthcare.
Pirhaji said fatty liver disease “was a good fit” for ReviveMed. She added that the MIT spinout would eventually focus on other metabolic diseases.
Riding the AI Wave
ReviveMed is one of a growing number of companies embracing artificial intelligence to make an impact in healthcare. Through the use of algorithms and machine learning firms in healthcare are able to cut through the haze of big data and come up with meaningful solutions.
Key ways AI is used in healthcare is pairing it with structured exercises in reading patient data and medical images to train machines to detect abnormalities. Algorithms are also being used to sift through vast amounts of medical literature to inform treatment decisions where it would be too onerous a task to have a human read through the same journals.
“I can see that the industry has changed since working to build my company,” Pirhaji said. “It’s definitely a good time to be a part of this movement and part of this exciting new era.”