How an AI solution can design new tuberculosis drug regimens

By | November 26, 2019
FacebooktwitterredditlinkedinmailFacebooktwitterredditlinkedinmail0
white mortar and pestle on black BG with ground up pills
(stevepb/pixabay)

With a shortage of new tuberculosis drugs in the pipeline, a software tool from U-M can predict how current drugs can be combined in new ways to create more effective treatments. Dubbed INDIGO (INferring Drug Interactions using chemoGenomics and Orthology) the application can also identify the genes that control these drug responses.

“This could replace our traditional trial-and-error system for drug development that is comparatively slow and expensive,” said Sriram Chandrasekaran, U-M assistant professor of biomedical engineering, who leads the research.

Tuberculosis kills 1.8 million people each year and is the world’s deadliest bacterial infection. At the same time, multidrug resistant strains are rapidly spreading. Because new drugs are in short supply, INDIGO’s outside-the-box approach represents a faster way of finding them.