Artificial Intelligence can design new TB drug regimens

With a shortage of new tuberculosis drugs in the pipeline, a software tool from the University of Michigan can predict how current drugs, including unlikely candidates, can be combined in new ways to create more effective treatments – leading to the design of TB drug regimens. Sriram Chandrasekaran, U-M assistant professor of biomedical engineering, who leads the research, said: "This could replace our traditional trial-and-error system for drug development that is comparatively slow and expensive. Dubbed INDIGO, short for INferring Drug Interactions using chemoGenomics and Orthology, the software tool has shown that the potency of tuberculosis drugs can be amplified when they are teamed with antipsychotics or antimalarials. Shuyi Ma, a research scientist at the University of Washington and a first author of the study, said: "This tool can accurately predict the activity of drug combinations, including synergy, where the activity of the combination is greater than the sum of the individual drugs. "It also accurately predicts antagonism between drugs, where the activity of the combination is lesser. In addition, it also identifies the genes that control these drug responses."