AI can help predict whether a patient will respond to specific tuberculosis treatments, paving way for personalized care

Analyzing large datasets with AI can help humanity gain a crucial edge over the the world’s deadliest bacterial infection, which took 1.3 million lives in 2022.’

Tuberculosis typically infects the lungs but can spread to the rest of the body. stockdevil/iStock via Getty Images Plus

By Sriram Chandrasekaran, Associate Professor of Biomedical Engineering, University of Michigan

Tuberculosis is the world’s deadliest bacterial infection. It afflicted over 10 million people and took 1.3 million lives in 2022. These numbers are predicted to increase dramatically because of the spread of multidrug-resistant TB.

Why does one TB patient recover from the infection while another succumbs? And why does one drug work in one patient but not another, even if they have the same disease?

People have been battling TB for millennia. For example, researchers have found Egyptian mummies from 2400 BCE that show signs of TB. While TB infections occur worldwide, the countries with the highest number of multidrug-resistant TB cases are Ukraine, Moldova, Belarus and Russia.