Gazing at a computer screen at Stanford University, science journalist Lisa M. Krieger was mystified by the colorful constellation of words and symbols.
But this cryptic code—a carefully crafted AI algorithm—could be life-saving. Powerful computers are quickly sifting through tens of thousands of chemical structures to help find and build the "next generation" of novel antibiotics to combat drug-resistant microbes. To be sure, AI is unsettling in many aspects of modern life. But it's also enormously helpful, turning drug discovery into a mere statistics problem. This work is essential, because it's been decades since we discovered a new class of antibiotics. And we're currently losing the evolutionary arms race with microbes, as our bodies are turning into incubators for the world’s next supercharged bacteria.
This multimedia project was built after extensive interviews with scientists at Stanford University, the University of California, Massachusetts Institute of Technology (MIT), University of Pennsylvania, and Canada's McMaster University. Krieger traveled to India to meet a young woman who had recovered from a highly resistant and dangerous form of tuberculosis, as well as a public health expert who leads India's antimicrobial campaign. She visited the California home of a mother who barely survived infection with drug-resistant MRSA.
Working with The Chronicle's graphics team, Krieger conceived of an interactive project that explains how AI helps find new molecules to build novel antibiotics and how microbes develop resistance. A historical timeline of the nation's faltering search for new antibiotics, and videos and photos of the patients complete this project, funded by The Pulitzer Center and published in the San Francisco Chronicle.
