Tumors with a high mutational burden, such as lung tumors, present a good news-bad news conundrum for targeted therapies. The many mutations in their genomes make finding an actionable driver mutation akin to finding a needle in a haystack, though those many mutations also make it likely that there is a needle in the haystack in the first place. Researchers from the University of Texas Southwestern Medical Center and the South Korean Yonsei University College of Medicine have now developed an analysis method to identify "therapeutic triads" consisting of a target mutation, an enrollment biomarker, and a tool compound effective against the target mutation.