The results from the PATHFINDER 2 study, published in Nature Medicine, show the efficacy of GRAIL’s Galleri test, which uses a machine-learning algorithm to examine chemical patterns that distinguish cell-free DNA originating from healthy cells versus cancerous cells.
The findings arrive at a pivotal moment for the field of multi-cancer early detection. On Wednesday, Nima Nabavizadeh, M.D., lead author of the study and professor of radiation medicine and director of early detection clinical research at the OHSU Knight Cancer Institute, is scheduled to present the results before a Food and Drug Administration advisory committee reviewing evidence supporting potential approval of the Galleri test.