WAVES, an algorithm designed to extract menstrual-cycle metrics from physiological signals such as basal body temperature, which oscillates with sex hormones, shows how different parameters change with age and helps determine whether each person maintains a stable individual pattern or personal footprint. A study based on data from 5,674 cycles from 753 women demonstrates through this tool that age is associated with higher temperatures, shorter cycles, and greater irregularity. In addition, several metrics show within-person stability, suggesting they could serve as personalized health markers.

Seven years, almost to the day, after releasing a draft guidance on post-approval pregnancy safety studies, the U.S. FDA is now finalizing it – albeit with a few changes.