Per- and polyfluoroalkyl substances (PFAS) are man-made contaminants that are found in drinking water and lead to a variety of health impacts, ranging from low birthweight to adverse effects on the immune system to an increased risk of cancer. Although known as “forever chemicals” due to their persistence once they’ve entered the ecosystem and people’s bodies. Understanding the amount of PFAS in a given person’s blood is important for that person, but also for governments and agencies that are trying to set clear guidance on risk levels in their communities. However, PFAS blood monitoring is not readily accessible. The authors, led by Abt’s Meghan Lynch, developed a pharmacokinetic model both for researchers and the general public to predict blood levels based on drinking water exposure, accounting for background exposures. They took what we know from the PFAS literature about two key parameters (half-life and volume of distribution) and used a Bayesian process to makes it easier to incorporate hundreds of datapoints from multiple studies to refine the estimates of those key parameters. These parameters improve our ability to better estimate PFAS blood levels.