A Tiered, Bayesian Approach to Estimating Population Variability for Regulatory Decision-Making

377 Received August 25, 2016; Accepted December 9, 2016; Epub December 13, 2016; doi:10.14573/altex.1608251 into account the genetic diversity within populations, overlooking uncertainties about how genetic variability might interact with environmental exposures to affect risk (Rusyn et al., 2010). As a result, while characterization of human variability in susceptibility to chemical toxicity is a critical issue in toxicology, public health, and risk assessment, it is usually addressed by a generic 10-fold safety/uncertainty factor despite encouragement to generate and use chemical-specific data (WHO/IPCS, 2005). The recent use of population-based animal in vivo (Rusyn et al., 2010; Chiu et al., 2014) and human in vitro (Abdo et al., 2015a,b; Eduati et al., 2015; Lock et al., 2012) experimental models that incorporate genetic diversity provides an opportunity to more precisely estimate human variability and increase confidence in decision-making. The technical feasibility and the scientific and practical value of large-scale in vitro population-based experimental approaches to more accurately estimate human