Systematic update to the mammalian relative potency estimate database and development of best estimate toxic equivalency factors for dioxin-like compounds.

The World Health Organization (WHO) assesses potential health risks of dioxin-like compounds using Toxic Equivalency Factors (TEFs). This study systematically updated the relative potency (REP) database underlying the 2005 WHO TEFs and applied advanced methods for quantitative integration of study quality and dose-response. Data obtained from fifty-one publications more than doubled the size of the previous REP database (∼1300 datasets). REP quality and relevance for these data was assessed via application of a consensus-based weighting framework. Using Bayesian dose-response modeling, available data were modeled to produce standardized dose/concentration-response Hill curves. Study quality and REP data were synthesized via Bayesian meta-analysis to integrate dose/concentration-response data, author-calculated REPs and benchmark ratios. The output is a prediction of the most likely relationship between each congener and its reference as model-predicted TEF uncertainty distributions, or the 'best estimate TEF' (BE-TEF). The resulting weighted BE-TEFs were similar to the 2005 TEFs, though provide more information to inform selection of TEF values as well as to provide risk assessors and managers with information needed to quantitatively characterize uncertainty around TEF values. Collectively, these efforts produce an updated REP database and an objective, reproducible approach to support development of TEF values based on all available data.