A multi-tiered hierarchical Bayesian approach to derive toxic equivalency factors for dioxin-like compounds.

ABSTRACT: In 2005, the World Health Organization (WHO) re-evaluated Toxic Equivalency factors (TEFs) developed for dioxin-like compounds believed to act through the Ah receptor based on an updated database of relative estimated potency (REP)(REP₂₀₀₄ database). This re-evalution identified the need to develop a consistent approach for dose-response modeling. Further, the WHO Panel discussed the significant heterogeneity of experimental datasets and dataset quality underlying the REPs in the database. There is a critical need to develop a quantitative, and quality weighted approach to characterize the TEF for each congener. To address this, a multi-tiered approach that combines Bayesian dose-response fitting and meta-regression with a machine learning model to predict REPS' quality categori

SUBMITTER: Ring C 

PROVIDER: S-EPMC11110530 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature