Aqueous and tissue residue‐based interspecies correlation estimation models provide conservative hazard estimates for aromatic compounds. (24th November 2015) - Bejarano, Adriana C.; Barron, Mace G.
Abstract: Interspecies correlation estimation (ICE) models were developed for 30 nonpolar aromatic compounds to allow comparison of prediction accuracy between 2 data compilation approaches. Type 1 models used data combined across studies, and type 2 models used data combined only within studies. Target lipid (TLM) ICE models were also developed using target lipid concentrations of the type 2 model dataset (type 2‐TLM). Analyses were performed to assess model prediction uncertainty introduced by each approach. Most statistically significant models (90%; 266 models total) had mean square errors < 0.27 and adjusted coefficients of determination (adj R 2 ) > 0.59, with the lowest amount of variation in mean square errors noted for type 2‐TLM followed by type 2 models. Cross‐validation success (>0.62) across most models (86% of all models) confirmed the agreement between ICE predicted and observed values. Despite differences in model predictive ability, most predicted values across all 3 ICE model types were within a 2‐fold difference of the observed values. As a result, no statistically significant differences ( p > 0.05) were found between most ICE‐based and empirical species sensitivity distributions (SSDs). In most cases hazard concentrations were within or below the 95% confidence intervals of the direct‐empirical SSD‐based values, regardless of model choice. Interspecies correlation estimation‐based 5th percentile (HC5) values showed a 200‐ to 900‐fold increase as the log K OW increased from 2 to 5.3. Results indicate that ICE models for aromatic compounds provide a statistically based approach for deriving conservative hazard estimates for protecting aquatic life. Environ Toxicol Chem 2016;35:56–64. © 2015 SETAC