John Wiley & Sons, Ltd.

Aqueous and tissue residue‐based interspecies correlation estimation models provide conservative hazard estimates for aromatic compounds

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Interspecies correlation estimation (ICE) models were developed for 30 nonpolar aromatic compounds to allow comparison of prediction accuracy between two data compilation approaches. Type1 models used data combined across studies and Type2 models used data combined only within studies. Target lipid (TLM) ICE models were also developed using target lipid concentrations of the Type2 model dataset (Type2‐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 (MSE) <0.27, and adjusted coefficients of determination (adj‐R2) >0.59, with the lowest amount of variation in MSEs noted for Type2‐TLM followed by Type2 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 three 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 (HC) were within or below the 95% confidence intervals of the direct‐empirical SSD‐based values, regardless of model choice. ICE‐based HC5 values showed a 200 to 900 fold increase as the Log KOW 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. This article is protected by copyright. All rights reserved

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