Integrated QSAR Models to Predict Acute Oral Systemic Toxicity.

Abstract

The ICCVAM Acute Toxicity Workgroup (U.S. Department of Health and Human Services), in collaboration with the U.S. Environmental Protection Agency (U.S. EPA, National Center for Computational Toxicology), coordinated the "Predictive Models for Acute Oral Systemic Toxicity" collaborative project to develop in silico models to predict acute oral systemic toxicity for filling regulatory needs. In this framework, new Quantitative Structure-Activity Relationship (QSAR) models for the prediction of very toxic (LD50 lower than 50 mg/kg) and nontoxic (LD50 greater than or equal to 2,000 mg/kg) endpoints were developed, as described in this study. Models were developed on a large set of chemicals (8992), provided by the project coordinators, considering the five OCED principles for QSAR applicability to regulatory endpoints. A Bayesian consensus approach integrating three different classification QSAR algorithms was applied as modelling method. For both the considered endpoints, the proposed approach demonstrated to be robust and predictive, as determined by a blind validation on a set of external molecules provided in a later stage by the coordinators of the collaborative project. Finally, the integration of predictions obtained for the very toxic and nontoxic endpoints allowed the identification of compounds associated to medium toxicity, as well as the analysis of consistency between the predictions obtained for the two endpoints on the same molecules. Predictions of the proposed consensus approach will be integrated with those originated from models proposed by the participants of the collaborative project to facilitate the regulatory acceptance of in-silico predictions and thus reduce or replace experimental tests for acute toxicity.