Development of a list of reference chemicals for evaluating alternative methods to in vivo fish bioaccumulation tests

Integrated Framework for Identifying Toxic Transformation Products in Complex Environmental Mixtures

Complex environmental mixtures consist of hundreds to thousands of unknown and unregulated organic compounds that may have toxicological relevance, including transformation products (TPs) of anthropogenic organic pollutants. Non-targeted analysis and suspect screening analysis offer analytical approaches for potentially identifying these toxic transformation products. However, additional tools and strategies are needed in order to reduce the number of chemicals of interest and focus analytical efforts on chemicals that may pose risks to humans and the environment. This brief review highlights recent developments in this field and suggests an integrated framework that incorporates complementary instrumental techniques, computational chemistry, and toxicity analysis, for prioritizing and identifying toxic TPs in the environment.

A tiered assessment strategy for more effective evaluation of bioaccumulation of chemicals in fish

There is currently limited guidance available for regulators and risk assessors on how to use data from non-guideline methods when assessing the bioaccumulation potential of a chemical. Furthermore, bioaccumulation assessments can be more subjective than they need to be due to the lack of a guidance framework on how to use/include the range of information that may be available for a substance. Under some circumstances, in silico, in vitro and/or in vivo non-test guideline data may be sufficient to classify whether a substance is bioaccumulative without the need for further animal testing. Classifying the bioaccumulative potential of a substance is especially difficult when the bioconcentration factor (BCF) is close to the threshold for defining it as bioaccumulative/very bioaccumulative (B/vB), and a more structured process is required to reduce uncertainty in the BCF estimates. In these situations, in silico and in vitro data can, and should, be used to provide greater confidence in classifying these substances. To aid future evaluations of bioaccumulation data, a proposed tiered assessment strategy is presented incorporating all available data on the bioaccumulative properties of a substance. In addition, a revised scheme is recommended for improving the classification of the bioaccumulative potential of a substance.

Comparison between bioconcentration factor (BCF) data provided by industry to the European Chemicals Agency (ECHA) and data derived from QSAR models

The bioconcentration factor (BCF) is the ratio of the concentration of a chemical in an organism to the concentration in the surrounding environment at steady state. It is a valuable indicator of the bioaccumulation potential of a substance. BCF is an essential environmental property required for regulatory purposes within the Registration, Evaluation, Authorization and restriction of Chemicals (REACH) and Globally Harmonized System (GHS) regulations. In silico models for predicting BCF can facilitate the risk assessment for aquatic toxicology and reduce the cost and number of animals used. The aim of the present study was to examine the correlation of BCF data derived from the dossiers of registered chemicals submitted to the European Chemical Agency (ECHA) with the results of a battery of Quantitative Structure-Activity Relationship (QSAR). After data pruning, statistical analysis was performed using the predictions of the selected models. Results in terms of R(2) had low rating around 0.5 for the pruned dataset. The use of the model applicability domain index (ADI) led to an improvement of the performance for compounds falling within it. The variability of the experimental data and the use of different parameters to define the applicability domain can influence the performance of each model. All available information should be adapted to the requirements of the regulation to obtain a safe decision.

Integrating QSAR and read-across for environmental assessment

Read-across and QSAR have different traditions and drawbacks. We address here two main questions: (1) How do we solve the issue of the subjectivity in the evaluation of data and results, which may be particularly critical for read-across, but may have a role also for the QSAR assessment? (2) How do we take advantage of the results of both approaches to support each other? The QSAR model starts from the training set. The presence of similar chemicals with property values close to that predicted can support the result. The approach in read-across is the opposite. The assessment is focused on the few substances similar to the target. The data quality of the similar chemicals is fundamental. A risk is poor standardization in the definition of 'similarity', because different approaches may be applied. Inspired by the principles of high transparency and reproducibility, a new program for read-across, called ToxRead, has been developed and made freely available ( www.toxgate.eu ). The output of ToxRead can be compared and integrated with the output of QSAR, within a weight-of-evidence strategy. We discuss the evaluation and integration of ToxRead and QSAR with examples of the assessment of bioconcentration factors of chemicals.