Classification of Phthalates According to Their (Q)SAR Predicted Acute Toxicity to Fish: A Case Study.

This report presents the preliminary results from a (Q)SAR investigation of the acute toxicity to fish (fathead minnow) for a dataset of phthalate esters. A chemical set of 341 phthalates was compiled by using different searching engines. Their acute toxicity to fathead minnow was calculated with the ECOSAR and TOPKAT software. A good correlation between the predictions from the two programs was established (r2 = 0.81). The chemicals were classified initially into four groups on a basis of their predicted by ECOSAR LC50 values: 1) no reasons for concern (LC50 > 100 mg/L), 2) harmful (10 mg/L 5). The predictions from TOPKAT (only predictions within the optimum prediction space were considered) correlated relatively well with those from ECOSAR. There were many high molecular weight phthalate esters in the chemical series, which appeared clearly outside the applicability domain of the ECOSAR models. This fact, as well as the understanding that beyond certain limits of hydrophobicity the toxicity of the organic chemicals decreases as a result of reduced bioconcentration, motivated the development of an algorithm for refinement of acute toxicity predictions of the phthalate esters using the bilinear relationship with log Kow. In addition, water solubility limits were considered. Long-term toxicity studies were not considered in this study. Transformation (e.g. biodegradability) of the parent compounds was not considered either. This could potentially be important as, theoretically, the transformation of very hydrophobic chemicals (log Kow > 7) or extremely hydrophobic chemicals (log Kow > 8.0) into more hydrophilic degradation/transformation products may increase the acute toxicity to fish. This case study provides an illustration of how (Q)SAR methods can be used in the development of chemical categories and how (Q)SAR results can be used to perform an initial screening in support of classification and labelling. The results are discussed and interpreted with a view of what constitutes a category, how it can be defined and described, what are its boundaries, and the need to define subcategories that might be useful for deciding on the level of acute toxicological hazard associated with different structural modifications. Due to the preliminary nature of the (Q)SAR models, the results of this study should be regarded as an illustration of the applicability of (Q)SAR methods. The actual model results and rule-based classification scheme will need validation and refinement before they could be considered for regulatory use.JRC.I.3-Toxicology and chemical substance

Review of Data Sources, QSARs and Integrated Testing Strategies for Aquatic Toxicity

This review collects information on sources of aquatic toxicity data and computational tools for estimation of chemical toxicity aquatic to aquatic organisms, such as expert systems and quantitative structure-activity relationship (QSAR) models. The review also captures current thinking of what constitutes an integrated testing strategy (ITS) for this endpoint. The emphasis of the review is on the usefulness of the models and for the regulatory assessment of chemicals, particularly for the purposes of the new European legislation for the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), which entered into force on 1 June 2007. Effects on organisms from three trophic levels (fish, Daphnia and algae) were subject of this review. In addition to traditional data sources such as databases, papers publishing experimental data are also identified. Models for narcoses, general (global) models as well as models for specific chemical classes and mechanisms of action are summarised. Where possible, models were included in a form allowing reproduction without consultation with the original paper. This review builds on work carried out in the framework of the REACH Implementation Projects, and was prepared as a contribution to the EU funded Integrated Project, OSIRIS.JRC.I.3-Toxicology and chemical substance

Preliminary Analysis of an Aquatic Toxicity Dataset and Assessment of QSAR Models for Narcosis

The purpose of the analyses presented in this report was to contribute to an evaluation of the possibility of using QSAR predictions for regulatory purposes. To this end QSAR predictions were compared with SIDS test data. Furthermore, the models were also assessed according to the extent to which they meet OECD principles for QSAR validation. The comparisons are not intended to be scientific validations, because the SIDS test chemicals were not selected to ensure that they are sufficiently representative for the entire applicability domain of the individual models. Nevertheless, many of the analyses presented form the basis for scientific validationJRC.I.3-Toxicology and chemical substance

Collection and Evaluation of (Q)SAR Models for Mutagenicity and Carcinogenicity

This evaluation of the non-commercial (Q)SARs for mutagenicity and carcinogenicity consisted of a preliminary survey (Phase I), and then of a more detailed analysis of short listed models (Phase II). In Phase I, the models were collected from the literature, and then assessed according to the OECD principles based on the information provided by the authors-. Phase I provided the support for short listing a number of promising models, that were analyzed more in depth in Phase II. In Phase II, the information provided by the authors was completed and complemented with a series of analyses aimed at generating an overall profile of each of the short listed models. The models can be divided into two families based on their target: a) congeneric; and b) non-congeneric sets of chemicals. The QSARs for congeneric chemicals include most of the chemical classes top ranking in the EU High Production Volume list, with the notable exception of the halogenated aliphatics. They almost exclusively aim at modeling Salmonella mutagenicity and rodent carcinogenicity, which are crucial toxicological endpoints in the regulatory context. The lack of models for in vivo genotoxicity should be remarked. Overall the short listed models can be interpreted mechanistically, and agree with, and/or support the available scientific knowledge, and most of the models have good statistics. Based on external prediction tests, the QSARs for the potency of congeneric chemicals are 30 to 70 % correct, whereas the models for discriminating between active and inactive chemicals have considerably higher accuracy (63 to 100 %), thus indicating that predicting intervals is more reliable than predicting individual data points. The internal validation procedures (e.g., cross-validation, etc...) did not seem to be a reliable measure of external predictivity. Among the non-local, or global approaches for non-congeneric data sets, four models based on the use of Structural Alerts (SA) were short listed and investigated in more depth. The four sets did not differ to a large extent in their performance. In the general databases of chemicals the SAs appear to agree around 65% with rodent carcinogenicity data, and 75% with Salmonella mutagenicity data. The SAs based models do not seem to work equally efficiently in the discrimination between active and inactive chemicals within individual chemical classes. Thus, their main role is that of preliminary, or large-scale screenings. A priority for future research on the SAs is their expansion to include alerts for nongenotoxic carcinogens. A general indication of this study, valid for both congeneric and noncongeneric models, is that there is uncertainty associated with (Q)SARs; the level of uncertainty has to be considered when using (Q)SAR in a regulatory context. However, (Q)SARs are not meant to be black-box machines for predictions, but have a much larger scope including organization and rationalization of data, contribution to highlight mechanisms of action, complementation of other data from different sources (e.g., experiments). Using only non-testing methods, the larger the evidence from QSARs (several different models, if available) and other approaches (e.g. chemical categories, read across) the higher the confidence in the prediction.JRC.I.3-Toxicology and chemical substance

The Benigni / Bossa Rulebase for Mutagenicity and Carcinogenicity - A Module of Toxtree

The Joint Resarch Centre's European Chemicals Bureau has developed a hazard estimation software called Toxtree, capable of making structure-based predictions for a number of toxicological endpoints. One of the modules developed as an extension to Toxtree is aimed at the prediction of carcinogenicity and mutagenicity. This module encodes the Benigni/Bossa rulebase for carcinogenicity and mutagenicity developed by Romualdo Benigni and Cecilia Bossa at the Istituto Superiore di Sanita¿, in Rome, Italy. The module was coded by the Toxtree programmer, Ideaconsult Ltd, Bulgaria. In the Toxtree implementation of this rulebase, the processing of a query chemical gives rise to limited number of different outcomes, namely: a) no structural alerts for carcinogenicity are recognised; b) one or more structural alerts (SAs) are recognised for genotoxic or non-genotoxic carcinogenicity; c) SAs relative to aromatic amines or aß-unsaturated aldehydes are recognised, and the chemical goes through Quantitative Structure-Activity Relationship (QSAR) analysis, which may result in a negative or positive outcome. If the query chemical belongs to the classes of aromatic amines or aß-unsaturated aldehydes, the appropriate QSAR is applied and provides a more refined assessment than the SAs, and should be given higher importance in a weight-of-evidence scheme. This report gives an introduction to currently available QSARs and SAs for carcinogenicity and mutagenicity, and provides details of the Benigni/Bossa rulebase.JRC.I.3-Consumer products safety and qualit

The Use of Computational Methods in the Grouping and Assessment of Chemicals - Preliminary Investigations

This document presents a perspective of how computational approaches could potentially be used in the grouping and assessment of chemicals, and especially in the application of read-across and the development of chemical categories. The perspective is based on experience gained by the authors during 2006 and 2007, when the Joint Research Centre's European Chemicals Bureau was directly involved in the drafting of technical guidance on the applicability of computational methods under REACH. Some of the experience gained and ideas developed resulted from a number of research-based case studies conducted in-house during 2006 and the first half of 2007. The case studies were performed to explore the possible applications of computational methods in the assessment of chemicals and to contribute to the development of technical guidance. Not all of the methods explored and ideas developed are explicitly included in the final guidance documentation for REACH. Many of the methods are novel, and are still being refined and assessed by the scientific community. At present, many of the methods have not been tried and tested in the regulatory context. The authors therefore hope that the perspective and case studies compiled in this document, whilst not intended to serve as guidance, will nevertheless provide an input to further research efforts aimed at developing computational methods, and at exploring their potential applicability in regulatory assessment of chemicals.JRC.I.3-Toxicology and chemical substance

Chemical Similarity and Threshold of Toxicological Concern (TTC) Approaches: Report of an ECB Workshop held in Ispra, November 2005

There are many national, regional and international programmes – either regulatory or voluntary – to assess the hazards or risks of chemical substances to humans and the environment. The first step in making a hazard assessment of a chemical is to ensure that there is adequate information on each of the endpoints. If adequate information is not available then additional data is needed to complete the dataset for this substance. For reasons of resources and animal welfare, it is important to limit the number of tests that have to be conducted, where this is scientifically justifiable. One approach is to consider closely related chemicals as a group, or chemical category, rather than as individual chemicals. In a category approach, data for chemicals and endpoints that have been already tested are used to estimate the hazard for untested chemicals and endpoints. Categories of chemicals are selected on the basis of similarities in biological activity which is associated with a common underlying mechanism of action. A homologous series of chemicals exhibiting a coherent trend in biological activity can be rationalised on the basis of a constant change in structure. This type of grouping is relatively straightforward. The challenge lies in identifying the relevant chemical structural and physicochemical characteristics that enable more sophisticated groupings to be made on the basis of similarity in biological activity and hence purported mechanism of action. Linking two chemicals together and rationalising their similarity with reference to one or more endpoints has been very much carried out on an ad hoc basis. Even with larger groups, the process and approach is ad hoc and based on expert judgement. There still appears to be very little guidance about the tools and approaches for grouping chemicals systematically. In November 2005, the ECB Workshop on Chemical Similarity and Thresholds of Toxicological Concern (TTC) Approaches was convened to identify the available approaches that currently exist to encode similarity and how these can be used to facilitate the grouping of chemicals. This report aims to capture the main themes that were discussed. In particular, it outlines a number of different approaches that can facilitate the formation of chemical groupings in terms of the context under consideration and the likely information that would be required. Grouping methods were divided into one of four classes – knowledge-based, analogue-based, unsupervised, and supervised. A flowchart was constructed to attempt to capture a possible work flow to highlight where and how these approaches might be best applied.JRC.I.3-Toxicology and chemical substance

The Role of the Joint Research Centre in Promoting Possible Applications of (Q)SARs in the REACH Process.

Abstract not availableJRC.I-Institute for Health and Consumer Protection (Ispra

QSARs for the Aquatic Toxicity of Aromatic Aldehydes from Tetrahymena Data

The aim of the study was to develop quantitative structure-activity relationships (QSARs) for a large group of 77 aromatic aldehydes tested for acute toxicity to the ciliate Tetrahymena pyriformis using mechanistically interpretable descriptors. The resulting QSARs revealed that the 1-octanol/water partition coefficient (log Kow), is the most important descriptor of aldehyde aquatic toxic potency. The model with log Kow was improved by adding electronic descriptor the maximum acceptor superdelocalizability in a molecule – Amax based on calculations with the semi-empirical AM1 model. The two descriptors reflect the two main processes responsible for demonstration of acute aquatic toxicity, namely penetration through cell membranes (log Kow) and interaction with the biomacromolecules (Amax) into the cells. Results showed that generally the studied group of aldehydes could be modeled by this simple two-descriptor approach. However, the group of 2- and/or 4-hydroxylated aldehydes demonstrates enhanced toxicity compared to the other aldehydes. Transformation to quinone-like structures is proposed as the explanation for this enhanced potency. The 2- and/or 4-hydroxylated aldehydes are modeled successfully by [log (1/IGC50) = 0.540 (0.038) log Kow + 8.30 (2.88) Amax – 3.11 (0.92), n = 25, R2 = 0.916, R2CV = 0.896, s = 0.141, F = 120], while the other aldehydes are modeled by the relationship [log (1/IGC50) = 0.583 (0.034) log Kow + 9.80 (2.62) Amax – 4.04 (0.85), n = 52, R2 = 0.864, R2CV = 0.844, s = 0.203, F = 156], which is similar to the general benzene model.JRC.I.3-Toxicology and chemical substance

Advances in Bioaccumulation: Reflections from the SETAC Europe 17th Annual Meeting

Different pieces of legislation worldwide, and particularly the European Registration Evaluation Authorisation of Chemicals (REACH) program, which entered into force on 1st June 2007, create an increased demand for more reliable information about different toxicological and fate properties, including bioaccumulation. Bioaccumulation has been the focus of dedicated Working Groups to develop guidance for the endpoint under the umbrella of the REACH Implementation Projects (RIP 3.3), and for overall PBT assessment of chemicals (RIP 3.2). The SETAC Advisory Group on Bioaccumulation Assessment (B-SAG) has a proven record of stimulating the incorporation of sound science within regulatory contexts by providing excellent forums for exchange of information and collaboration between scientists from government, industry and academia, and for creating a friendly environment where novel research and young scientists find warm welcome. For the 17th Annual Meeting, the B-SAG organised two oral sessions and two poster corners, which attracted ~60 abstracts and considerable attention at the meeting. The sessions were logically organised around the main themes of in vitro/modelling approaches and lab/field studies, and gave a forum to presenters from two continents, equally eager to share experience and move the science forward. Here we share top lines from the platform presentations.JRC.I.3-Toxicology and chemical substance