New Developments in Environmental Exposure Assessment in the EU Pesticide Regulatory Process

The paper discusses key aspects of the European Union (EU) regulatory policy for environmental exposure assessment of agricultural pesticide active substances (a.s.) in soil and water, which is examined in the context of the EU Authorisations Directive (91/414/EEC). For agricultural pesticide regulation within EU Member States (MS), the Authorisations Directive will gradually replace existing national systems. Discussion is concentrated on this directive, looking in particular at the Uniform Principles therein and the possible ways that these decision-making guidelines are being developed into a workable regulatory framework. The aim in this process of negotiated development involving the Member States, the Agrochemical Industry and the European Commission (EC), is to identify any questions or data requirements that will be needed for agricultural pesticides.     

Predictions for existing chemicals-a multilateral QSAR project

Abstract Following a previous collaborative EU/EPA project focussed on QSAR predictions for a selection of new chemicals which had been notified in the EU, a similar exercise was started in 1993 on existing chemicals. In a first phase, the project addresses the High Production Volume (HPV) chemicals which are produced or imported at levels above a 1000t/year in the EU and 454t/year in the US. The relevant EU (Annex 1 of Existing Chemicals Regulation No. 793/93) and US-EPA lists contain 1036 and 2881 organic substances respectively of which HPV 749 chemicals are in common. The joint project aims at an estimation through validated QSAR models of the physical-chemical, ecotoxicity and toxicity endpoints which are included in the regulation and where experimental data will become available in IUCLID (International Unified Chemicals Information Database). Next to EC-JRC (ECB) and US-EPA, various laboratories in the EU are contributing to the project and recently, two institutes in Japan have joined in this project.     

A Noncongeneric Model for Predicting Toxicity of Organic Molecules to Vibrio Fischeri

Abstract

A general Quantitative Structure-Activity Relationship (QSAR) model on Vibrio fischeri (Microtox^? test) was derived using the autocorrelation method for describing the molecules and a neural network as statistical tool. From a training set of 1068 organic chemicals described by means of four different autocorrelation vectors, it was possible to obtain valuable models but presenting some large outliers. Addition of the time of exposure as variable allowed us to derive a more powerful model from 2795 toxicity results. The predictive power of this 36/26/1 neural network model was tested on an external testing set of 385 toxicity data and compared with the performances of linear models designed for polar narcotic amines and for weak acid respiratory uncouplers.     

Evaluation of SARs for the prediction of eye irritation/corrosion potential–structural inclusion rules in the BfR decision support system†

The proposed REACH regulation within the European Union (EU) aims to minimise the number of laboratory animals used for human hazard and risk assessment while ensuring adequate protection of human health and the environment. One way to achieve this goal is to develop non-testing methods, such as (quantitative) structure–activity relationships ([Q]SARs), suitable for identifying toxicological hazard from chemical structure and physicochemical properties alone. A database containing data submitted within the EU New Chemicals Notification procedure was compiled by the German Bundesinstitut für Risikobewertung (BfR). On the basis of these data, the BfR built a decision support system (DSS) for the prediction of several toxicological endpoints. For the prediction of eye irritation and corrosion potential, the DSS contains 31 physicochemical exclusion rules evaluated previously by the European Chemicals Bureau (ECB), and 27 inclusion rules that define structural alerts potentially responsible for eye irritation and/or corrosion. This work summarises the results of a study carried out by the ECB to assess the performance of the BfR structural rulebase. The assessment included: (a) evaluation of the structural alerts by using the training set of 1341 substances with experimental data for eye irritation and corrosion; and (b) external validation by using an independent test set of 199 chemicals. Recommendations are made for the further development of the structural rules in order to increase the overall predictivity of the DSS.     

Evaluation of SARs for the prediction of eye irritation/corrosion potential: structural inclusion rules in the BfR decision support system

The proposed REACH regulation within the European Union (EU) aims to minimise the number of laboratory animals used for human hazard and risk assessment while ensuring adequate protection of human health and the environment. One way to achieve this goal is to develop non-testing methods, such as (quantitative) structure-activity relationships ([Q]SARs), suitable for identifying toxicological hazard from chemical structure and physicochemical properties alone. A database containing data submitted within the EU New Chemicals Notification procedure was compiled by the German Bundesinstitut für Risikobewertung (BfR). On the basis of these data, the BfR built a decision support system (DSS) for the prediction of several toxicological endpoints. For the prediction of eye irritation and corrosion potential, the DSS contains 31 physicochemical exclusion rules evaluated previously by the European Chemicals Bureau (ECB), and 27 inclusion rules that define structural alerts potentially responsible for eye irritation and/or corrosion. This work summarises the results of a study carried out by the ECB to assess the performance of the BfR structural rulebase. The assessment included: (a) evaluation of the structural alerts by using the training set of 1341 substances with experimental data for eye irritation and corrosion; and (b) external validation by using an independent test set of 199 chemicals. Recommendations are made for the further development of the structural rules in order to increase the overall predictivity of the DSS.     

The prospects for using (Q)SARs in a changing political environment--high expectations and a key role for the European Commission's joint research centre

Recent policy developments in the European union (EU) and within the Organisation for Economic Cooperation and Development (OECD) have placed increased emphasis on the use of structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs), collectively referred to as (Q)SARs, within various regulatory programmes for the assessment of chemicals and products. The most significant example within the EU is the European commission's proposal (of 29 October 2003) to introduce a new system for managing chemicals (called REACH), which calls for an increased use of (Q)SARs and other non-animal methods, especially for the assessment of low production volume chemicals. Another development within the EU is the Seventh Amendment to the Cosmetics Directive, which foresees the phasing out of animal testing on cosmetics, combined with the imposition of marketing bans on cosmetics that have been tested on animals after certain deadlines. At the same time, the Existing Chemicals programme within the OECD is investigating ways of increasing the use of chemical category approaches, which depend heavily on the use of (Q)SARs, activity-activity relationships and read-across. Such developments are placing an enormous challenge on industry, regulatory bodies, and on the European commission's Joint Research Centre (JRC), which is responsible for providing independent scientific advice to policy makers in the European Commission and the Member States. This paper reviews the different scientific and regulatory purposes for which reliable (Q)SARs could be used, and describes the current work of the JRC in providing scientific support for the development, validation and implementation of (Q)SARs.     

Identification of Phototoxic Polycyclic Aromatic Hydrocarbons in Sediments Through Sample Fractionation and QSAR Analysis

Abstract

The toxicity of certain polycyclic aromatic hydrocarbons (PAHs) can be greatly increased by simultaneous exposure of test organisms to ultraviolet (UV) wavelengths present in sunlight. This phenomenon, commonly termed photoinduced toxicity, had been evaluated extensively in laboratory settings where only one chemical of concern was present. However, more recent studies have demonstrated that complex mixtures of PAHs present, for example in sediments, also can cause phototoxicity to a variety of aquatic species when the samples are tested in simulated sunlight. Unfortunately, because these types of samples can contain thousands of substituted and unsubstituted PAHs it is difficult, if not impossible, to use conventional analytical techniques to identify those responsible for photoinduced toxicity. The objective of the present study was to link two powerful ecotoxicology tools, toxicity-based fractionation techniques and QSAR models, to identify phototoxic chemicals in a sediment contaminated with PAHs emanating from an oil refinery. Extensive chromatographic fractionation of pore water from the sediment, in conjunction with toxicity testing, yielded a simplified set of sample fractions containing 12 PAHs that were identified via mass spectroscopy. Evaluation of these compounds using a recently developed QSAR model revealed that, based upon their HOMO-LUMO gap energies, about half were capable of producing photoinduced toxicity. We further evaluated the phototoxic potential of the reduced set of PAHs by determining their propensity to bioaccumulate in test organisms, through calculation of octanol-water partition coefficients for the chemicals. These studies represent a novel linkage of sample fractionation methods with QSAR models for conducting an ecological risk assessment.     

Quantitative Relationships of Structure-Activity and Volume Fraction For Selected Nonpolar and Polar Narcotic Chemicals

Abstract

The relative toxicity of selected industrial organic chemicals was secured from the literature for the static 48-h Tetrahymena pyriformis 50% population growth impairment and the flow-through 96-h Pimephales promelas 50% mortality endpoints. Chemicals were selected to represent the nonpolar narcosis (aliphatic alcohols and aliphatic ketones) and polar narcosis (anilines and phenols) mechanisms of toxic action. molar volume (MV) and 1-octanol/water partition coefficient (log K _ow) data were generated for each chemical. High-quality, log K _ow dependent quantitative structure-activity relationships were observed for each chemical class and mechanism of action for both endpoints. The volume fraction (V _t) for each chemical in the target phase was determined from the toxicant concentration in the water (toxicity data), the MV, and the target/water partition coefficient (K _tw) with K _tw considered equal to K _ow ^(1-a). Analyses of target sites, by way of “a” revealed that “a” was constant for a mechanism of action regardless of chemical class, but distinct for a given test system. Mean V _t was constant for each mechanism of action regardless of chemical class or test system. These results suggest, at least for reversible physical mechanisms, that volume fraction analyses are significant in determining the mechanism of toxic action of a chemical.     

Development of a chronic fish toxicity model for predicting sub-lethal NOEC values for non-polar narcotics

To comply with the REACH (Registration, Evaluation, Authorisation and restriction of Chemicals) regulations, the generation of chronic fish toxicity data is required for chemicals produced or imported within or into the EU in quantities greater than 100 tonnes per year. This comes at a great cost to industry and consumers alike and requires the sacrifice of many vertebrates. In acknowledgment of these issues the REACH regulations encourage the use of non-testing methods (NTM). These include read-across, weight-of-evidence and QSAR (quantitative structure–activity relationship) techniques. There are many QSAR tools available to generate predictive values for a number of physico-chemical properties, as well as human and environmental health end points; however, close analysis of the currently available chronic fish models identified room for improvement in both the selection of data used and in its application in model creation. In light of this a model was developed using only sub-lethal no-observed-effect concentration (NOEC) end-point data according to best practice QSAR development. Only the lowest value was taken for each compound, in line with the conservative approach taken by the European Chemicals Agency (ECHA). The model developed meets the Organisation for Economic Co-operation and Development (OECD) principles, has strong internal and external validation statistics, and can reliably predict sub-lethal chronic NOEC values for fish within its defined applicability domain.     

Regulatory use of (Q)SARs in toxicological hazard assessment strategies

In 2001, the European Commission published a policy statement ("White Paper") on future chemicals regulation and risk reduction that proposed the use of non-animal test systems and tailor-made testing approaches, including (Q)SARs, to reduce financial costs and the number of test animals employed. The authors have compiled a database containing data submitted within the EU chemicals notification procedure. From these data, (Q)SARs for the prediction of local irritation/corrosion and/or sensitisation potential were developed and published. These (Q)SARs, together with an expert system supporting their use, will be submitted for official validation and application within regulatory hazard assessment strategies. The main features are: ? two sets of structural alerts for the prediction of skin sensitisation hazard classification as defined by the European risk phrase R43, comprising 15 rules for chemical substructures deemed to be sensitising by direct action with cells or proteins, and three rules for substructures acting indirectly, i.e., requiring biochemical transformation; ? a decision support system (DSS) for the prediction of skin and/or eye lesion potential built from information extracted from our database. This DSS combines SARs defining reactive chemical substructures relevant for local lesions to be classified, and QSARs for the prediction of the absence of such a potential. The role of the BfR database, and (Q)SARs derived from it, in the use of current and future (EU) testing strategies for irritation and sensitisation is discussed.     

Development of classification models for predicting chronic toxicity of chemicals to Daphnia magna and Pseudokirchneriella subcapitata

Both the acute toxicity and chronic toxicity data on aquatic organisms are indispensable parameters in the ecological risk assessment priority chemical screening process (e.g. persistent, bioaccumulative and toxic chemicals). However, most of the present modelling actions are focused on developing predictive models for the acute toxicity of chemicals to aquatic organisms. As regards chronic aquatic toxicity, considerable work is needed. The major objective of the present study was to construct in silico models for predicting chronic toxicity data for Daphnia magna and Pseudokirchneriella subcapitata. In the modelling, a set of chronic toxicity data was collected for D. magna (21 days no observed effect concentration (NOEC)) and P. subcapitata (72 h NOEC), respectively. Then, binary classification models were developed for D. magna and P. subcapitata by employing the k-nearest neighbour method (k-NN). The model assessment results indicated that the obtained optimum models had high accuracy, sensitivity and specificity. The model application domain was characterized by the Euclidean distance-based method. In the future, the data gap for other chemicals within the application domain on their chronic toxicity for D. magna and P. subcapitata could be filled using the models developed here.     

First proficiency testing to evaluate the ability of European Union National Reference Laboratories to detect staphylococcal enterotoxins in milk products

The European Commission has designed a network of European Union-National Reference Laboratories (EU-NRLs), coordinated by a Community Reference Laboratory (CRL), for control of hygiene of milk and milk products (Council Directive 92/46/ECC). As a common contaminant of milk and milk products such as cheese, staphylococcal enterotoxins are often involved in human outbreaks and should be monitored regularly. The main tasks of the EU-CRLs were to select and transfer to the EU-NRLs a reference method for detection of enterotoxins, and to set up proficiency testing to evaluate the competency of the European laboratory network. The first interlaboratory exercise was performed on samples of freeze-dried cheese inoculated with 2 levels of staphylococcal enterotoxins (0.1 and 0.25 ng/g) and on an uninoculated control. These levels were chosen considering the EU regulation for staphylococcal enterotoxins in milk and milk products and the limit of detection of the enzyme-linked immunosorbent assay test recommended in the reference method. The trial was conducted according to the recommendations of ISO Guide 43. Results produced by laboratories were compiled and compared through statistical analysis. Except for data from 2 laboratories for the uninoculated control and cheese inoculated at 0.1 ng/g, all laboratories produced satisfactory results, showing the ability of the EU-NRL network to monitor the enterotoxin contaminant.     

Rapid Determination of Anthracene and Benzo(a)pyrene by High-Performance Liquid Chromatography with Fluorescence Detection

A rapid and simple method was optimized and validated for the separation and quantification of anthracene and benzo(a)pyrene, two of the most toxic polycyclic aromatic hydrocarbons, at ultratrace levels in aqueous samples by direct injection. The determination of anthracene and benzo(a)pyrene was performed by reverse-phase high-performance liquid chromatography (HPLC) with fluorescence detection. A fractional factorial matrix and a Box–Behnken design were chosen for screening and optimization purposes, respectively. The optimized parameters that significantly influenced the system were the flow rate (1?mL?min^?1), mobile-phase strength (90% acetonitrile:10% deionized water), column temperature (35°C), and excitation wavelength (254 and 267?nm for anthracene and benzo(a)pyrene, respectively). The injection volume and emission wavelength were fixed at 100?µL and 416?nm, respectively. The quantification limits were 75?ng?L^?1 for anthracene and 30?ng?L^?1 for benzo(a)pyrene. The relative standard deviations for the recovery and intra and interday precision values were lower than 20%. The method allows the analysis of aqueous samples with a good resolution for anthracene and benzo(a)pyrene below values permitted by the recently developed European Directive 2013 Directive. 2013. Directive 2013/39/EU of the European parliament and of the council of 12 August 2013 amending directives 2000/60/EC and 2008/105/EC as regards priority substances in the field of water policy. Official Journal of the European Union L 226:1–17. [Google Scholar]/39/EU for inland surface waters. In addition, this work provides guidelines for the simultaneous optimization of several parameters by experimental design.