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Abstract REACH requires information on hazardous properties of substances to be generated avoiding animal testing where possible. It is the objective of the present case study with thiochemicals to extract as much information as possible from available experimental data with fish, daphnia and algae and to fill data gaps for analogues to be registered under REACH in 2018. Based on considerations of chemical similarity and common mode of action (MOA) the data gaps regarding the aquatic toxicity of the thiochemicals were largely closed by trend analysis ("category approach") and read-across within the same group, for example, thioglycolates or mercaptopropionates. Among 16 thiochemicals to be registered by 2018 there are only 2 substances with sufficient data. 36 data gaps for 14 thiochemicals were identified. Most of the required data (>60%) could be estimated by in silico methods. Only 14 tests (6 algae, 6 daphnia, 1 limit fish test and 1 acute fish test) were proposed. When the results of these tests are available it has to be discussed whether 2 further fish (limit) tests are required. For two substances (exposure-based) waiving was suggested. The relatively high toxicity of the thiochemicals is manifested in low predicted no-effect concentrations (PNECs). Only preliminary predicted environmental concentrations (PECs) could be derived for the thiochemicals for which a risk assessment has to be performed (production rate >10 t/y). The preliminary PEC/PNEC ratios indicate no risk for the aquatic compartment at the production site. PECs due to down-stream use must not exceed the estimated PNECs. Graphical abstract Image Highlights • Case study on acute aquatic toxicity of 16 thiochemicals to be registered in 2018. • Filling data gaps based on chemical similarity and common mode of action (MOA). • Testing strategies with algae and daphnia, avoiding tests with fish if possible. • >60% of required testing can be replaced by alternative information. [ABSTRACT FROM AUTHOR]

Aquatic bioconcentration factors (BCFs) are critical in PBT (persistent, bioaccumulative, toxic) and risk assessment of chemicals. High costs and use of more than 100 fish per standard BCF study (OECD 305) call for alternative methods to replace as much in vivo testing as possible. The BCF waiving scheme is a screening tool combining QSAR classifications based on physicochemical properties related to the distribution (hydrophobicity, ionisation), persistence (biodegradability, hydrolysis), solubility and volatility (Henry's law constant) of substances in water bodies and aquatic biota to predict substances with low aquatic bioaccumulation (nonB, BCF < 2000). The BCF waiving scheme was developed with a dataset of reliable BCFs for 998 compounds and externally validated with another 181 substances. It performs with 100% sensitivity (no false negatives), > 50% efficacy (waiving potential), and complies with the OECD principles for valid QSARs. The chemical applicability domain of the BCF waiving scheme is given by the structures of the training set, with some compound classes explicitly excluded like organometallics, poly- and perfluorinated compounds, aromatic triphenylphosphates, surfactants. The prediction confidence of the BCF waiving scheme is based on applicability domain compliance, consensus modelling, and the structural similarity with known nonB and B/vB substances. Compounds classified as nonB by the BCF waiving scheme are candidates for waiving of BCF in vivo testing on fish due to low concern with regard to the B criterion. The BCF waiving scheme supports the 3Rs with a possible reduction of > 50% of BCF in vivo testing on fish. If the target chemical is outside the applicability domain of the BCF waiving scheme or not classified as nonB, further assessments with in silico , in vitro or in vivo methods are necessary to either confirm or reject bioaccumulative behaviour. [ABSTRACT FROM AUTHOR]

Highlights: [•] Chemistry-driven in silico methods to identify hazardous substances under REACH. [•] Substances of concern: PBT, vPvB, CMR, sensitisers, endocrine disruptors. [•] Applicability domains to measure the reliability of in silico predictions. [•] Consensus modelling to consolidate multiple, possibly conflicting, results. [•] Optimised testing strategies with minimal consumption of animals, money and time. [ABSTRACT FROM AUTHOR]

The present study presents a data-oriented, tiered approach to assessing the bioaccumulation potential of chemicals according to the European chemicals regulation on Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH). The authors compiled data for eight physicochemical descriptors (partition coefficients, degradation half-lives, polarity, and so forth) for a set of 713 organic chemicals for which experimental values of the bioconcentration factor (BCF) are available. The authors employed supervised machine learning methods (conditional inference trees and random forests) to derive relationships between the physicochemical descriptors and the BCF values. In a first tier, the authors established rules for classifying a chemical as bioaccumulative (B) or nonbioaccumulative (non-B). In a second tier, the authors developed a new tool for estimating numerical BCF values. For both cases the optimal set of relevant descriptors was determined; these are biotransformation half-life and octanol-water distribution coefficient (log D) for the classification rules and log D, biotransformation half-life, and topological polar surface area for the BCF estimation tool. The uncertainty of the BCF estimates obtained with the new estimation tool was quantified by comparing the estimated and experimental BCF values of the 713 chemicals. Comparison with existing BCF estimation methods indicates that the performance of this new BCF estimation tool is at least as high as that of existing methods. The authors recommend the present study's classification rules and BCF estimation tool for a consensus application in combination with existing BCF estimation methods. Environ Toxicol Chem 2013;32:1187-1195. © 2013 SETAC [ABSTRACT FROM AUTHOR]

Environmental contaminants are frequently encountered as mixtures, and the behavior of chemicals in a mixture may not correspond to that predicted from data on the pure compounds. This paper reviews current quantitative structure-activity relationship (QSAR) methodology for the analysis of mixture toxicity. Interactions of components in a mixture can cause complex and substantial changes in the apparent properties of its constituents, resulting in synergistic or antagonistic effects as opposed to the ideal reference case of additive behavior: concentration addition (CA) and independent action (IA) are two prominent reference models for the evaluation of joint activity, and both have mechanistic support from pharmacology. After discussing graphical tools for analyzing binary mixtures and joint effect indices suitable also for multicomponent mixtures, water solubility and hydrophobicity of mixtures are analyzed with respect to the property contributions of the individual components. With the former, small but significant deviations from ideal behavior are observed even for simple organics, whereas in the case of low concentrations, mixture hydrophobicity was found to agree approximately with the fractional contributions of the components. A variety of studies suggest that mixtures of compounds exerting only one (narcotic or specific) mode of action can be modeled satisfactorily by assuming CA, whereas the interaction of differently acting compounds tends to yield a less than CA joint activity. The QSARs have been used to predict concentrations of components in mixtures from joint effects and defined mixture ratios and have been developed to predict narcotic-type mixture toxicity from molecular descriptors that are calculated as composite properties according to the fractional concentrations of the mixture components. In the case of ionogenic compounds, initial results suggest that CA may serve as a firstorder approximation for the joint effect of un-ionized and... [ABSTRACT FROM AUTHOR]

An inventory of marine biotest methods for the evaluation of dredged material and sediments was compiled on behalf of the Federal Environmental Agency of Germany. Relevant assays were identified from the literature and experts from several countries contributed to a questionnaire survey on established and developing procedures. The biotest methods are applicable to whole sediment, sediment suspension, sediment elutriate, porewater and/or sediment extract. The endpoints cover acute and long-term toxicity, bioaccumulation, endocrine effects, toxic effects on reproduction, carcinogenicity and mutagenicity.Comparative analyses and evaluation of the biotest methods were conducted with regard to their sensitivity, specificity, applicability (regional specificity, availability and suitability of the test organisms), variability (physico-chemical factors, natural factors and factors related to sampling and testing), cost-effectiveness, aspects of animal ethics, standardization (guidelines, intercalibration) and application for monitoring purposes in the areas of the OSPAR and Helsinki Conventions. The available information was integrated to rate the validity of the methods, their relevance for assessing impacts on ecosystems and the suitability of the methods for the evaluation of marine sediments and dredged material.Based on the rating of the individual bioassays, a tiered testing is suggested in a hierarchical approach representing a variety in taxa, biological processes and exposure routes, thereby covering the cellular, species, population and community level with a wide discriminatory and sensitivity range. The toxicological significance and complexity increases with the tiers: (1) screening and detection of impacts, (2) characterization of toxic effects, (3) verification of in situ alterations. [Copyright &y& Elsevier]

The 9th German Pharm-Tox Summit (GPTS) and the 90th Annual Meeting of the German Society for Experimental and Clinical Pharmacology and Toxicology (DGPT) took place in Munich from March 13–15, 2024. The event brought together over 700 participants from around the world to discuss cutting-edge developments in the fields of pharmacology and toxicology as well as scientific innovations and novel insights. A key focus of the conference was on the rapidly increasing role of computational toxicology, artificial intelligence (AI), and machine learning (ML) into the field, marking a shift away from traditional methods and allowing the reduction of animal testing as primary tool for toxicological risk assessment. Tools such as Toxometris.ai showcased the potential of AI-based risk assessments for predicting carcinogenicity, offering more ethical and efficient alternatives. Additionally, computer-driven models like computer-aided pattern analysis (C@PA) for drug toxicity prediction were presented, emphasizing the growing role of chem- and bioinformatic applications in computational sciences. Throughout the summit, there was a strong focus on the need for regulatory innovation to support the adoption of these advanced technologies and ensure the safety and sustainability of chemical substances and drugs. • Predictive AI- and machine learning (ML)-based toxicology. • Approaches in AI-Driven Computational Toxicology. • Transformation in the fields of toxicology. [ABSTRACT FROM AUTHOR]

To satisfy REACH requirements a high number of data on chemical of interest should be supplied to the European Chemicals Agency. To organize the various kinds of information and help the registrants to choose the best strategy to obtain the needed information limiting at the minimum the use of animal testing, integrated testing strategies (ITSs) schemes can be used. The present work deals with regulatory data requirements for assessing the hazards of chemicals to the aquatic pelagic environment. We present an ITS scheme for organizing and using the complex existing data available for aquatic toxicity assessment. An ITS to optimize the choice of the correct prediction strategy for aquatic pelagic toxicity is described. All existing information (like physico-chemical information), and all the alternative methods (like in silico , in vitro or the acute-to-chronic ratio) are considered. Moreover the weight of evidence approach to combine the available data is included. [ABSTRACT FROM AUTHOR]

Abstract: REACH (registration, evaluation, authorisation and restriction of chemicals) regulation requires that all the chemicals produced or imported in Europe above 1 tonne/year are registered. To register a chemical, physicochemical, toxicological and ecotoxicological information needs to be reported in a dossier. REACH promotes the use of alternative methods to replace, refine and reduce the use of animal (eco)toxicity testing. Within the EU OSIRIS project, integrated testing strategies (ITSs) have been developed for the rational use of non-animal testing approaches in chemical hazard assessment. Here we present an ITS for evaluating the bioaccumulation potential of organic chemicals. The scheme includes the use of all available data (also the non-optimal ones), waiving schemes, analysis of physicochemical properties related to the end point and alternative methods (both in silico and in vitro). In vivo methods are used only as last resort. Using the ITS, in vivo testing could be waived for about 67% of the examined compounds, but bioaccumulation potential could be estimated on the basis of non-animal methods. The presented ITS is freely available through a web tool. [Copyright &y& Elsevier]

The acute toxicity of aryl- and benzylhalides to Daphnia magna was investigated to test the validity of existing classification schemes for chemicals by mode of action, mainly based on fish studies, and theapplicability of predictive quantitative structure-activity relationship (QSAR) models. Halobenzenes and halotoluenes are generally agreed to be unambiguous baseline toxicants (class I) with the major exception of the benzylic structures, which are reactive in fish tests (class III). Eighty-nine percent of the arylhalides tested in this studymatch a log Pow-dependent QSAR, including fluorinated, chlorinated, brominated, and iodinated derivatives, thereby confirming the validity of the baseline models also for variously halogenated compounds (other than only-chloro compounds). The toxicities of the benzylhalides relative to baseline QSARs clearly indicate that these compounds belong to two classes by mode of action, i.e., they either actas narcotic toxicants (class I) or reveal excess toxicity due to unspecific reactivity (class III). On some occasions, the assignment to the two classes in D. magna deviates from the structural rules derived from fish, i.e., iodinated compounds as well as alpha,alpha-Cl2-toluenes lack reactive excess toxicity but behave as nonpolarnonspecific toxicants. The QSARs derived during this study reveal lower slopes and higher intercepts than typical baseline models and, together with the analysis of mixture toxicity studies, behavioral studies, and critical body burden, advocate the hypothesis that there areseveral different ways to produce baseline toxicity. Most halobenzenes and halotoluenes are actually baseline chemicals with some extra reactivity and as such form a subgroup, whose limits still have to be defined. Different primary sites of action could explain why the chemicals are discriminated by different classification systems, but still they must have some rate-limiting interaction in common (e.g., lipid dif [ABSTRACT FROM AUTHOR]