Combination of computational new approach methodologies for enhancing evidence of biological pathway conservation across species.

The ability to predict which chemicals are of concern for environmental safety is dependent, in part, on the ability to extrapolate chemical effects across many species. This work investigated the complementary use of two computational new approach methodologies to support cross-species predictions of chemical susceptibility: the US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool and Unilever's recently developed Genes to Pathways - Species Conservation Analysis (G2P-SCAN) tool. These stand-alone tools rely on existing biological knowledge to help understand chemical susceptibility and biological pathway conservation across species. The utility and challenges of these combined computational approaches were demonstrated using case examples focused on chemical interactions with peroxisome proliferator activated receptor alpha (PPARα), estrogen receptor 1 (ESR1), and gamma-aminobutyric acid type A receptor subunit alpha (GABRA1). Overall, the biological pathway information enhanced the weight of evidence to support cross-species susceptibility predictions. Through comparisons of relevant molecular and functional data gleaned from adverse outcome pathways (AOPs) to mapped biological pathways, it was possible to gain a toxicological context for various chemical-protein interactions. The information gained through this computational approach could ultimately inform chemical safety assessments by enhancing cross-species predictions of chemical susceptibility. It could also help fulfill a core objective of the AOP framework by potentially expanding the biologically plausible taxonomic domain of applicability of relevant AOPs.

Method validation and environmental monitoring of triethanolamine ester quaternary ammonium compounds.

In this study water and sediment samples, collected from the River Nene (Northamptonshire) at several sites in the vicinity of the Great Billing sewage treatment plant (STP), were analysed for triethanolamine quaternary compounds (TEAQ, ester quats). A method was developed using liquid chromatography tandem mass spectrometry (LC/MS/MS) with a electrospray ionisation source (ESI). Ten components were determined using a characterised commercial sample of Tallow TEAQ as a standard. To our knowledge this is the first time environmental concentrations of a wide spectrum of individual homologues of TEAQ have been reliably quantified covering a broad range of environmental matrices (STP influent, STP effluent, surface waters and sediments), due to the challenging nature of the analytical method. The method featured novel solutions for the determination of long and multiple chain length alkyl quats, controlling loss processes, background contamination and chromatographic performance. TEAQ compounds were found to be highly removed in the sewage treatment plant resulting in low effluent concentrations. Low concentrations in both river water and sediment samples were found also. In many cases levels were below the Method Detection Limit (MDL). In river water samples, mean values of TEAQ compounds found were 210-398 ng/L for C16:0/C18:0 TEAQ diester and 126-287 ng/L for C18:0/C18:0 TEAQ diester. River sediment was found to contain mean TEAQ levels of 7.07-12.5, 19.7 to 40.3 and 7.04-35.1 µg/kg dry weight for C16:0/C16:0, C16:0/C18:0, and C18:0/C18:0 TEAQ, respectively. At Great Billing STP monoesters and diesters of TEAQ were shown to be efficiently removed (>97 and 99 %, respectively), although limited samples were taken on this occasion.

Partitioning into phosphatidylcholine-cholesterol membranes: liposome measurements, coarse-grained simulations, and implications for bioaccumulation.

Membrane-water partitioning is an important physical property for the assessment of bioaccumulation and environmental impact. Here, we advance simulation methodology for predicting the partitioning of small molecules into lipid membranes and compare the computational predictions to experimental measurements in liposomes. As a step towards high-throughput screening, we present an automated mapping and parametrization procedure to produce coarse-grained models compatible with the Martini 3 force field. The methodology is general and can also be used for other applications where coarse-grained simulations are appropriate. This article addresses the effect on membrane-water partitioning of adding cholesterol to POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) membranes. Nine contrasting neutral, zwitterionic and charged solutes are tested. Agreement between experiment and simulation is generally good, with the most challenging cases being permanently charged solutes. For all solutes, partitioning is found to be insensitive to membrane cholesterol concentration up to 25% mole fraction. Hence, for assessment of bioaccumulation into a range of membranes (such as those found in fish), partitioning data measured in pure lipid membranes are still informative.

Genes-to-Pathways Species Conservation Analysis: Enabling the Exploration of Conservation of Biological Pathways and Processes Across Species.

The last two decades have witnessed a strong momentum toward integration of cell-based and computational approaches in safety assessments. This is fueling a global regulatory paradigm shift toward reduction and replacement of the use of animals in toxicity tests while promoting the use of new approach methodologies. The understanding of conservation of molecular targets and pathways provides an opportunity to extrapolate effects across species and ultimately to determine the taxonomic applicability domain of assays and biological effects. Despite the wealth of genome-linked data available, there is a compelling need for improved accessibility, while ensuring that it reflects the underpinning biology. We present the novel pipeline Genes-to-Pathways Species Conservation Analysis (G2P-SCAN) to further support understanding on cross-species extrapolation of biological processes. This R package extracts, synthetizes, and structures the data available from different databases, that is, gene orthologs, protein families, entities, and reactions, linked to human genes and respective pathways across six relevant model species. The use of G2P-SCAN enables the overall analysis of orthology and functional families to substantiate the identification of conservation and susceptibility at the pathway level. In the present study we discuss five case studies, demonstrating the validity of the developed pipeline and its potential use as species extrapolation support. We foresee this pipeline will provide valuable biological insights and create space for the use of mechanistically based data to inform potential species susceptibility for research and safety decision purposes. Environ Toxicol Chem 2023;42:1152-1166. © 2023 UNILEVER GLOBAL IP LTD. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Using membrane-water partition coefficients in a critical membrane burden approach to aid the identification of neutral and ionizable chemicals that induce acute toxicity below narcosis levels.

The risk assessment of thousands of chemicals used in our society benefits from adequate grouping of chemicals based on the mode and mechanism of toxic action (MoA). We measure the phospholipid membrane-water distribution ratio (DMLW) using a chromatographic assay (IAM-HPLC) for 121 neutral and ionized organic chemicals and screen other methods to derive DMLW. We use IAM-HPLC based DMLW as a chemical property to distinguish between baseline narcosis and specific MoA, for reported acute toxicity endpoints on two separate sets of chemicals. The first set comprised 94 chemicals of US EPA's acute fish toxicity database: 47 categorized as narcosis MoA, 27 with specific MoA, and 20 predominantly ionic chemicals with mostly unknown MoA. The narcosis MoA chemicals clustered around the median narcosis critical membrane burden (CMBnarc) of 140 mmol kg-1 lipid, with a lower limit of 14 mmol kg-1 lipid, including all chemicals labelled Narcosis_I and Narcosis_II. This maximum 'toxic ratio' (TR) between CMBnarc and the lower limit narcosis endpoint is thus 10. For 23/28 specific MoA chemicals a TR >10 was derived, indicative of a specific adverse effect pathway related to acute toxicity. For 10/12 cations categorized as "unsure amines", the TR <10 suggests that these affect fish via narcosis MoA. The second set comprised 29 herbicides, including 17 dissociated acids, and evaluated the TR for acute toxic effect concentrations to likely sensitive aquatic plant species (green algae and macrophytes Lemna and Myriophyllum), and non-target animal species (invertebrates and fish). For 21/29 herbicides, a TR >10 indicated a specific toxic mode of action other than narcosis for at least one of these aquatic primary producers. Fish and invertebrate TRs were mostly <10, particularly for neutral herbicides, but for acidic herbicides a TR >10 indicated specific adverse effects in non-target animals. The established critical membrane approach to derive the TR provides for useful contribution to the weight of evidence to bin a chemical as having a narcosis MoA or less likely to have acute toxicity caused by a more specific adverse effect pathway. After proper calibration, the chromatographic assay provides consistent and efficient experimental input for both neutral and ionizable chemicals to this approach.

Construction of an In Silico Structural Profiling Tool Facilitating Mechanistically Grounded Classification of Aquatic Toxicants.

The performance of chemical safety assessment within the domain of environmental toxicology is often impeded by a shortfall of appropriate experimental data describing potential hazards across the many compounds in regular industrial use. In silico schemes for assigning aquatic-relevant modes or mechanisms of toxic action to substances, based solely on consideration of chemical structure, have seen widespread employment─including those of Verhaar, Russom, and later Bauer (MechoA). Recently, development of a further system was reported by Sapounidou, which, in common with MechoA, seeks to ground its classifications in understanding and appreciation of molecular initiating events. Until now, this Sapounidou scheme has not seen implementation as a tool for practical screening use. Accordingly, the primary purpose of this study was to create such a resource─in the form of a computational workflow. This exercise was facilitated through the formulation of 183 structural alerts/rules describing molecular features associated with narcosis, chemical reactivity, and specific mechanisms of action. Output was subsequently compared relative to that of the three aforementioned alternative systems to identify strengths and shortcomings as regards coverage of chemical space.

A scheme to evaluate structural alerts to predict toxicity - Assessing confidence by characterising uncertainties.

Structure-activity relationships (SARs) in toxicology have enabled the formation of structural rules which, when coded as structural alerts, are essential tools in in silico toxicology. Whilst other in silico methods have approaches for their evaluation, there is no formal process to assess the confidence that may be associated with a structural alert. This investigation proposes twelve criteria to assess the uncertainty associated with structural alerts, allowing for an assessment of confidence. The criteria are based around the stated purpose, description of the chemistry, toxicology and mechanism, performance and coverage, as well as corroborating and supporting evidence of the alert. Alerts can be given a confidence assessment and score, enabling the identification of areas where more information may be beneficial. The scheme to evaluate structural alerts was placed in the context of various use cases for industrial and regulatory applications. The analysis of alerts, and consideration of the evaluation scheme, identifies the different characteristics an alert may have, such as being highly specific or generic. These characteristics may determine when an alert can be used for specific uses such as identification of analogues for read-across or hazard identification.

Data-driven learning of narcosis mode of action identifies a CNS transcriptional signature shared between whole organism Caenorhabditis elegans and a fish gill cell line.

With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical.

Screening the baseline fish bioconcentration factor of various types of surfactants using phospholipid binding data.

Fish bioconcentration factors (BCFs) are commonly used in chemical hazard and risk assessment. For neutral organic chemicals BCFs are positively correlated with the octanol-water partition ratio (KOW), but KOW is not a reliable parameter for surfactants. Membrane lipid-water distribution ratios (DMLW) can be accurately measured for all kinds of surfactants, using phospholipid-based sorbents. This study first demonstrates that DMLW values for ionic surfactants are more than 100 000 times higher than the partition ratio to fish-oil, representing neutral storage lipid. A non-ionic alcohol ethoxylate surfactant showed almost equal affinity for both lipid types. Accordingly, a baseline screening BCF value for surfactants (BCFbaseline) can be approximated for ionic surfactants by multiplying DMLW by the phospholipid fraction in tissue, and for non-ionic surfactants by multiplying DMLW by the total lipid fraction. We measured DMLW values for surfactant structures, including linear and branched alkylbenzenesulfonates, an alkylsulfoacetate and an alkylethersulfate, bis(2-ethylhexyl)-surfactants (e.g., docusate), zwitterionic alkylbetaines and alkylamine-oxides, and a polyprotic diamine. Together with sixty previously published DMLW values for surfactants, structure-activity relationships were derived to elucidate the influence of surfactant specific molecular features on DMLW. For 23 surfactant types, we established the alkyl chain length at which BCFbaseline would exceed the EU REACH bioaccumulation (B) threshold of 2000 L kg-1, and would therefore require higher tier assessments to further refine the BCF estimate. Finally, the derived BCFbaseline are compared with measured literature in vivo BCF data where available, suggesting that refinements, most notably reliable estimates of biotransformation rates, are needed for most surfactant types.

Development of an Enhanced Mechanistically Driven Mode of Action Classification Scheme for Adverse Effects on Environmental Species.

This study developed a novel classification scheme to assign chemicals to a verifiable mechanism of (eco-)toxicological action to allow for grouping, read-across, and in silico model generation. The new classification scheme unifies and extends existing schemes and has, at its heart, direct reference to molecular initiating events (MIEs) promoting adverse outcomes. The scheme is based on three broad domains of toxic action representing nonspecific toxicity (e.g., narcosis), reactive mechanisms (e.g., electrophilicity and free radical action), and specific mechanisms (e.g., associated with enzyme inhibition). The scheme is organized at three further levels of detail beyond broad domains to separate out the mechanistic group, specific mechanism, and the MIEs responsible. The novelty of this approach comes from the reference to taxonomic diversity within the classification, transparency, quality of supporting evidence relating to MIEs, and that it can be updated readily.

Vision of a near future: Bridging the human health-environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment.

There is a growing recognition that application of mechanistic approaches to understand cross-species shared molecular targets and pathway conservation in the context of hazard characterization, provide significant opportunities in risk assessment (RA) for both human health and environmental safety. Specifically, it has been recognized that a more comprehensive and reliable understanding of similarities and differences in biological pathways across a variety of species will better enable cross-species extrapolation of potential adverse toxicological effects. Ultimately, this would also advance the generation and use of mechanistic data for both human health and environmental RA. A workshop brought together representatives from industry, academia and government to discuss how to improve the use of existing data, and to generate new NAMs data to derive better mechanistic understanding between humans and environmentally-relevant species, ultimately resulting in holistic chemical safety decisions. Thanks to a thorough dialogue among all participants, key challenges, current gaps and research needs were identified, and potential solutions proposed. This discussion highlighted the common objective to progress toward more predictive, mechanistically based, data-driven and animal-free chemical safety assessments. Overall, the participants recognized that there is no single approach which would provide all the answers for bridging the gap between mechanism-based human health and environmental RA, but acknowledged we now have the incentive, tools and data availability to address this concept, maximizing the potential for improvements in both human health and environmental RA.

Improved Algal Toxicity Test System for Robust Omics-Driven Mode-of-Action Discovery in Chlamydomonas reinhardtii.

Algae are key components of aquatic food chains. Consequently, they are internationally recognised test species for the environmental safety assessment of chemicals. However, existing algal toxicity test guidelines are not yet optimized to discover molecular modes of action, which require highly-replicated and carefully controlled experiments. Here, we set out to develop a robust, miniaturised and scalable Chlamydomonas reinhardtii toxicity testing approach tailored to meet these demands. We primarily investigated the benefits of synchronised cultures for molecular studies, and of exposure designs that restrict chemical volatilisation yet yield sufficient algal biomass for omics analyses. Flow cytometry and direct-infusion mass spectrometry metabolomics revealed significant and time-resolved changes in sample composition of synchronised cultures. Synchronised cultures in sealed glass vials achieved adequate growth rates at previously unachievably-high inoculation cell densities, with minimal pH drift and negligible chemical loss over 24-h exposures. Algal exposures to a volatile test compound (chlorobenzene) yielded relatively high reproducibility of metabolic phenotypes over experimental repeats. This experimental test system extends existing toxicity testing formats to allow highly-replicated, omics-driven, mode-of-action discovery.

Chemical hazard prediction and hypothesis testing using quantitative adverse outcome pathways.

Current efforts in chemical safety are focused on utilizing human in vitro or alternative animal data in biological pathway context. However, it remains unclear how biological pathways, and toxicology data developed in that context, can be used to quantitatively facilitate decision-making.  The objective of this work is to determine if hypothesis testing using Adverse Outcome Pathways (AOPs) can provide quantitative chemical hazard predictions.  Current methods for predicting hazards of chemicals in a biological pathway context were extensively reviewed, specific case studies examined and computational modeling used to demonstrate quantitative hazard prediction based on an AOP. Since AOPs are chemically agnostic, we propose that AOPs function as hypotheses for how specific chemicals may cause adverse effects via specific pathways. Three broad approaches were identified for testing the hypothesis with AOPs, semi-quantitative weight of evidence, probabilistic, and mechanistic modeling. We then demonstrate how these approaches could be used to test hypotheses using high throughput in vitro data and alternative animal data. Finally, we discuss standards in development and documentation that would facilitate use in a regulatory context. We conclude that quantitative AOPs provide a flexible hypothesis framework for predicting chemical hazards. It accommodates a wide range of approaches that are useful at many stages and build upon one another to become increasingly quantitative.

Harvesting the promise of AOPs: An assessment and recommendations.

The Adverse Outcome Pathway (AOP) concept is a knowledge assembly and communication tool to facilitate the transparent translation of mechanistic information into outcomes meaningful to the regulatory assessment of chemicals. The AOP framework and associated knowledgebases (KBs) have received significant attention and use in the regulatory toxicology community. However, it is increasingly apparent that the potential stakeholder community for the AOP concept and AOP KBs is broader than scientists and regulators directly involved in chemical safety assessment. In this paper we identify and describe those stakeholders who currently-or in the future-could benefit from the application of the AOP framework and knowledge to specific problems. We also summarize the challenges faced in implementing pathway-based approaches such as the AOP framework in biological sciences, and provide a series of recommendations to meet critical needs to ensure further progression of the framework as a useful, sustainable and dependable tool supporting assessments of both human health and the environment. Although the AOP concept has the potential to significantly impact the organization and interpretation of biological information in a variety of disciplines/applications, this promise can only be fully realized through the active engagement of, and input from multiple stakeholders, requiring multi-pronged substantive long-term planning and strategies.

The Role of Omics in the Application of Adverse Outcome Pathways for Chemical Risk Assessment.

In conjunction with the second International Environmental Omics Symposium (iEOS) conference, held at the University of Liverpool (United Kingdom) in September 2014, a workshop was held to bring together experts in toxicology and regulatory science from academia, government and industry. The purpose of the workshop was to review the specific roles that high-content omics datasets (eg, transcriptomics, metabolomics, lipidomics, and proteomics) can hold within the adverse outcome pathway (AOP) framework for supporting ecological and human health risk assessments. In light of the growing number of examples of the application of omics data in the context of ecological risk assessment, we considered how omics datasets might continue to support the AOP framework. In particular, the role of omics in identifying potential AOP molecular initiating events and providing supportive evidence of key events at different levels of biological organization and across taxonomic groups was discussed. Areas with potential for short and medium-term breakthroughs were also discussed, such as providing mechanistic evidence to support chemical read-across, providing weight of evidence information for mode of action assignment, understanding biological networks, and developing robust extrapolations of species-sensitivity. Key challenges that need to be addressed were considered, including the need for a cohesive approach towards experimental design, the lack of a mutually agreed framework to quantitatively link genes and pathways to key events, and the need for better interpretation of chemically induced changes at the molecular level. This article was developed to provide an overview of ecological risk assessment process and a perspective on how high content molecular-level datasets can support the future of assessment procedures through the AOP framework.

Advancing the adverse outcome pathway framework-An international horizon scanning approach.

Our ability to conduct whole-organism toxicity tests to understand chemical safety has been outpaced by the synthesis of new chemicals for a wide variety of commercial applications. As a result, scientists and risk assessors are turning to mechanistically based studies to increase efficiencies in chemical risk assessment and making greater use of in vitro and in silico methods to evaluate potential environmental and human health hazards. In this context, the adverse outcome pathway (AOP) framework has gained traction in regulatory science because it offers an efficient and effective means for capturing available knowledge describing the linkage between mechanistic data and the apical toxicity end points required for regulatory assessments. A number of international activities have focused on AOP development and various applications to regulatory decision-making. These initiatives have prompted dialogue between research scientists and regulatory communities to consider how best to use the AOP framework. Although expert-facilitated discussions and AOP development have been critical in moving the science of AOPs forward, it was recognized that a survey of the broader scientific and regulatory communities would aid in identifying current limitations while guiding future initiatives for the AOP framework. To that end, a global horizon scanning exercise was conducted to solicit questions concerning the challenges or limitations that must be addressed to realize the full potential of the AOP framework in research and regulatory decision-making. The questions received fell into several broad topical areas: AOP networks, quantitative AOPs, collaboration on and communication of AOP knowledge, AOP discovery and development, chemical and cross-species extrapolation, exposure/toxicokinetics considerations, and AOP applications. Expert ranking was then used to prioritize questions for each category, where 4 broad themes emerged that could help inform and guide future AOP research and regulatory initiatives. In addition, frequently asked questions were identified and addressed by experts in the field. Answers to frequently asked questions will aid in addressing common misperceptions and will allow for clarification of AOP topics. The need for this type of clarification was highlighted with surprising frequency by our question submitters, indicating that improvements are needed in communicating the AOP framework among the scientific and regulatory communities. Overall, horizon scanning engaged the global scientific community to help identify key questions surrounding the AOP framework and guide the direction of future initiatives. Environ Toxicol Chem 2017;36:1411-1421. © 2017 SETAC.

Critical micelle concentration values for different surfactants measured with solid-phase microextraction fibers.

The amphiphilic nature of surfactants drives the formation of micelles at the critical micelle concentration (CMC). Solid-phase microextraction (SPME) fibers were used in the present study to measure CMC values of 12 nonionic, anionic, cationic, and zwitterionic surfactants. The SPME-derived CMC values were compared to values determined using a traditional surface tension method. At the CMC of a surfactant, a break in the relationship between the concentration in SPME fibers and the concentration in water is observed. The CMC values determined with SPME fibers deviated by less than a factor of 3 from values determined with a surface tension method for 7 out of 12 compounds. In addition, the fiber-water sorption isotherms gave information about the sorption mechanism to polyacrylate-coated SPME fibers. A limitation of the SPME method is that CMCs for very hydrophobic cationic surfactants cannot be determined when the cation exchange capacity of the SPME fibers is lower than the CMC value. The advantage of the SPME method over other methods is that CMC values of individual compounds in a mixture can be determined with this method. However, CMC values may be affected by the presence of compounds with other chain lengths in the mixture because of possible mixed micelle formation. Environ Toxicol Chem 2016;35:2173-2181. © 2016 SETAC.

Adverse Outcome Pathways for Regulatory Applications: Examination of Four Case Studies With Different Degrees of Completeness and Scientific Confidence.

Adverse outcome pathways (AOPs) offer a pathway-based toxicological framework to support hazard assessment and regulatory decision-making. However, little has been discussed about the scientific confidence needed, or how complete a pathway should be, before use in a specific regulatory application. Here we review four case studies to explore the degree of scientific confidence and extent of completeness (in terms of causal events) that is required for an AOP to be useful for a specific purpose in a regulatory application: (i) Membrane disruption (Narcosis) leading to respiratory failure (low confidence), (ii) Hepatocellular proliferation leading to cancer (partial pathway, moderate confidence), (iii) Covalent binding to proteins leading to skin sensitization (high confidence), and (iv) Aromatase inhibition leading to reproductive dysfunction in fish (high confidence). Partially complete AOPs with unknown molecular initiating events, such as 'Hepatocellular proliferation leading to cancer', were found to be valuable. We demonstrate that scientific confidence in these pathways can be increased though the use of unconventional information (eg, computational identification of potential initiators). AOPs at all levels of confidence can contribute to specific uses. A significant statistical or quantitative relationship between events and/or the adverse outcome relationships is a common characteristic of AOPs, both incomplete and complete, that have specific regulatory uses. For AOPs to be useful in a regulatory context they must be at least as useful as the tools that regulators currently possess, or the techniques currently employed by regulators.

Ecotoxicological thresholds-practical application to an industrial inventory.

The concept of thresholds of toxicological concern as a potentially useful tool in environmental risk assessment has been applied to the inventory of a home and personal care products company to derive a series of chemical class-based ecotoxicological threshold of concern (ecoTTC) values. Cationic chemicals of various types show notably higher toxicity than other classes and should be treated separately. Despite this, the ecoTTC for the full data set in the present study is only slightly lower than that derived previously for chemicals causing toxicity via Verhaar modes of action (MoAs) 1 to 3. Exclusion of cationic chemicals resulted in an ecoTTC value slightly higher than the MoA 1 to 3 value. These observations indicate that such data sets contain few specifically acting chemicals. The applicability of threshold approaches in environmental risk assessment has been extended to include a limited number of inorganic/organometallic chemicals, polymers, and all classes of surfactants. The use of such ecoTTC values in conjunction with mode of action-based quantitative structure-activity relationships will allow the efficient screening and prioritization of large inventories of heterogeneous chemicals, focusing resources on those chemicals that require additional information to better understand any potential risk.