Roger L. Breton

A comparison of model performance for six quantitative structure-activity relationship packages that predict acute toxicity to fish

Some regulatory programs rely on quantitative structure-activity relationship (QSAR) models to predict toxic effects to biota. Many currently existing QSAR models can predict the effects of a wide range of substances to biota, particularly aquatic biota. The difficulty for regulatory programs is in choosing the appropriate QSAR model or models for application in their new and existing substances programs. We evaluated model performance of six QSAR modeling packages: Ecological Structure Activity Relationship (ECOSAR), TOPKAT, a Probabilistic Neural Network (PNN), a Computational Neural Network (CNN), the QSAR components of the Assessment Tools for the Evaluation of Risk (ASTER) system, and the Optimized Approach Based on Structural Indices Set (OASIS) system. Using a testing data set of 130 substances that had not been included in the training data sets of the QSAR models under consideration, we compared model predictions for 96-h median lethal concentrations (LC50s) to fathead minnows to the corresponding measured toxicity values available in the AQUIRE database. The testing data set was heavily weighted with neutral organics of low molecular weight and functionality. Many of the testing data set substances also had a nonpolar narcosis mode of action and/or were chlorinated. A variety of statistical measures (correlation coefficient, slope and intercept from a linear regression analysis, mean absolute and squared difference between log prediction and log measured toxicity, and the percentage of predictions within factors of 2, 5, 10, 100, and 1,000 of measured toxicity values) indicated that the PNN model had the best model performance for the full testing data set of 130 substances. The rank order of the remainder of the models depended on the statistical measure employed. TOPKAT also had excellent model performance for substances within its optimum prediction space. Only 37% of the substances in the testing data set, however, fell within this optimum prediction space.

An overview of the use of quantitative structure‐activity relationships for ranking and prioritizing large chemical inventories for environmental risk assessments

Ecological risk assessments for chemical stressors are used to establish linkages between likely exposure concentrations and adverse effects to ecological receptors. At times, it is useful to conduct screening risk assessments to assist in prioritizing or ranking chemicals on the basis of potential hazard and exposure assessment parameters. Ranking of large chemical inventories can provide evidence for focusing research and/or cleanup efforts on specific chemicals of concern. Because of financial and time constraints, data gaps exist, and the risk assessor is left with decisions on which models to use to estimate the parameter of concern. In this review, several methods are presented for using quantitative structure-activity relationships (QSARs) in conducting hazard screening or screening-level risk assessments. The ranking methods described include those related to current regulatory issues associated with chemical inventories from Canada, Europe, and the United States and an example of a screening-level risk assessment conducted on chemicals associated with a watershed in the midwest region of the United States.

Quantitative prediction of biodegradability, metabolite distribution and toxicity of stable metabolites

An evaluation of the capability of organic chemicals to mineralize is an important factor to consider when assessing their fate in the environment. Microbial degradation can convert a toxic chemical into an innocuous one, and vice versa , or alter the toxicity of a chemical. Moreover, primary biodegradation can convert chemicals into stable products that can be difficult to mineralize. In this paper, we present some new results obtained on the basis of a recently developed probabilistic approach to modeling biodegradation based on microbial transformation pathways. The metabolic transformations and their hierarchy were calibrated by making use of the ready biodegradability data from the MITI-I test and expert knowledge for the most probable transformation pathways. A model was developed and integrated into an expert software system named CATABOL that is able to predict the probability of biodegradation of organic chemicals directly from their structure. CATABOL simulates the effects of microbial enzyme systems, generates the most plausible transformation pathways, and quantitatively predicts the persistence and toxicity of the biodegradation products. A subset of 300 organic chemicals were selected from Canadas Domestic Substances List and subjected to CATABOL to compare predicted properties of the parent chemicals with their respective first stable metabolite. The results show that most of the stable metabolites have a lower acute toxicity to fish and a lower bioaccumulation potential compared to the parent chemicals. In contrast, the metabolites appear to be generally more estrogenic than the parent chemicals.

A new quality assurance system for the evaluation of ecotoxicity studies submitted under the New Substances Notification Regulations in Canada.

Abstract New substances destined for import into, or manufacture in, Canada must be reported to Environment Canada and Health Canada under the New Substances Notification Regulations (Chemicals and Polymers) (NSNR). With the use of information provided by the notifier, and other complementary information available to the 2 departments, the New Substances Program conducts ecological and human health risk assessments. Over the past 10 y, more than 750 ecotoxicity studies have been submitted to the New Substances Program of Environment Canada under the NSNR. Most of these experimental studies are not publicly available but are useful in the ecological risk assessment of new substances and for the development of Quantitative Structure–Activity Relationships (QSARs). In this paper, we describe the development and validation of a computer-based scoring system and our approach in the development of scoring methods used to assess the quality and usability of ecotoxicity studies with fish, Daphnia spp., and green algae. Results of ranking exercises conducted with these methods are described and discussed, together with the potential use of these results in a regulatory context. In addition, the methods are discussed in comparison with other similar evaluation schemes described in the literature.

Assessing the reliability of ecotoxicological studies: An overview of current needs and approaches

In general, reliable studies are well designed and well performed, and enough details on study design and performance are reported to assess the study. For hazard and risk assessment in various legal frameworks, many different types of ecotoxicity studies need to be evaluated for reliability. These studies vary in study design, methodology, quality, and level of detail reported (e.g., reviews, peer-reviewed research papers, or industry-sponsored studies documented under Good Laboratory Practice [GLP] guidelines). Regulators have the responsibility to make sound and verifiable decisions and should evaluate each study for reliability in accordance with scientific principles regardless of whether they were conducted in accordance with GLP and/or standardized methods. Thus, a systematic and transparent approach is needed to evaluate studies for reliability. In this paper, 8 different methods for reliability assessment were compared using a number of attributes: categorical versus numerical scoring methods, use of exclusion and critical criteria, weighting of criteria, whether methods are tested with case studies, domain of applicability, bias toward GLP studies, incorporation of standard guidelines in the evaluation method, number of criteria used, type of criteria considered, and availability of guidance material. Finally, some considerations are given on how to choose a suitable method for assessing reliability of ecotoxicity studies. Integr Environ Assess Manag 2017;13:640-651.

An Ecological Risk Assessment of Phenol in the Aquatic Environment

A probabilistic ecological risk assessment of phenol was undertaken to determine the risks posed to biota as a result of phenol release to the Canadian environment. A three-tiered approach was used to estimate risks, with progressively more realistic assumptions being applied at each tier. In Canada, the major sources of phenol are municipal wastewater treatment plants, pulp, paper and wood products mills, steel and metal products facilities and refineries. Thus, the highest exposures will occur in receiving waters near these point sources, primarily due to the short half-life of phenol in the aquatic environment. Sensitive aquatic organisms include salmonids (e.g., rainbow trout Oncorhynchus mykiss) and amphibians (e.g., leopard frog Rana pipiens). The results of the risk assessment indicate that species are exposed to elevated levels of phenol near point sources, but these levels represent only a minor risk to aquatic biota.

Ecological risk assessments of priority substances in Canada: Identification and resolution of difficult issues

Environment Canada has revised its guidance manual for ecological risk assessments of priority substances under the Canadian Environmental Protection Act. This paper briefly summarizes the guidance provided on: problem formulation; data collection and generation; analysis of entry, exposure and effects; and risk characterization. The purpose of this paper is to discuss some of the difficult issues common to all programs conducting ecological risk assessments of substances, and to describe the approaches the authors have taken. Example issues include: (1) how should low toxic effects be determined, (2) how should risks be quantified, and (3) how can the ecological consequences of exposures to substances be determined? Finally, comments are provided on the process followed during the preparation of the revised manual. These comments are provided because the authors believe that the open and transparent process followed was beneficial to the identification and resolution of these and other difficult issues.

Ecological risk assessment for Pacific salmon exposed to dimethoate in California

A probabilistic risk assessment of the potential direct and indirect effects of acute dimethoate exposure to salmon populations of concern was conducted for 3 evolutionarily significant units (ESUs) of Pacific salmon in California. These ESUs were the Sacramento River winter-run chinook, the California Central Valley spring-run chinook, and the California Central Valley steelhead. Refined acute exposures were estimated using the Soil and Water Assessment Tool, a river basin-scale model developed to quantify the impact of land-management practices in large, complex watersheds. Both direct effects (i.e., inhibition of brain acetylcholinesterase activity) and indirect effects (i.e., altered availability of aquatic invertebrate prey) were assessed. Risk to salmon and their aquatic invertebrate prey items was determined to be de minimis. Therefore, dimethoate is not expected to have direct or indirect adverse effects on Pacific salmon in these 3 ESUs. Environ Toxicol Chem 2017;36:532-543.

Ecological risk assessment for mink and short-tailed shrew exposed to PCBs, dioxins, and furans in the Housatonic River area

A probabilistic risk assessment was conducted to characterize risks to a representative piscivorous mammal (mink, Mustela vison) and a representative carnivorous mammal (short-tailed shrew, Blarina brevicauda) exposed to PCBs, dioxins, and furans in the Housatonic River area downstream of the General Electric (GE) facility in Pittsfield, Massachusetts. Contaminant exposure was estimated using a probabilistic total daily intake model and parameterized using life history information of each species and concentrations of PCBs, dioxins, and furans in prey collected in the Housatonic River study area. The effects assessment preferentially relied on dose-response curves but defaulted to benchmarks or other estimates of effect when there were insufficient toxicity data. The risk characterization used a weight of evidence approach. Up to 3 lines of evidence were used to estimate risks to the selected mammal species: 1) probabilistic exposure and effects modeling, 2) field surveys, and 3) species-specific feeding or field studies. The weight of evidence assessment indicated a high risk for mink and an intermediate risk for short-tailed shrew.

Deriving a water quality guideline for protection of aquatic communities exposed to triclosan in the Canadian environment

Triclosan is an antibacterial and antifungal chemical used in a variety of consumer products, including soaps, detergents, moisturizers, and cosmetics. Aquatic ecosystems may be exposed to triclosan following the release of remaining residues in wastewater effluents and biosolids. In December 2017, Environment and Climate Change Canada (ECCC) released a federal environmental quality guideline (FEQG) report that contained a federal water quality guideline (FWQG) for triclosan. This guideline will be used as an adjunct to the risk assessment and risk management of priority chemicals identified under the Government of Canadas Chemicals Management Plan (CMP). The FWQG value for triclosan (0.47 μg/L) was derived by ECCC using a hazardous concentration for 5% of species (HC5) from a species sensitivity distribution (SSD). We recalculated the FWQG after performing an independent analysis and evaluation of the available aquatic toxicity data for triclosan and compared our results with the ECCC FWQG value. Our independent analysis of the available aquatic toxicity data entailed conducting a literature search of all available and relevant studies, evaluating the quality and reliability of all studies considered using thorough and consistent study evaluation criteria, and thereby generating a data set of high-quality toxicity values. The selected data set includes 22 species spanning 5 taxonomic groups. An SSD was developed using this data set following the ECCC approaches. The HC5 from the SSD derived based on our validated data set is 0.76 μg/L. This HC5 value is slightly greater (i.e., less sensitive) than the value presented in ECCCs final FWQG. Integr Environ Assess Manag 2018;14:437-441.