Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that could help in meeting these challenges. However, to use mechanistic data to support chemical assessments, there is a need for effective translation of this information into endpoints meaningful to ecological risk-effects on survival, development, and reproduction in individual organisms and, by extension, impacts on populations. Here we discuss a framework designed for this purpose, the adverse outcome pathway (AOP). An AOP is a conceptual construct that portrays existing knowledge concerning the linkage between a direct molecular initiating event and an adverse outcome at a biological level of organization relevant to risk assessment. The practical utility of AOPs for ecological risk assessment of chemicals is illustrated using five case examples. The examples demonstrate how the AOP concept can focus toxicity testing in terms of species and endpoint selection, enhance across-chemical extrapolation, and support prediction of mixture effects. The examples also show how AOPs facilitate use of molecular or biochemical endpoints (sometimes referred to as biomarkers) for forecasting chemical impacts on individuals and populations. In the concluding sections of the paper, we discuss how AOPs can help to guide research that supports chemical risk assessments and advocate for the incorporation of this approach into a broader systems biology framework.

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Models were developed to predict the bioconcentration of well-metabolized chemicals by rainbow trout. The models employ intrinsic clearance data from in vitro studies with liver S9 fractions or isolated hepatocytes to estimate a liver clearance rate, which is extrapolated to a whole-body biotransformation rate constant (kMET ). Estimated kMET values are then used as inputs to a mass-balance bioconcentration prediction model. An updated algorithm based on measured binding values in trout is used to predict unbound chemical fractions in blood, while other model parameters are designed to be representative of small fish typically used in whole-animal bioconcentration testing efforts. Overall model behavior was shown to be strongly dependent on the relative hydrophobicity of the test compound and assumed rate of in vitro activity. The results of a restricted sensitivity analysis highlight critical research needs and provide guidance on the use of in vitro biotransformation data in a tiered approach to bioaccumulation assessment.

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Abstract:The objective of the present study was to review the current knowledge regarding the bioaccumulation potential of ionizable organic compounds (IOCs), with a focus on the availability of empirical data for fish. Aspects of the bioaccumulation potential of IOCs in fish that can be characterized relatively well include the pH dependence of gill uptake and elimination, uptake in the gut, and sorption to phospholipids (membrane-water partitioning). Key challenges include the lack of empirical data for biotransformation and binding in plasma. Fish possess a diverse array of proteins that may transport IOCs across cell membranes. Except in a few cases, however, the significance of this transport for uptake and accumulation of environmental contaminants is unknown. Two case studies are presented. The first describes modeled effects of pH and biotransformation on the bioconcentration of organic acids and bases, while the second employs an updated model to investigate factors responsible for accumulation of perfluorinated alkyl acids. The perfluorinated alkyl acid case study is notable insofar as it illustrates the likely importance of membrane transporters in the kidney and highlights the potential value of read-across approaches. Recognizing the current need to perform bioaccumulation hazard assessments and ecological and exposure risk assessment for IOCs, the authors provide a tiered strategy that progresses (as needed) from conservative assumptions (models and associated data) to more sophisticated models requiring chemical-specific information. Environ Toxicol Chem 2017;36:882-897. # 2016 SETAC

The occurrence of pharmaceuticals in the environment presents a challenge of growing concern. In contrast to many industrial compounds, pharmaceuticals undergo extensive testing prior to their introduction to the environment. In principle, therefore, it may be possible to employ existing pharmacological safety data using biological "read-across" methods to support screening-level bioaccumulation environmental risk assessment. However, few approaches and robust empirical data sets exist, particularly for comparative pharmacokinetic applications. For many pharmaceuticals, the primary cytochrome P450 (CYP) enzymes responsible for their metabolism have been identified in humans. The purpose of the present study was to employ a comparative approach to determine whether rainbow trout biotransform pharmaceuticals known to be substrates for specific human CYPs. Seven compounds were selected based on their primary metabolism in humans by CYP3A4, CYP2D6, or CYP2C9. Five additional test compounds are known to be substrates for multiple CYPs. Metabolism by rainbow trout liver S9 fractions was evaluated using a substrate-depletion approach, which provided an estimate of intrinsic hepatic clearance (CLIN VITRO,INT ). An isotope dilution liquid chromatography-tandem mass spectrometry method was employed for quantitation of parent chemical concentrations. Only 2 general CYP substrates demonstrated measurable levels of substrate depletion. No significant biotransformation was observed for known substrates of human CYP2D6, CYP2C9, or CYP3A4. The results of this study provide novel information for therapeutics that fish models are likely to metabolize based on existing mammalian data. Further, these results suggest that pharmaceuticals may possess a greater tendency to bioaccumulate in fish than previously anticipated.