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Information about acute fish toxicity is routinely required in many jurisdictions for environmental risk assessment of chem­icals. This information is typically obtained using a 96-hour juvenile fish test for lethality according to OECD test guideline (TG) 203 or equivalent regional guidelines. However, TG 203 has never been validated using the criteria currently required for new test methods including alternative methods. Characterization of the practicality and validity of TG 203 is important to provide a benchmark for alternative methods. This contribution systematically summarizes the available knowledge on limitations and uncertainties of TG 203, based on methodological, statistical, and biological consider­ations. Uncertainties stem from the historic flexibility (e.g., use of a broad range of species) and constraints of the basic test design (e.g., no replication). Other sources of uncertainty arise from environmental safety extrapolation based on TG 203 data. Environmental extrapolation models, combined with data from alternative methods, including mechanistic indicators of toxicity, may provide at least the same level of environmental protection. Yet, most importantly, the 3R advan­tages of alternative methods allow a better standardization, characterization, and an improved basic study design. This can enhance data reliability and thus facilitate the comparison of chemical toxicity, as well as the environmental classifi­cations and prediction of no-effect concentrations of chemicals. Combined with the 3R gains and the potential for higher throughput, a reliable assessment of more chemicals can be achieved, leading to improved environmental protection.

In silico methods are typically underrated in the current risk assessment paradigm, as evidenced by the recent document from the European Chemicals Agency (ECHA) on animal alternatives, in which quantitative structure-activity relationships (QSARs) were practically used only as a last resort. Their primary use is still to provide supporting evidence for read-across strategies or to add credence to experimental results of unknown or limited validity (old studies, studies without good laboratory practices [GLPs], limited information reported, etc.) in hazard assessment, but under the pressure of increasing burdens of testing, industry and regulators alike are at last warming to them. Nevertheless, their true potential for data-gap filling and for resolving sticking points in risk assessment methodology and beyond has yet to be recognized. We postulate that it is possible to go beyond the level of simply increasing confidence to the point of using in silico approaches to accurately predict results that cannot be resolved analytically. For example, under certain conditions it is possible to obtain meaningful results by in silico extrapolation for tests that would be technically impossible to conduct in the laboratory or at least extremely challenging to obtain reliable results. The following and other concepts are explored in this article: the mechanism of action (MechoA) of the substance should be determined, as an aid verifying that the QSAR model is applicable to the substance under review; accurate QSARs should be built with high-quality data that were not only curated but also validated with expert judgment; although a rule of thumb for acute to chronic ratios appears applicable for nonpolar narcotics, it seems unlikely that a "one-value-fits-all" answer exists for other MechoAs; a holistic approach to QSARs can be employed (via reverse engineering) to help validate or invalidate an experimental endpoint value on the basis of multiple experimental studies. Integr Environ Assess Manag 2019;15:40-50. © 2018 SETAC., (© 2018 SETAC.)