How in silico and QSAR approaches can increase confidence in environmental hazard and risk assessment

Abstract

EDITOR'S NOTE:This article was generated from the session "Predictive models in ecotoxicology: Bridging the gap between scientific progress and regulatory applicability," presented at the 27th SETAC Europe Annual Meeting (May 2017, Brussels, Belgium). The session considered approaches used in ecotoxicology for understanding and predicting the effects of chemicals, from QSAR to ecological modelling. This series aims to critically analyze and debate application examples and future developments to increase the acceptability of predictive models by regulators, managers, NGOs, and other stakeholders. ABSTRACTIn 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. C 2018 SETAC

Strategies to apply 3Rs in preclinical testing

“…Thus, QSAR studies represent a good option to replace in vivo testing. In this sense, defined endpoint, unambiguous algorithm, defined domain of applicability, robustness, predictivity, and data curation must be mandatory principles to obtain an adequate and reliable QSAR result to ensure the success of this approach 20–22 …”

Predictive models in ecotoxicology: Bridging the gap between scientific progress and regulatory applicability—Remarks and research needs

“…Thomas and coworkers () describe a mechanistic approach that considers the mode of action of toxic chemicals and show how knowledge of the mode of action allows a better understanding of the mechanistic rationale that underlies QSAR models. The authors also show that, on the other hand, QSARs may help in the understanding of some aspects of the mode of action, such as the differences in the acute‐to‐chronic ratio for different classes of chemicals.…”

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

“…More recently there has been a growing recognition that classifying chemicals using the mechanism of action can add more confidence in toxicity prediction. 19 The MechoA scheme as one such example has recently been developed and available freely online is the KREATiS MechoA scheme 20 to predict the toxicity mechanism based on the chemical structure. 21,22 The recent scheme of Sapounidou et al 23,24 is another such example which follows an analogous approach to the MechoA scheme.…”