Volume 15, Issue 1 p. 40-50
Special Series

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

Paul C Thomas

Corresponding Author

Paul C Thomas

KREATiS SAS, L'Isle D'Abeau, France

Address correspondence to [email protected]

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Pascal Bicherel

Pascal Bicherel

KREATiS SAS, L'Isle D'Abeau, France

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Franklin J Bauer

Franklin J Bauer

KREATiS SAS, L'Isle D'Abeau, France

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First published: 17 November 2018
Citations: 18
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.

ABSTRACT

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