High-throughput screening and environmental risk assessment: State of the science and emerging applications

Abstract

In 2007 the United States National Research Council (NRC) published a vision for toxicity testing in the 21st century that emphasized the use of in vitro high-throughput screening (HTS) methods and predictive models as an alternative to in vivo animal testing. In the present study we examine the state of the science of HTS and the progress that has been made in implementing and expanding on the NRC vision, as well as challenges to implementation that remain. Overall, significant progress has been made with regard to the availability of HTS data, aggregation of chemical property and toxicity information into online databases, and the development of various models and frameworks to support extrapolation of HTS data. However, HTS data and associated predictive models have not yet been widely applied in risk assessment. Major barriers include the disconnect between the endpoints measured in HTS assays and the assessment endpoints considered in risk assessments as well as the rapid pace at which new tools and models are evolving in contrast with the slow pace at which regulatory structures change. Nonetheless, there are opportunities for environmental scientists and policymakers alike to take an impactful role in the ongoing development and implementation of the NRC vision. Six specific areas for scientific coordination and/or policy engagement are identified. Environ Toxicol Chem 2019;38:12-26. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Keywords: Adverse outcome pathway; Computational toxicology; Effects-based monitoring; In vitro to in vivo extrapolation; Mixtures; Risk assessment.

Figure 1:

Integration of extrapolation models and frameworks required for more effective use of high throughput screening data in environmental risk assessment.

Figure 2:

Applications of HTS data in (A) screening potential human health risk(s) (Judson et al. 2011) and (B) screening ecological risk to fish as an example.

Figure 3.

Practical applications of HTS data for risk assessment using the EAR and BEQ approach and how the different approaches relate to each other. EC_y(i) = effect concentration at y effect level of compound/sample i; ACC = activity cut-off concentration (often close to EC₂₀(i))