Read-across, a popular data gap filling technique, traditionally relies on a thorough expert assessment. This approach can lead to inconsistent predictions, has limitations in terms of the numbers of chemicals that can be evaluated and offers little insight into the generalizability of the approach or its performance. We sought to evaluate the baseline performance of read-across for a large set of chemicals in a systematic, objective and reproducible manner and to provide quantitative measures of uncertainty for the predictions derived. The approach developed, generalized read-across (GenRA), relies on chemical descriptor information and/or in vitro bioactivity data (from ToxCast high throughput screening data) to derive read-across predictions of effects observed in in vivo repeat-dose toxicity studies. A web-based GenRA tool was then developed anchored around the established category workflow and a dynamic grid interface structure. The default starting point is identifying source analogues with associated in vivo data on the basis of chemical fingerprints. The next step is to analyze the scope and quantity of available data (both in vitro and in vivo). The third step generates a data matrix in order to evaluate the analogues – in terms of their consistency and concordance of effects across the different toxicity effects. The final steps involve generating a GenRA prediction and exporting the predictions. Here we describe the functionality and features of the GenRA web application which has recently been released as a new feature in the US EPA CompTox Chemistry Dashboard. Users are able to search the dashboard for a substance of interest, browse available information including toxicity information and then derive GenRA predictions. GenRA offers a novel and practical means of being able to perform objective read-across that can be helpful in screening level hazard assessments. This abstract does not necessarily represent U.S. EPA policy.

Translating research into practical tools: A case study of GenRA, a new read-across tool

256th National Meeting (2018)

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