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Actualizing research into practical tools: A case study of GenRA, a new read-across tool
Citation:
Helman, G., I. Shah, AND G. Patlewicz. Actualizing research into practical tools: A case study of GenRA, a new read-across tool. Presented at American Chemical Society, New Orleans, LA, March 18 - 22, 2018. https://doi.org/10.23645/epacomptox.6827069
Impact/Purpose:
This is an update of GenRA in terms of the latest analysis that has been performed and its implementation into the GenRA prototype tool. Presentation at the American Chemical Society meeting March 2018.
Description:
Read-across, a popular data gap filling technique traditionally relies on a thorough expert driven assessment. This 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 (derived from high throughput screening data from ToxCast) to derive read-across predictions of toxicity effects in in vivo repeat-dose toxicity studies. In translating the approach into a web-based tool, we anchored its development around the typical category workflow and structured this into a dynamic grid interface. The default starting point is to identify 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 in a flat file. Recent work has investigated physicochemical similarity and its impact in improving the read-across performance from the baseline GenRA. Using the Lipinski rule of 5 parameters, the performance for target organs aggregated over all study types was evaluated. In general, filtering structural analogues on the basis of physicochemical parameters led to a decrease in performance, whereas expanding the analogue identification to optimize both physicochemical and structural similarity resulted in improved performance. We describe the functionality and features of the GenRA web application which has recently been released in open beta including ongoing refinements such as point of departure prediction and extending the chemical space to cover all of the DSSTox inventory. 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.
URLs/Downloads:
DOI: Actualizing research into practical tools: A case study of GenRA, a new read-across tool
ACS_GHELMAN_GENRA_GP090318_JC_CLEARED.PDF (PDF, NA pp, 896.037 KB, about PDF)