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Case study of read-across predictions using a Generalized Read-Across (GenRA) Approach (10th World Congress)
Citation:
Helman, G., I. Shah, AND G. Patlewicz. Case study of read-across predictions using a Generalized Read-Across (GenRA) Approach (10th World Congress). Presented at 10th World Congress on Alternatives and Animal Use in the Life Sciences, Seattle, WA, August 20 - 24, 2017.
Impact/Purpose:
platform presentation at the WC10 meeting in Seattle, WA
Description:
We developed the Generalized Read-Across (GenRA) approach to facilitate automated, algorithmic read across predictions. GenRA uses in vitro bioactivity data in conjunction with chemical information to predict up to 574 different apical outcomes from repeat-dose toxicity studies. Here, we use a case-study approach to characterize GenRA read-across predictions for a group of reference chemicals. We highlight examples where physicochemical parameters such as LogKow are helpful in refining the read-across predictions. These efforts demonstrate the utility of automated approaches for chemical analogue selection using algorithmic read-across approaches. EPA disclaimer: The views expressed in this abstract are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.
URLs/Downloads:
WCONGRESS ABSTRACT_HELMAN_FINAL_240317.PDF (PDF, NA pp, 78.631 KB, about PDF)WCONGRESS_GH_FINAL.PDF (PDF, NA pp, 524.063 KB, about PDF)