You are here:
Transitioning the Generalised Read-Across approach (GenRA) to quantitative predictions: A case study using acute oral toxicity data
Citation:
Helman, G., I. Shah, AND G. Patlewicz. Transitioning the Generalised Read-Across approach (GenRA) to quantitative predictions: A case study using acute oral toxicity data. Computational Toxicology. Elsevier B.V., Amsterdam, Netherlands, 12(November 2019):100097, (2019). https://doi.org/10.1016/j.comtox.2019.100097
Impact/Purpose:
Extending the scope of GenRA from binary qualitative predictions to quantitative predictions using a dataset of LD50 acute rat oral studies as a case study.
Description:
Objective read-across approaches continue to evolve as does their utility in the field of risk assessment. Previously we presented our generalized read-across (GenRA) approach (Shah et al., 2016), which utilizes chemical descriptor and/or in vitro bioactivity data to make read-across predictions on the basis of the similarity weighted average of nearest neighbors. The current public version of GenRA predicts 574 apical outcomes as a binary call from repeat dose toxicity studies available in ToxRefDB (Helman et al., 2019). Here we investigated the application of GenRA to quantitative values, specifically using a large dataset of rat oral acute LD50 toxicity data (LD50 values for 7011 discrete chemicals) that had been collected under the auspices of the ICCVAM acute toxicity workgroup (ATWG). GenRA LD50 predictions were made based on the following criteria – chemicals were characterized by Morgan chemical fingerprints with a minimum similarity threshold of 0.5 and a maximum of 10 nearest neighbors over the entire dataset. An R2 value of 0.61 and RMSE of 0.58 was achieved based on these parameters. Monte Carlo cross validation was then used to estimate confidence in the R2. Cross validated R2 values were found to fall in the range of 0.52 to 0.69. However, when evaluating GenRA locally to clusters of mechanistically or structurally-similar chemicals, average R2 values improved up to 0.91. GenRA can be extended to make reasonable quantitative predictions of acute oral rodent toxicity with improved performance exhibited for specific local domains.
URLs/Downloads:
DOI: Transitioning the Generalised Read-Across approach (GenRA) to quantitative predictions: A case study using acute oral toxicity data