Science Inventory

Comparison of in silico, in vitro, and in vivo toxicity benchmarks suggests a role for ToxCast data in ecological hazard assessment

Citation:

Schaupp, C., E. Maloney, K. Mattingly, J. Olker, AND D. Villeneuve. Comparison of in silico, in vitro, and in vivo toxicity benchmarks suggests a role for ToxCast data in ecological hazard assessment. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 195(2):145-154, (2023). https://doi.org/10.1093/toxsci/kfad072

Impact/Purpose:

The advent of new approach methodologies (NAMs) has allowed for the high-throughput generation of in vitro toxicity data for thousands of chemicals. However, most publicly accessible NAMs data, such as those in ToxCast, are mammalian-centric and their relevance to ecological toxicology and risk assessment remains unresolved. In contrast, the Ecotoxicology Knowledgebase (ECOTOX) is the primary source for a wealth of peer-reviewed, animal-based ecotoxicity information. Because many pathways are relatively well conserved across taxa and NAMs data can be used to calculate point-of-departure (POD) estimates via concentration-response modeling, we were interested in comparing PODs derived from ToxCast and ECOTOX across 649 chemicals with appropriate data quality. (Toxicity estimates from QSARs were also included for comparison.) As such, this work represents an important step toward understanding the potential for using ToxCast data in an ecological context. Our findings suggest that the chemical-specific ToxCast cytotoxic burst values are as effective as QSARs for predicting in vivo toxicity. Furthermore, ToxCast activity concentrations about cutoff (ACCs) below the cytotoxic burst, while not an effective predictor of benchmark concentrations per se, can provide mechanistic insight for chemicals with unknown pathways of toxicity. Together, these findings point to a potentially valuable role for ToxCast data in helping prioritize chemicals for further in-depth evaluation of ecological risk. The integration of ToxCast data into ecological risk assessment is being actively pursued as part of a collaborative project with toxicologists at EPA’s Region 10 but has broad implications for other Regions and program offices interested in making greater use of available NAMs data for ecological hazard evaluation.

Description:

Large repositories of in vitro bioactivity data such as US EPA's Toxicity Forecaster (ToxCast) provide a wealth of publicly accessible toxicity information for thousands of chemicals. These data can be used to calculate point-of-departure (POD) estimates via concentration-response modeling that may serve as lower bound, protective estimates of in vivo effects. However, the data are predominantly based on mammalian models and discussions to date about their utility have largely focused on potential integration into human hazard assessment, rather than application to ecological risk assessment. The goal of the present study was to compare PODs based on (1) quantitative structure-activity relationships (QSARs), (2) the 5th centile of the activity concentration at cutoff (ACC), and (3) lower-bound cytotoxic burst (LCB) from ToxCast, with the distribution of in vivo PODs compiled in the Ecotoxicology Knowledgebase (ECOTOX). While overall correlation between ToxCast ACC5 and ECOTOX PODs for 649 chemicals was weak, there were significant associations among PODs based on LCB and ECOTOX, LCB and QSARs, and ECOTOX and QSARs. Certain classes of compounds showed moderate correlation across datasets (eg, antimicrobials/disinfectants), while others, such as organophosphate insecticides, did not. Unsurprisingly, more precise classifications of the data based on ECOTOX effect and endpoint type (eg, apical vs biochemical; acute vs chronic) had a significant effect on overall relationships. Results of this research help to define appropriate roles for data from new approach methodologies in chemical prioritization and screening of ecological hazards.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:09/28/2023
Record Last Revised:12/27/2023
OMB Category:Other
Record ID: 359993