Integrating publicly available information to screen potential candidates for chemical prioritization under the Toxic Substances Control Act: A proof of concept case study using genotoxicity and carcinogenicity

Abstract

The Toxic Substances Control Act (TSCA) became law in the U.S. in 1976 and was amended in 2016. The amended law requires the U.S. EPA to perform risk-based evaluations of existing chemicals. Here, we developed a tiered approach to screen potential candidates based on their genotoxicity and carcinogenicity information to inform the selection of candidate chemicals for prioritization under TSCA. The approach was underpinned by a large database of carcinogenicity and genotoxicity information that had been compiled from various public sources. Carcinogenicity data included weight-of-evidence human carcinogenicity evaluations and animal cancer data. Genotoxicity data included bacterial gene mutation data from the Salmonella (Ames) and Escherichia coli WP2 assays and chromosomal mutation (clastogenicity) data. Additionally, Ames and clastogenicity outcomes were predicted using the alert schemes within the OECD QSAR Toolbox and the Toxicity Estimation Software Tool (TEST). The evaluation workflows for carcinogenicity and genotoxicity were developed along with associated scoring schemes to make an overall outcome determination. For this case study, two sets of chemicals, the TSCA Active Inventory non-confidential portion list available on the EPA CompTox Chemicals Dashboard (33,364 chemicals, 'TSCA Active List') and a representative proof-of-concept (POC) set of 238 chemicals were profiled through the two workflows to make determinations of carcinogenicity and genotoxicity potential. Of the 33,364 substances on the 'TSCA Active List', overall calls could be made for 20,371 substances. Here 46.67%% (9507) of substances were non-genotoxic, 0.5% (103) were scored as inconclusive, 43.93% (8949) were predicted genotoxic and 8.9% (1812) were genotoxic. Overall calls for genotoxicity could be made for 225 of the 238 POC chemicals. Of these, 40.44% (91) were non-genotoxic, 2.67% (6) were inconclusive, 6.22% (14) were predicted genotoxic, and 50.67% (114) genotoxic. The approach shows promise as a means to identify potential candidates for prioritization from a genotoxicity and carcinogenicity perspective.

Keywords: Carcinogenicity; Genotoxicity; Mutagenicity; TSCA; Toxic Substance Control Act.

Figure 1.

Tiered evaluation process associated with the carcinogenicity domain. The workflow begins with the determination of human carcinogenicity from an authoritative source and ends with one of the dashed-line boxes. Solid-line boxes represent intermediate decision points. IG is the information-gathering flag.

Figure 2.

Tiered evaluation process associated with the genotoxicity domain. The process determines the gene and chromosomal (clastogenicity) mutagenicity of a chemical. IG is the information gathering flag.

Figure 3.

The first 50 records from the experimental genotoxicity dataset aggregated by substance to illustrate the number of studies by type.

Figure 4.

Histograms of the number of studies per chemical per aggregate study type. The experimental genotoxicity data was aggregated by substance and aggregate study type to determine how many studies had been conducted per substance of a certain type.

Figure 5.

Count plot showing how the 20,371 ‘TSCA Active List’ substances for which an overall call could be made were assigned to each of the genotoxicity scores based on the criteria provided in Table 2. In the plot, score 1 indicates absence of genotoxicity in experimental studies if available or predictions; score 2 indicates inconsistent experimental results; score 3 are predicted genotoxicity outcomes and score 4 are positive genotoxic outcomes in experimental studies.

Figure 6.

Count plot showing thow the 225 POC substances for which an overall call could be made were assigned to each of the genotoxicity scores based on the criteria provided in Table 2. In the plot, score 1 indicates absence of genotoxicity in experimental studies if available or predictions; score 2 indicates inconsistent experimental results; score 3 are predicted genotoxicity outcomes and score 4 are positive genotoxic outcomes in experimental studies.