Abstract
Regulatory agencies across the world are facing the challenge of performing risk-based prioritization of thousands of chemicals in commerce. Here, we present an approach using the Threshold of Toxicological Concern (TTC) combined with heuristic high-throughput exposure (HTE) modelling to rank order chemicals for further evaluation. Accordingly, for risk-based prioritization, chemicals with exposures > TTC would be ranked as higher priority for further evaluation whereas substances with exposures < TTC would be ranked as lower priority. An initial proof of concept, using a dataset of 7986 substances with previously modeled median and upper 95% credible interval (UCI) total daily median exposure rates showed fewer than 5% of substances had UCI exposures > the Cramer Class III TTC (1.5 μg/kg-day). We extended the analysis by profiling the same dataset through the TTC workflow published by Kroes et al. (2004) which accounts for known exclusions to the TTC as well as structural alerts. UCI exposures were then compared to the appropriate class-specific TTC. None of the substances categorized as Cramer Class I or Cramer Class II exceeded their respective TTC values and no more than 2% of substances categorized as Cramer Class III or acetylcholinesterase inhibitors exceeded their respective TTC values. The modeled UCI exposures for the majority of the 1853 chemicals with genotoxicity structural alerts did exceed the TTC of 0.0025 μg/kg-day, but only 79 substances exceeded this TTC if median exposure values were used. For substances for which UCI exposures exceeded relevant TTC values, we highlight possible approaches for consideration to refine the HTE: TTC approach. Overall, coupling TTC with HTE offers promise as a pragmatic first step in ranking substances as part of a risk-based prioritization approach.
Highlights
The last decade has seen an ever-increasing number of regulatory frameworks being implemented for chemical safety evaluation
To test the feasibility of this approach, we initially assumed none of the 7986 substances in the dataset were automatically excluded from the Threshold of Toxicological Concern (TTC) approach or contained structural alerts that raised a concern for potential genotoxicity
4.1 Initial Evaluation for Proof of Concept. To first investigate this approach, we assumed none of the substances were automatically excluded from the TTC approach or contained structural alerts that raised a concern for potential genotoxicity
Summary
The last decade has seen an ever-increasing number of regulatory frameworks being implemented for chemical safety evaluation. Approaches for conducting risk-based prioritization are not new, and, in various forms, they represent an important component of regulatory frameworks in many countries, including Australia, Canada, US and the EU (summarized in Supplemental Material) This is challenging in the US since the TSCA requires the US EPA to perform risk-based prioritization of chemicals in commerce and for high-priority substances, develop risk evaluations that integrate toxicity data with exposure information derived from intended conditions of use [5]. There has been an acceleration of exposure science initiatives focused on deriving exposure estimates so that these advanced methods can generate exposure information for integrating with 21st century toxicity information to enable risk-based decision-making One such example is the ExpoCast initiative by US EPA that has been instrumental in developing mechanistic and heuristic models for making high-throughput exposure (HTE) predictions that can be rapidly parameterized for thousands of chemicals. An example has recently been published using TTC within the RISK21 project for prioritizing potential drinking water contaminants based on theoretical exposures derived from water solubilities [17]
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