Search

The Threshold of Toxicological Concern (TTC) for non-genotoxic substances, a risk assessment tool to establish safe exposure levels for chemicals with insufficient toxicological data, is based on the 5th percentile of cumulated distributions of Point of Departures in a high amount of repeat-dose, developmental and reproductive toxicity studies, grouped by Cramer Classes. The lack of organosilicon compounds in this dataset has resulted in regulatory concerns over the applicability of the TTC concept for this chemistry. We collected publicly available, scientifically robust oral repeat-dose and DART studies for 71 organosilicon substances for inclusion in the existing TTC dataset, using criteria for evaluation of studies and derivation of points of departure analogous to the Munro and COSMOS TTC publications. The resulting 5th percentile of this dataset was 13-fold higher than the 5th percentile for Cramer Class III compounds reported by Munro (which is the default for silicon-containing substances). Both the existing TTC for Cramer Class III compounds from Munro (1.5 μg/kg bw/day) and the COSMOS TTC (2.3 μg/kg bw/day), recommended by the SCCS for cosmetics-related substances, provide a conservative and sufficiently protective approach for this class of chemistry.

The multi-compound, and multi-dose (MC-MD) route physiologically based pharmacokinetic (PBPK) model for cyclic siloxanes reported by McMullin et al. (2016) brought together the series of models for octamethylcyclotetrasiloxane (D4) and decamethylcyclopentasiloxane (D5) in rat and human into a unified code structure that would allow simulation of both compounds following the inhalation and dermal routes of exposure. The refined MC-MD PBPK model presented here expands upon this effort to include representation of rat kinetic data in plasma, tissues and exhaled breath for the parent compounds after oral bolus administration. Additional refinements were made with regards to hepatic induction of metabolism in the liver and allometric scaling of rate constants for the deep tissue compartments which will allow the MC-MD model to be used in uncertainty analysis. Overall, the refined MC-MD model was able to reproduce both parent D4 and D5 kinetic data in rat and human after inhalation exposure (rat and human) or dermal exposure (human). The inclusion of sequestered (i.e., lipid associated) oral absorption into plasma after oral bolus dosing successfully described the lack of exhalation as well as the initial distribution of siloxane to the liver which was higher than simple partitioning from plasma would allow. The refined MC-MD PBPK model presented here can be incorporated into uncertainty and variability analysis and cross-species dosimetry for both D4 and D5.

The HESI-led RISK21 effort has developed a framework supporting the use of twenty-first century technology in obtaining and using information for chemical risk assessment. This framework represents a problem formulation-based, exposure-driven, tiered data acquisition approach that leads to an informed decision on human health safety to be made when sufficient evidence is available. It provides a transparent and consistent approach to evaluate information in order to maximize the ability of assessments to inform decisions and to optimize the use of resources. To demonstrate the application of the framework’s roadmap and matrix, this case study evaluates a large number of chemicals that could be present in drinking water. The focus is to prioritize which of these should be considered for human health risk as individual contaminants. The example evaluates 20 potential drinking water contaminants, using the tiered RISK21 approach in combination with graphical representation of information at each step, using the RISK21 matrix. Utilizing the framework, 11 of the 20 chemicals were assigned low priority based on available exposure data alone, which demonstrated that exposure was extremely low. The remaining nine chemicals were further evaluated, using refined estimates of toxicity based on readily available data, with three deemed high priority for further evaluation. In the present case study, it was determined that the greatest value of additional information would be from improved exposure models and not from additional hazard characterization.