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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.

Threshold of Toxicological Concern (TTC) aids assessment of human health risks from exposure to low levels of chemicals when toxicity data are limited. The objective here was to explore the potential refinement of exposure for applying the oral TTC to chemicals found in cosmetic products, for which there are limited dermal absorption data. A decision tree was constructed to estimate the dermally absorbed amount of chemical, based on typical skin exposure scenarios. Dermal absorption was calculated using an established predictive algorithm to derive the maximum skin flux adjusted to the actual ‘dose’ applied. The predicted systemic availability (assuming no local metabolism), can then be ranked against the oral TTC for the relevant structural class. The predictive approach has been evaluated by deriving the experimental/prediction ratio for systemic availability for 22 cosmetic chemical exposure scenarios. These emphasise that estimation of skin penetration may be challenging for penetration enhancing formulations, short application times with incomplete rinse-off, or significant metabolism. While there were a few exceptions, the experiment-to-prediction ratios mostly fell within a factor of 10 of the ideal value of 1. It can be concluded therefore, that the approach is fit-for-purpose when used as a screening and prioritisation tool.