Incorporating exposure information into the toxicological prioritization index decision support framework

The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to potential for endocrine disruption. However, exposure information is required along with hazard information to prioritize chemicals for further testing. The goal of this analysis is to demonstrate the utility of the ToxPi framework for incorporating exposure information to rank chemicals and improve understanding of key exposure surrogates. The ToxPi tool was applied to common exposure surrogates (i.e., fate parameters, manufacturing volume, and occurrence measurements) and the relationship between resulting rankings and higher-tiered exposure estimates was investigated. As information more directly relevant to human exposure potential is incorporated, relative rank of chemicals changes. Binned ToxPi results are shown to be consistent with chemical priorities based on crude measures of population-level exposure for a limited set of chemicals. However, these bins are not predictive of higher tiered estimates of exposure such as those developed for pesticide registration. Although rankings based on exposure surrogates are used in a variety of contexts, analysis of the relevance of these tools is challenging. The ToxPi framework can be used to gain insight into the factors driving these rankings and aid identification of key exposure metrics. Additional exposure data is required to build confidence in exposure-based chemical prioritization.

► We apply a decision support tool to incorporate exposure surrogates and prioritize chemicals based on exposure potentials.
► The ranking scheme is qualitatively compared with NHANES biomonitoring data and with chronic dietary exposure estimates.
► The ToxPi tool facilitates a high level view of large amount of exposure information.
► This knowledge-driven approach allows for the key drivers of exposure potential to be identified efficiently.
► Studies are needed to understand relationship between exposure surrogates, screening assessment, biomonitoring data.