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Incorporating exposure information into the toxicological prioritization index decision support framework
Citation:
GANGWAL, S., D. REIF, S. MOSHER, P. P. EGEGHY, J. F. WAMBAUGH, R. JUDSON, AND E. A. COHEN-HUBAL. Incorporating exposure information into the toxicological prioritization index decision support framework . SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier Ireland Limited, Limerick, Ireland, 435-436C:316-325, (2012).
Impact/Purpose:
Application of the ToxPi decision support approach to evaluate exposure potential facilitates a high level view of large amounts of information, semi-quantitative analysis of the value of available exposure surrogates for comparing chemicals, and efficient identification of chemicals of concern. By using this type of knowledge-driven approach, key drivers for exposure potential can be identified and resources focused on the most significant gaps in understanding measurement data. The ToxPi platform provides context for incorporation of exposure data along with hazard information into chemical prioritization schemes as well as for the application and further development of exposure models. In general, however, the analyses conducted here for relatively data rich compounds demonstrate the need for further studies to understand the relationship between simple exposure surrogates, tiered screening-level exposure assessments, and population-level biomonitoring data. Capturing the complex source-to-dose system in an efficient prioritization scheme will require selection and development of metrics and surrogates that can confidently be used to predict key elements of exposure space.
Description:
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.
