Characterizing chemical exposure from biomonitoring data using the Exposure Related Dose Estimating Model (ERDEM)
C.C. Dary1, P.G. Georgopoulus2, D.A. Vallero1, R. Tornero-Velez1, M. Morgan1, M. Okino1, M. Dellarco3, F. Power1, J.N. Blancato4
1USEPA, National Exposure Research Laboratory, Research Triangle Park, NC; 2Environmental & Occupational Health Sciences Institute, Piscataway, NJ; 3USEPA National Center for Environmental Assessment, Washington DC; 4USEPA, National Center for Computational Toxicology, Research Triangle Park, NC
The Exposure Related Dose Estimating Model (ERDEM) serves as a physiologically based pharmacokinetic (PBPK) and pharmacodynamic (PD) modeling platform linking exposure with biomarker data in biological fluids. The PBPK model is expected to be representative of the chemicals of interest and complete with respect to the absorption, distribution, metabolism, and elimination (ADME) for tissue concentrations and elimination profiles. The success of dose reconstruction of exposure is dependent on the quality and integrity of the PBPK model, the sampling design for the biomarker data, and knowledge about the exposures that contribute to the dose response outcomes. However from our understanding, dose reconstruction is an anecdotal or meta-analytical exercise. Few, if any, studies were designed with dose reconstruction in mind. They frequently lack sufficient exposure information such that exposure events and pathways are often speculative in nature. Success in dose reconstruction is, therefore, dependent on the research “assets” gleaned from a host of loosely connected studies designed and performed at various levels of complexity and compliance with QA strictures. We examined case studies that span general epidemiological surveys to controlled laboratory studies with various levels of inherent and statistical uncertainty that might serve to connect exposure with biomonitoring outcomes through the use of PBPK/PD models. We anticipate that this approach will enable us to identify the key exposure response characteristics that are essential to develop more complete dose reconstruction estimates in the future.
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