EPA-Expo-Box (A Toolbox for Exposure Assessors)
(Biomonitoring and Reverse Dosimetry)
As described on the overview page for this toolset, exposure reconstruction is one of the three main approaches to estimating exposure. Exposure reconstruction differs from the other two approaches discussed in the Approaches Tool Set (i.e., scenario evaluation and direct measurement) in that exposure dose is estimated from internal body measurements rather than from external measurements. (See the Indirect Estimation and Direct Measurement Modules in EPA-Expo-Box for information and resources on these other approaches.)
Exposure reconstruction is an approach that allows for estimates of exposure and absorbed dose using biomarker data (U.S. EPA, 2012). Stated another way, exposure reconstruction uses information collected following exposure and "downstream" of the point of exposure, whereas scenario evaluation and direct measurement use information collected prior to exposure and "upstream" of the point of exposure. Successfully performing exposure reconstruction requires modeling tools such as pharmacokinetic (PK) models and the data necessary to run these models, physiological parameters, and the biomarker measurements themselves.
Biomonitoring data are necessary for exposure reconstruction. Biomonitoring involves analyzing human samples, such as tissues and body fluids, to determine contaminant or biomarker concentrations (U.S. EPA, 1992). Biomarkers are the cellular, biochemical, analytical, or molecular measures obtained via biomonitoring from biological media (e.g., tissues, cells, fluids) that indicate exposure to a chemical (U.S. EPA, 1992). A particular metabolite identified in urine, for example, might be a biomarker for exposure to the parent (metabolized) chemical. Blood lead levels can be measured to determine if a child has been exposed to lead.
Biomonitoring data can be combined with PK models to reconstruct or estimate the amount of chemical a person was exposed to (i.e., the exposure dose). PK models simulate the distribution and movement of chemicals within a living system using knowledge of quantitative relationships (e.g., the transfer rate of chemicals between the blood and the liver). PK models can also be applied to predict an internal dose or biomarker concentration using the intake dose.
The primary benefit of reconstructing exposure using biomonitoring data is that this approach can be used to quantify both aggregate exposure (exposure to a single chemical from all sources, routes, and pathways) and cumulative exposure (exposure to multiple chemicals that cause the same effect via a common mechanism). However, when evaluating biomonitoring data to estimate dose, the assessor must still try to understand the implications of different routes of exposure (e.g., inhalation, ingestion, or dermal exposure followed by absorption, distribution, etc.), internal metabolism (e.g., formation of metabolites), and other contributing factors. Irrespective of whether they are used in a PK model for exposure reconstruction, biomonitoring data present a potentially powerful set of information for characterizing exposure.