Science Inventory

High-throughput methods for estimating food contact substance exposures to support risk-based chemical prioritization

Citation:

Isaacs, K. High-throughput methods for estimating food contact substance exposures to support risk-based chemical prioritization. 2018 Workshop: Predicting the safety of food contact articles: New science and digital opportunities, Zurich, SWITZERLAND, October 04, 2018.

Impact/Purpose:

This talk was presented by Dr. Kristin Isaacs as an invited talk at the Food Packaging Forum public workshop Predicting the safety of food contact articles: New science and digital opportunities on October 4, 2018 in Zurich, Switzerland. The talk describes a published high-throughput model of exposure to chemicals in food packaging and incorporation into consensus model predictions for 1000s of chemicals.

Description:

Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present methods to estimate HT exposures to chemicals migrating into food from food contact substances (FCS). These methods consisted of combining an empirical model of chemical migration with estimates of daily population food intakes derived from food diaries from the National Health and Nutrition Examination Survey (NHANES). A linear regression model for migration at equilibrium was developed by fitting available migration measurements as a function of temperature, food type (i.e., fatty, aqueous, acidic, alcoholic), initial chemical concentration in the FCS (C0) and chemical properties. The most predictive variables in the resulting model were C0, molecular weight, log Kow, and food type (R2=0.71, p<0.0001). Migration-based concentrations for 1009 chemicals identified via publicly-available data sources as being present in polymer FCSs were predicted for 12 food groups (combinations of 3 storage temperatures and food type). The model was parameterized with screening-level estimates of C0 based on the functional role of chemical in FCS. By combining these concentrations with daily intakes for food groups derived from NHANES, population ingestion exposures of chemical in mg/kg-bodyweight/day (mg/kg-BW/day) were estimated. Calibrated aggregate exposures were estimated for 1931 chemicals by fitting HT FCS and consumer product exposures to exposures inferred from NHANES biomonitoring (R2=0.61, p<0.001); both FCS and consumer product pathway exposures were significantly predictive of inferred exposures. Including the FCS pathway significantly impacted the ratio of predicted exposures to those estimated to produce steady-state blood concentrations equal to in-vitro bioactive concentrations. While these HT methods have large uncertainties (and thus may not be appropriate for assessments of single chemicals), they can provide critical refinement to aggregate exposure predictions used in risk-based chemical priority–setting.

Record Details:

Record Type:DOCUMENT( PRESENTATION/ SLIDE)
Product Published Date:10/04/2018
Record Last Revised:02/20/2019
OMB Category:Other
Record ID: 344168