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New High-throughput Methods to 

Estimate Chemical Exposure 

New High Throughput Methods to Estimate Chemical Exposure 

FIFRA Scientific Advisory Panel Meeting 

July 29 – August 1, 2014 

INTRODUCTION TO THE CHARGE QUESTIONS 

The risk posed by any of the thousands of untested man-made chemicals in our environment is a 

function of both the hazard presented by the chemical, and the extent of exposure. EPA’s use of 

rapid bioactivity screening, or high throughput screening (HTS), for the Endocrine Disruptor 

Screening Program (EDSP) was reviewed by a Scientific Advisory Panel (SAP) in January, 

2013. While many recent advances have been made in high throughput bioactivity profiling, 

concurrent advances in rapid, quantitative prediction of human and ecological exposures have 

been lacking, despite the importance of both measures for an integrated approach to prioritizing 

and initial screening chemicals in the EDSP universe. Relatively few chemicals have estimates of 

exposure intake or toxicokinetics (TK), limiting the ability to integrate elements of activity or 

hazard with exposure in early stages of chemical prioritization and screening. 

A recent report by the National Research Council of the National Academies, “Exposure Science 

in the 21st Century: a Vision and a Strategy”, described a number of examples of both chemical 

toxicity and risk evaluation in critical need of quantitative exposure predictions. These examples 

included the prioritization and screening of chemicals for targeted toxicity testing, focused 

exposure assessments or monitoring studies, and quantification of population vulnerability. 

ExpoCast is an EPA Office of Research and Development initiative to develop the approaches 

and tools necessary for rapidly prioritizing thousands of chemicals based on the potential for 

human and ecological exposure. This focus for ExpoCast is distinct from many existing 

exposure tools that support either screening level assessments on a per chemical basis or full 

chemical-specific regulatory risk assessments. These traditional exposure tools are lower 

throughput, requiring considerable data to make predictions of sufficient precision for a full risk 

assessment. ExpoCast efforts have focused on empirically assessing the uncertainty in highthroughput exposure (HTE) predictions by evaluation and calibration with available monitoring 

data. By using rigorous statistical techniques to reconcile HTE estimates based on the limited 

data that is available, we can empirically assess the uncertainty in these predictions. We refer to 

this framework as the Systematic Empirical Evaluation of Models (SEEM). We find that in some 

cases, even highly uncertain predictions may be useful, in combination with HTS, for integrated 

prioritization and initial screening of chemicals in the EDSP universe. 

The complexity of mathematical models for regulatory science must match the available data and 

application in order for their assumptions and conclusions to be defensible. In other words, the 

models must be fit for purpose. If the current resources and tools permit in depth study of only a 

handful of chemicals annually, then new tools requiring fewer resources must be developed to 

prioritize the thousands of untested chemicals in order to identify those chemicals most likely to 

be in need of further investigation with more traditional methods. 

This SAP will review the use of the SEEM framework and the underlying science that is 

intended to provide the necessary approaches and tools for High Throughput Exposure (HTE) to 
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New High-throughput Methods to 

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prioritize thousands of chemicals based on the potential for human and ecological exposure. In 

addition to exposure, this SAP will also review the high-throughput toxicokinetics (HTTK) 

methods to extrapolate from in vitro concentrations data to in vivo doses for chemicals that have 

been run through a battery of high-throughput endocrine screening assays (not to be confused 

with the EDSP tier 1 battery). HTTK provides a bridge between bioactivity in the HTS assays 

and exposure, by both predicting tissue concentrations due to exposure or inferring the 

administered doses needed to reach bioactive concentrations in vivo. 

The integration of HTE prediction and HTTK, integrated with HTS bioactivity profiling as an 

indicator of hazard, will allow for rapid prioritization and initial screening of chemicals in the 

EDSP universe. This SAP is requested to review the HTE and HTTK approaches, together with 

the characterization of associated uncertainty, in the context of the data poor landscape that 

exists for many EDSP chemicals, and with the future application in prioritization and screening 

in mind. The synthesis of high throughput activity or hazard and exposure prioritization tools 

will be reviewed by a future SAP. 

 
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New High-throughput Methods to 

Estimate Chemical Exposure 

Scientific Advisory Panel Meeting 

New High-throughput Methods to Estimate Chemical Exposure 

July 2014 

CHARGE QUESTIONS 

1. The Systematic Empirical Evaluation of Models (SEEM) Framework for Exposure 

Prioritization 

These charge questions address the science described in the Section entitled “Exposure 

Prioritization with ExpoCast Research.” The SEEM framework for evaluating high-throughput 

exposure (HTE) information (including descriptors, exposure factors, mechanistic models, and 

heuristics for thousands of chemicals) extrapolates from chemicals with monitoring data to those 

with no monitoring data. By comparing forward model predictions to exposure/doses inferred for 

the subset of chemicals with monitoring data, we are able to empirically calibrate our metamodel and provide an estimate of uncertainty in exposure predictions. 

1.1) In the absence of sufficient exposure information to estimate exposure for the 

majority of the chemicals of interest in the EDSP using EPA's historical low-throughput 

methods, please comment on whether the SEEM approach is scientifically sound and 

suitable for using HTE methods to estimate relative levels of chemical exposures and the 

associated uncertainty of these estimates for consideration in a prioritization approach. 

1.2) Please suggest the most important steps for EPA that could decrease uncertainties 

and increase confidence in using the HTE approach to predict exposures in various 

demographic groups (e.g., young children, women of child bearing age) for large 

numbers of chemicals. 

2. High Throughput Toxicokinetics (HTTK) and Reverse Toxicokinetics (RTK) 

These charge questions address the science described in the Section with the same name. TK can 

be used to provide an administered dose context to the concentrations showing bioactivity in the 

endocrine-related HTS assays. A lack of data on the TK of chemicals in organisms is a 

substantial impediment to providing this context. The recent development of HTTK methods 

provides a solution to this problem by measuring key TK parameters for each chemical. To date, 

HTTK data have been gathered on roughly 500 chemicals as part of the ExpoCast project. The 

HTTK assays can be incorporated into relatively simple in vitro-to-in vivo extrapolation (IVIVE) 

computational models to predict steady-state blood concentrations. HTTK assays combined with 

physiological information and quantitative structure activity relationships (QSAR) that predict 

tissue partitioning can be utilized in more complex, high-throughput physiologically-based TK 

(HTPBTK) models to predict relevant TK parameters such as area under the curve (AUC), 

maximum blood concentration (Cmax), and tissue and blood concentrations under non-steadystate conditions. For in vitro to in vivo extrapolation (IVIVE), reverse toxicokinetics (RTK) can 

be performed using either simple or more complex HTPBPK models to predict the administered 
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New High-throughput Methods to 

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dose (mg/kg BW/day) required to produce human tissue concentrations (μM) equal to 

concentrations that activate endocrine-related in vitro assays (e.g., ToxCast, Tox21). Although 

current models based on HTTK data allow for a significantly higher throughput than traditional 

in vivo studies, as with ExpoCast predictions, the faster and less data intensive predictions 

allowed by HTTK methods are associated with higher uncertainty compared to in vivo methods. 

This higher uncertainty is due in part to the lack of availability of in vitro methods to capture 

biological processes important to toxicokinetics (e.g., active transport, enterohepatic circulation, 

etc.). 

2.1) In the absence of sufficient empirical toxicokinetics information for the thousands of 

EDSP relevant chemicals, please comment on the approach of using HTTK, HTPBTK, 

IVIVE, and RTK for estimating chemical TK to provide an administered dose context to the 

concentrations showing bioactivity in the endocrine-related HTS assays. 

2.2) A comparison of the HTTK-predicted steady-state blood concentrations with in vivo

values from the literature suggests that the overall correlation is low, but that the discrepancy 

between the two can be predicted using a combination of chemical properties, quantitative 

structure activity relationships (QSAR), and cutoffs from the HTTK assays. Please comment 

on: a) how well this approach characterizes the uncertainty in the steady-state blood 

concentrations, and b) whether the identification of chemical classes that need additional TK 

investigation is useful in a chemical prioritization or initial screening context. 

2.3) Please comment on whether the assumptions made in these models are appropriate given 

the current state of the science and data limitations. 

2.4) Please suggest the most important steps EPA should take to improve the various kinetic 

models to provide rapid and cost-effective predictions for large number of chemicals. 

2.5) Please comment on the approaches presented in the present White Paper for comparing 

RTK-derived endocrine-active dose ranges with exposure predictions from ExpoCast. 

Discuss the strengths and limitations of these comparisons, and whether this or other 

approaches are suitable for clearly distinguishing chemicals with higher predicted doses from 

chemicals with lower predicted RTK adjusted doses. 

3. Future Direction 

These charge questions address the science described in the Section with the same name. Science 

is proceeding in three key areas to support high throughput exposure prioritization: 1) near-field 

(indoor or consumer use) exposures to humans; 2) ecological exposures; and 3) refinement of 

high-throughput toxicokinetics. For all three of these areas, ongoing science development efforts 

address the need for rapid prioritization and initial screening of EDSP and other chemicals. 

3.1) Please comment on the three key areas including whether there are other areas that are 

of equal or higher priority to support an integrated activity/hazard and exposure based 

prioritization and screening approach within the EDSP or other chemical programs. 

3.2) We propose applying the ExpoCast framework to ecological exposures using 

aggregated water monitoring data to evaluate the predictions of environmental fate and 
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New High-throughput Methods to 

Estimate Chemical Exposure 

transport models. Please identify other data, models or environmental media that may 

be of greater value in the initial model calibration and uncertainty analysis. 

3.3) Please identify other relatively high-throughput sources of exposure-related 

information that should be included in these three key areas and suggest how this 

information would be used to help prioritize chemicals. 

3.4) For the HTTK work going forward, please comment on additional studies that 

could be performed or approaches that could be taken to improve rapid and cost efficient 

predictions of TK for large numbers of chemicals.