1 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 thous ands of untested man-made chem icals in our environment is a function of both the hazard presented by the chemi cal, and the extent of exposure. EPA’s use of rapid bioactivity screening, or high throughput sc reening (HTS), for the Endocrine Disruptor Screening Program (EDSP) was reviewed by a Sc ientific Advisory Panel (SAP) in January, 2013. While many recent advances have been made in high throughput bioactivity profiling, concurrent advances in rapid, quantitative pred iction of human and ecolo gical exposures have been lacking, despite the importa nce of both measures for an inte grated approach to prioritizing and initial screening chemicals in the EDSP univers e. Relatively few chemicals have estimates of exposure intake or toxicokinetics (TK), limiting th e 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”, desc ribed a number of exam ples of both chemical toxicity and risk evaluation in critical need of quantitative expo sure predictions. These examples included the prioritization and sc reening of chemicals for target ed toxicity testing, focused exposure assessments or monitoring studies, and quantification of population vulnerability.

ExpoCast is an EPA Office of Research and Deve lopment initiative to develop the approaches and tools necessary for rapidly prioritizing t housands 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 le vel 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 pred ictions of sufficient precision for a full risk assessment. ExpoCast efforts have focused on empirically assessing th e uncertainty in highthroughput exposure (HTE) predictio ns by evaluation and calibrati on 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 Eval uation of Models (SEEM). We find that in some cases, even highly uncertain predic tions 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 conc lusions to be defensible. In other words, the models must be fit for purpose. If the current re sources and tools permit in depth study of only a handful of chemicals annually, th en new tools requiring fewer reso urces must be developed to prioritize the thousands of unteste d 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 fr amework and the underlying science that is intended to provide the necessary approaches and tools for High Throughput Exposure (HTE) to2 New High-throughput Methods to Estimate Chemical Exposure prioritize thousands of chemicals based on the po tential for human and ecological exposure. In addition to exposure, this SAP will also revi ew 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 hi gh-throughput endocrine screening a ssays (not to be confused with the EDSP tier 1 battery). HTTK provides a br idge between bioactivity in the HTS assays and exposure, by both predicting tissue concen trations due to expos ure or inferring the administered doses needed to reach bioactive concentrations in vivo

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The integration of HTE predicti on and HTTK, integrated with HTS bioactivity profiling as an indicator of hazard, will allow for rapid prioritization a nd 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 futu re application in prio ritization and screening in mind. The synthesis of high throughput activity or hazard and exposure prioritization tools will be reviewed by a future SAP.3 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 Re search.” The SEEM framework for evaluating high-throughput exposure (HTE) information (including descriptor s, exposure factors, mechanistic models, and heuristics for thousands of chemi cals) extrapolates from chemical s with monitoring data to those with no monitoring data. By comp aring 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 rela tive levels of chemical exposures and the associated uncertainty of these estimates fo r consideration in a pr ioritization approach.

1.2) Please suggest the most important steps fo r EPA that could decrease uncertainties and increase confidence in using the HTE a pproach to predict exposures in various demographic groups (e.g., young children, wome n of child beari ng age) for large

numbers of chemicals.

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

These charge questions address the science descri bed in the Section with the same name. TK can be used to provide an administer ed dose context to the concentra tions 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 contex t. 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 ch emicals as part of th e ExpoCast project. The HTTK assays can be incorporat ed into relatively simple in vitro -to- in vivo extrapolation (IVIVE) computational models to predict steady-state blo od concentrations. HTTK assays combined with physiological information and quantitative structur e activity relationships (QSAR) that predict tissue partitioning can be utilized in more complex, high-throughput physiologically-based TK (HTPBTK) models to predict re levant TK parameters such as area under the curve (AUC), maximum blood concentration (Cmax), and tissu e and blood concentratio ns under non-steadystate conditions. For in vitro to in vivo extrapolation (IVIVE), reverse toxicokinetics (RTK) can be performed using either simple or more comp lex HTPBPK models to predict the administered4 New High-throughput Methods to Estimate Chemical Exposure dose (mg/kg BW/day) required to produce human tissue concentrations (μM) equal to concentrations that act ivate endocrine-related in vitro assays (e.g., ToxCast, Tox21). Although current models based on HTTK data allow for a significantly higher thro ughput than traditional

in vivo studies, as with ExpoCast predictions, the faster and less data intensive predictions allowed by HTTK methods ar e 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 trans port, enterohepatic circulation, etc.).

2.1) In the absence of sufficient empirical toxic okinetics 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 st eady-state blood con centrations with in vivo

values from the literatu re suggests that the overall correlati on is low, but that the discrepancy between the two can be predicte d using a combination of chem ical properties, quantitative structure activity relationships (QSAR), and cu toffs from the HTTK assays. Please comment on: a) how well this approach characterizes the uncertainty in the steady-state blood concentrations, and b) whether th e identification of ch emical classes that need additional TK investigation is useful in a chemical pr ioritization or initial screening context. 2.3) Please comment on whether the a ssumptions made in these m odels 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 pr edictions 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 thes e comparisons, and whether this or other approaches are suitable for clearly distinguishi ng chemicals with highe r predicted doses from chemicals with lower predicted RTK adjusted doses.

3. Future Direction

These charge questions address the science descri bed in the Section with the same name. Science is proceeding in three key areas to support high throughput exposure prioriti zation: 1) near-field (indoor or consumer use) exposures to humans; 2) ecological exposures; and 3) refinement of high-throughput toxicokinetics. Fo r all three of these areas, ongoi ng science development efforts address the need for rapid prioritization and in itial 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 in tegrated activity/hazard and exposure based prioritization and screening approach with in the EDSP or other chemical programs. 3.2) We propose applying the ExpoCast framew ork to ecological exposures using aggregated water monitoring data to evaluate the predictions of environmental fate and5 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 m odel 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, pleas e comment on additi onal studies that could be performed or approaches that could be taken to improve rapid and cost efficient predictions of TK for larg e numbers of chemicals.