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OTHER REGULATORY APPLICATIONS
Impact/Purpose:
There will be additional objectives in response to the future needs of clients. The following specific objectives have been identified at this time. There will be some overlap with work being conducted under other tasks, and this work will be conducted collaboratively.
Subtask 1. Customize PBPK/PD Models for Individual Chemicals
1. Quantify the relevant dose metrics, and associated uncertainties, under scenarios of regulatory interest.
2. Develop and evaluate methods for species-to-species, age, and route-to-route extrapolation.
3. Evaluate and identify important mechanisms of chemical interaction for cumulative risk assessment.
4. Identify data gaps and recommend targeted experimental studies to reduce the uncertainties in the dose metric estimates.
5. Provide information on common absorption, distribution, metabolism, and excretion (ADME) pathways to recommend enhancements of the general ERDEM dose modeling platform.
6. Develop specific chemical and chemical class PBPK/PD models to support risk assessments, pesticide product registration and re-registration demands through 2008. As of FY06, the current chemicals of interest for this task include the N-methyl carbamates and trichloroethylene.
Subtask 2. Application of SHEDS-Pesticides for Carbamates
1. Develop SHEDS input data files for the carbamate assessment and work closely with OPP to apply the model to scenarios of interest to OPP
2. Collaborate with OPP to understand how the SHEDS model and its outputs are similar and different compared to other aggregate models being used by OPP in its carbamate assessment, and train OPP staff in the use of SHEDS
3. Release the SHEDS model code and n-methyl carbamate input files on the EPA internet and develop a functional relationship between "macro" and "micro" activities for young children
Description:
The overall goal of this task is to support program offices, Regions, States, and local agencies, by providing modeling tools and data to enable them to conduct exposure and risk assessments, and which will reduce the uncertainty in their exposure and risk assessments. This task addresses the modeling of chemicals of regulatory interest other than pyrethroids and PFCs, which are covered by other HEASD tasks.
Our exposure and dose models are fairly mature at this point, and have been designed to be flexible and to be able handle new chemicals identified by clients. The chemical-specific model inputs and algorithms improved or developed under this task highlight common methods, analyses, and data requirements for general exposure and dose modeling. Application to client specific needs will serve to strengthen to capabilities of, and science behind, our models. Specific objectives of this task relate directly to customer needs and contributions to the scientific field. There are two subtasks under this task; subtasks will be added as specific client needs are identified.
Subtask 1. Customize PBPK/PD Models for Individual Chemicals. This subtask aims to strengthen the general scientific foundation of EPA's exposure and risk assessment processes by refining state-of-the-art exposure to dose computational models. This research will produce physiologically-based pharmacokinetic (PBPK) and pharmacodynamic (PD) models for specific and often times unique applications. The models are expected to provide estimates of relevant dose metrics for diverse exposure scenarios. Two client applications are currently identified to be supported under this subtask, the OPP SAP for n-methyl carbamates cumulative risk assessment and the NCEA revised risk assessment for TCE.
Subtask 2. Application of SHEDS-Pesticides for the OPP N-Methyl Carbamates Assessment. The goal of this task is to support EPA's Office of Pesticide Programs, Health Effects Division in its n-methyl carbamates assessment by applying the SHEDS-Pesticides model to various dietary and residential scenarios. This work will be conducted collaboratively between branch members in HEASD and HED so that this application also allows OPP clients to better understand and be able to run the SHEDS-Pesticides model.