Citation:

CHANG, D., M. S. OKINO, FRED W. POWER, R. TORNERO-VELEZ, J. F. KENNEKE, CHRIS S. MAZUR, C. C. DARY, AND TIM W. COLLETTE. ESTIMATION OF CHEMICAL SPECIFIC PARAMETERS WITHIN PHYSIOLOGICALLY BASED PHARMACOKINETIC/PHARMACODYNAMIC MODELS. Presented at EPA Science Forum 2006, Washington, DC, May 16 - 18, 2006.

Impact/Purpose:

The overall goal of this work is to reduce the uncertainty in risk assessment. The chemical-specific models developed under this task highlight common methods, analyses, and data requirements for general dose modeling. Specific objectives relate directly to customer needs and contributions to the scientific field.

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 ADME pathways to recommend enhancements of the general ERDEM dose modeling platform.

6)Develop specific chemical and chemical class PBPK/PD models to support pesticide product registration and re-registration demands through 2008 (EPA Strategic Plan Objective 4.1.1: Reduce exposure to toxic pesticides).

Description:

While relationships between chemical structure and observed properties or activities (QSAR - quantitative structure activity relationship) can be used to predict the behavior of unknown chemicals, this method is semiempirical in nature relying on high quality experimental data to construct statistically relevant relationships for a set of chemically similar compounds (congeners).

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