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Life-Stage PBPK Models for Multiple Routes of Ethanol Exposure in the Rat
Citation:
MARTIN, S. A., P. J. BUSHNELL, W. K. BOYES, H. A. EL-MASRI, W. Lewfew, W. M. OSHIRO, T. E. BEASLEY, P. A. EVANSKY, L. DEGN, D. W. HERR, A. D. LEDBETTER, J. L. FORD, E. MCLANAHAN, J. L. CAMPBELL, H. J. CLEWELL, AND K. Choi. Life-Stage PBPK Models for Multiple Routes of Ethanol Exposure in the Rat. Presented at Society of Toxicology (SOT) Annual Meeting, Washington, DC, March 06 - 10, 2011.
Impact/Purpose:
This work covers a range of ethanol tissue concentrations associated with DNT in rodents, and thus may be useful for risk assessments.
Description:
Ethanol is commonly blended with gasoline (10% ethanol) in the US, and higher ethanol concentrations are being considered. While the pharmacokinetics and toxicity of orally-ingested ethanol are widely reported, comparable work is limited for inhalation exposure (IE), particularly at concentrations producing blood (BEC) and brain (BrEC) ethanol concentrations associated with developmental neurotoxicity (DNT). Multi-route, life-stage PBPK models for adult, pregnant, and neonatal rats were developed and used to predict inhalation exposure concentrations yielding BEC and BrEC associated with DNT. Based on model predictions, Long-Evans rats received multiple 6-hr IE at 5,000 to 20,000ppm to assess the pharmacokinetics of ethanol. Tissues (blood, brain, eyes, liver) were collected for analysis via headspace gas chromatography to provide quantitative data and support model calibration. Kinetic time points were specific to each IE and designed to capture loading, peak, and clearance phases across low and high IE and tissue concentrations, while remaining comparable to literature data at lower concentrations. Simulations using the calibrated ethanol model were in good agreement with peak and post-exposure BEC and BrEC for most datasets, though additional work is needed to refine estimates of metabolism. This work covers a range of ethanol tissue concentrations associated with DNT in rodents, and thus may be useful for risk assessments. These models will be coupled with a gasoline model to describe biofuel blends. This abstract does not reflect EPA policy.