Abstract
Abstract
A quantitative property–property relationship model was developed to predict intrinsic clearance (Clint) for 403 chemicals across a broad range of chemical properties and validated using a published set of Clint measurements. Clint measurements were predicted using octanol–water and water–air partition coefficients that are readily available or can be quickly estimated for most chemicals. These two chemical properties were determined to be statistically significant predictors of Clint, with >90% of predictions being within a factor of 10 of their measured value, and >60% being within a factor of 3. The resulting Clint estimates, with appropriate confidence bounds, can be readily incorporated into a generic physiologically based pharmacokinetic model for a wide range of chemicals, which can be used to estimate steady-state blood concentrations resulting from environmental exposures. The level of precision associated with this approach (i.e., within an order of magnitude) allows a screening-level estimation of this important metabolic parameter for a wide range of chemicals.
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