US EPA

Biologically-based pharmacokinetic models are being increasingly used in the risk assessment of environmental chemicals. These models are based on biological, mathematical, statistical and engineering principles. Their potential uses in risk assessment include extrapolation between individuals, species, doses and routes of exposures. However, the use of formal statistical methods in developing and evaluating these models for use in risk assessment has been limited. This workshop will review applications of statistical methods to both pharmacokinetic modeling in particular and mathematical modeling more generally, with discussion of the utility of applying such methods to pharmacokinetic models in risk assessment and ways to improve and facilitate their use. Proceedings from this workshop will be developed.

The purpose of this workshop is to identify statistical methods that have or can be applied to pharmacokinetic models for use in risk assessment. Potential uses may include comparing alternative model structures; estimating the uncertainty in model parameters, addressing inter-species, inter-individual, inter-occasion, and experimental (or measurement) variability; evaluating models’ predictive capacity, and characterizing the impact of these factors on predictions relevant for risk assessment.