The development of a stochastic physiologically-based pharmacokinetic model for lead

Abstract

This presentation describes the development of a prototype Monte Carlo module for the physiologically-based pharmacokinetic (PBPK) model for lead, created by Dr Ellen O'Flaherty. The module uses distributions for the following: exposure parameters (soil and dust concentrations, daily soil and ingestion rate, water lead concentration, water ingestion rate, air lead concentration, inhalation rate and dietary lead intake); absoption parameters; and key pharmacokinetic parameters (red blood binding capacity and half saturation concentration). Distributions can be specified as time-invariant or can change with age. Monte Carlo model predicted blood levels were calibrated to empirically measured blood lead levels for children lining in Midvale, Utah (a milling/smelting community). The calibrated model was then evaluated using blood lead data from Palmerton, Pennsylvania (a town with a former smelt) and Sandy, Utah, (a town with a former smelt and slag piles). Our initial evaluation using distributions for exposure parameters showed that the model accurately predicted geometric (GM) blood lead level of Palmerton and Sandy and slightly over predicted the GSD. Consideration of uncertainty in red blood cell parameters substantially inflated the GM. Future model development needs to address the correlation among parameters and the use of parameters for long-term exposure derived from short-term studies.