The application of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling for exploring risk assessment approaches of chemical mixtures.

When dealing with health impacts of environmental or occupational exposure such as groundwater contamination from or remediation effort associated with hazardous waste sites, we are obviously not facing individual, single chemicals. Thus, we are immediately confronted with the following questions: (1) Is single chemical risk assessment approach applicable to the multiple chemicals in hazardous waste sites? (2) How do we handle risk assessment of chemical mixtures? Although there were pioneering and commendable efforts from the USEPA to formulate guidelines for risk assessment of chemical mixtures, these guidelines were principally based on additivity concept. As new scientific advances are made, improvement and refinement of risk assessment methodology will be anticipated. At Colorado State University (CSU), our research effort is devoted to the challenges and potential applications of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling in the risk assessment of chemical mixtures. With the ultimate goal of Predictive Toxicology, 3 specific research projects are described: (1) PBPK/PD modeling of toxicologic interactions between trichloroethylene (TCE) and 1,1-dichloroethylene (1,1-DCE) and the investigation and defining of an 'Interaction Threshold'; (2) PBPK/PD modeling of toxicologic interactions between Kepone and carbon tetrachloride (CCl4) and the coupling of Monte Carlo simulation for the prediction of acute toxicity; (3) PBPK modeling of the inhibition of pharmacokinetics and enzyme kinetics of TCE caused by low-level, repeated dosing of a chemical mixture of 7 groundwater contaminants. Since this paper is meant to be a commentary and the emphasis is on approaches for dealing with chemical mixtures, detailed presentation of data is avoided. These examples illustrate partially our ongoing research activities and the related ideas with respect to possible novel risk assessment applications to chemical mixtures.