Improving the risk assessment of lipophilic persistent environmental chemicals in breast milk.

Lipophilic persistent environmental chemicals (LPECs) have the potential to accumulate within a woman's body lipids over the course of many years prior to pregnancy, to partition into human milk, and to transfer to infants upon breastfeeding. As a result of this accumulation and partitioning, a breastfeeding infant's intake of these LPECs may be much greater than his/her mother's average daily exposure. Because the developmental period sets the stage for lifelong health, it is important to be able to accurately assess chemical exposures in early life. In many cases, current human health risk assessment methods do not account for differences between maternal and infant exposures to LPECs or for lifestage-specific effects of exposure to these chemicals. Because of their persistence and accumulation in body lipids and partitioning into breast milk, LPECs present unique challenges for each component of the human health risk assessment process, including hazard identification, dose-response assessment, and exposure assessment. Specific biological modeling approaches are available to support both dose-response and exposure assessment for lactational exposures to LPECs. Yet, lack of data limits the application of these approaches. The goal of this review is to outline the available approaches and to identify key issues that, if addressed, could improve efforts to apply these approaches to risk assessment of lactational exposure to these chemicals.

Characterizing interspecies uncertainty using data from studies of anti-neoplastic agents in animals and humans.

For most chemicals, the Reference Dose (RfD) is based on data from animal testing. The uncertainty introduced by the use of animal models has been termed interspecies uncertainty. The magnitude of the differences between the toxicity of a chemical in humans and test animals and its uncertainty can be investigated by evaluating the inter-chemical variation in the ratios of the doses associated with similar toxicological endpoints in test animals and humans. This study performs such an evaluation on a data set of 64 anti-neoplastic drugs. The data set provides matched responses in humans and four species of test animals: mice, rats, monkeys, and dogs. While the data have a number of limitations, the data show that when the drugs are evaluated on a body weight basis: 1) toxicity generally increases with a species' body weight; however, humans are not always more sensitive than test animals; 2) the animal to human dose ratios were less than 10 for most, but not all, drugs; 3) the current practice of using data from multiple species when setting RfDs lowers the probability of having a large value for the ratio. These findings provide insight into inter-chemical variation in animal to human extrapolations and suggest the need for additional collection and analysis of matched toxicity data in humans and test animals.

Variance of Microsomal Protein and Cytochrome P450 2E1 and 3A Forms in Adult Human Liver.

Differences in the pharmacokinetics of xenobiotics among humans makes them differentially susceptible to risk. Differences in enzyme content can mediate pharmacokinetic differences. Microsomal protein is often isolated from liver to characterize enzyme content and activity, but no measures exist to extrapolate these data to the intact liver. Measures were developed from up to 60 samples of adult human liver to characterize the content of microsomal protein and cytochrome P450 (CYP) enzymes. Statistical evaluations are necessary to estimate values far from the mean value. Adult human liver contains 52.9 +/- 1.476 mg microsomal protein per g; 2587 +/- 1.84 pmoles CYP2E1 per g; and 5237 +/- 2.214 pmols CYP3A per g (geometric mean +/- geometric standard deviation). These values are useful for identifying and testing susceptibility as a function of enzyme content when used to extrapolate in vitro rates of chemical metabolism for input to physiologically based pharmacokinetic models which can then be exercised to quantify the effect of variance in enzyme expression on risk-relevant pharmacokinetic outcomes.