Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency.

Serial measurements of serum lipid 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) concentrations in 36 adults from Seveso, Italy, and three patients from Vienna, Austria, with initial serum lipid TCDD concentrations ranging from 130 to 144,000 ppt, were modeled using a modified version of a previously published toxicokinetic model for the distribution and elimination of dioxins. The original model structure accounted for a concentration-dependent increase in overall elimination rate for TCDD due to nonlinear distribution of TCDD to the liver (secondary to induction of the binding protein CYP1A2), from which elimination takes place via a first-order process. The original model structure was modified to include elimination due to lipid partitioning of TCDD from circulation into the large intestine, based on published human data. We optimized the fit of the modified model to the data by varying the hepatic elimination rate parameter for each of the 39 people. The model fits indicate that there is significant interindividual variability of TCDD elimination efficiency in humans and also demonstrate faster elimination in men compared to women, and in younger vs. older persons. The data and model results indicate that, for males, the mean apparent half-life for TCDD (as reflected in changes in predicted serum lipid TCDD level) ranges from less than 3 years at serum lipid levels above 10,000 ppt to over 10 years at serum lipid levels below 50 ppt. Application of the model to serum sampling data from the cohort of US herbicide-manufacturing workers assembled by the National Institute of Occupational Safety and Health (NIOSH) indicates that previous estimates of peak serum lipid TCDD concentrations in dioxin-exposed manufacturing workers, based on first-order backextrapolations with half-lives of 7-9 years, may have underestimated the maximum concentrations in these workers and other occupational cohorts by several-fold to an order of magnitude or more. Such dose estimates, based on a single sampling point decades after last exposure, are highly variable and dependent on a variety of assumptions and factors that cannot be fully determined, including interindividual variations in elimination efficiency. Dose estimates for these cohorts should be re-evaluated in light of the demonstration of concentration-dependent elimination kinetics for TCDD, and the large degree of uncertainty in back-calculated dose estimates should be explicitly incorporated in quantitative estimates of TCDD's carcinogenic potency based on such data.

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Biomarkers associated with asthma aetiology and exacerbation have been sought to shed light on this multifactorial disease. One candidate is the serum concentration of the Clara cell secretory protein (CC16, sometimes referred to as CC10 or uteroglobin). In this review, we examine serum CC16's relation to asthma aetiology and exacerbation. There is evidence that acute exposures to certain pulmonary irritants can cause a transient increase in serum CC16 levels, and limited evidence also suggests that a transient increase in serum CC16 levels can be caused by a localized pulmonary inflammation. Research also indicates that a transient increase in serum CC16 is not associated with measurable pulmonary damage or impairment of pulmonary function. The biological interpretation of chronic changes in serum CC16 is less clear. Changes in serum CC16 concentrations (either transient or chronic) are not specific to any one agent, disease state, or aetiology. This lack of specificity limits the use of serum CC16 as a biomarker of specific exposures. To date, many of the critical issues that must be understood before serum CC16 levels can have an application as a biomarker of effect or exposure have not been adequately addressed.

Advances in both sensitivity and specificity of analytical chemistry have made it possible to quantify substances in human biological specimens, such as blood, urine, and breast milk, in specimen volumes that are practical for collection from individuals. Research laboratories led by the Centers for Disease Control and Prevention (CDC) in its series National Report on Human Exposure to Environmental Chemicals [Centers for Disease Control and Prevention (CDC), 2005. Third National Report on Human Exposure to Environmental Chemicals. NCEH Pub. No. 05-0570.] are dedicating substantial resources to designing and conducting human biomonitoring studies and compiling biomonitoring data for the general population. However, the ability to quantitatively interpret the results of human biomonitoring in the context of a health risk assessment currently lags behind the analytical chemist's ability to make such measurements. The traditional paradigm for human health risk assessment of environmental chemicals involves comparing estimated daily doses to health-based criteria for acceptable, safe, or tolerable daily intakes (for example, reference doses [RfDs], tolerable daily intakes [TDIs], or minimal risk levels [MRLs]) to assess whether estimated doses exceed such health screening levels. However, biomonitoring efforts result in measured chemical concentrations in biological specimens (the result of absorption, distribution, metabolism and excretion of administered doses) rather than estimated intake doses. Quantitative benchmarks of acceptable or safe concentrations in biological specimens (analogous to RfDs, TDIs, or MRLs) needed to interpret these levels exist for very few chemicals of environmental interest. This paper discusses issues inherent in converting existing health screening benchmarks based on intake doses to screening levels for evaluating biomonitoring data, and presents methods and approaches that can be used to derive such screening levels (termed ''Biomonitoring Equivalents,'' or BEs) for a range of chemicals and biological media.