An In Silico Approach for Evaluating a Fraction-Based, Risk Assessment Method for Total Petroleum Hydrocarbon Mixtures

Both the Massachusetts Department of Environmental Protection (MADEP) and the Total Petroleum Hydrocarbon Criteria Working Group (TPHCWG) developed fraction-based approaches for assessing human health risks posed by total petroleum hydrocarbon (TPH) mixtures in the environment. Both organizations defined TPH fractions based on their expected environmental fate and by analytical chemical methods. They derived toxicity values for selected compounds within each fraction and used these as surrogates to assess hazard or risk of exposure to the whole fractions. Membership in a TPH fraction is generally defined by the number of carbon atoms in a compound and by a compound's equivalent carbon (EC) number index, which can predict its environmental fate. Here, we systematically and objectively re-evaluate the assignment of TPH to specific fractions using comparative molecular field analysis and hierarchical clustering. The approach is transparent and reproducible, reducing inherent reliance on judgment when toxicity information is limited. Our evaluation of membership in these fractions is highly consistent (˜80% on average across various fractions) with the empirical approach of MADEP and TPHCWG. Furthermore, the results support the general methodology of mixture risk assessment to assess both cancer and noncancer risk values after the application of fractionation

Prospective Power Calculations for the Four Lab Study of A Multigenerational Reproductive/Developmental Toxicity Rodent Bioassay Using A Complex Mixture of Disinfection By-Products in the Low-Response Region

In complex mixture toxicology, there is growing emphasis on testing environmentally representative doses that improve the relevance of results for health risk assessment, but are typically much lower than those used in traditional toxicology studies. Traditional experimental designs with typical sample sizes may have insufficient statistical power to detect effects caused by environmentally relevant doses. Proper study design, with adequate statistical power, is critical to ensuring that experimental results are useful for environmental health risk assessment. Studies with environmentally realistic complex mixtures have practical constraints on sample concentration factor and sample volume as well as the number of animals that can be accommodated. This article describes methodology for calculation of statistical power for non-independent observations for a multigenerational rodent reproductive/developmental bioassay. The use of the methodology is illustrated using the U.S. EPA’s Four Lab study in which rodents were exposed to chlorinated water concentrates containing complex mixtures of drinking water disinfection by-products. Possible experimental designs included two single-block designs and a two-block design. Considering the possible study designs and constraints, a design of two blocks of 100 females with a 40:60 ratio of control:treated animals and a significance level of 0.05 yielded maximum prospective power (~90%) to detect pup weight decreases, while providing the most power to detect increased prenatal loss

EPA project-level research strategies for chemical mixtures: targeted research for meaningful results

Project-level research strategies at the U.S. Environmental Protection Agency regarding chemical mixtures are impacted by administrative priorities, public interests, expert opinions, scientific advances, regulatory needs, and legislative actions, influencing the setting of priorities and goals. Perhaps, the most significant influence on conducting chemical mixtures research is the passage of laws requiring the EPA to investigate the potential toxicity of various mixtures, specifically the Comprehensive Environmental Response, Compensation, and Liability Act of 1980, the Food Quality Protection Act of 1996, and the Safe Drinking Water Act Amendments of 1996. Scarce resources are allocated to broadly defined issues for consideration by teams of scientists, who design and implement specific projects. Because resources are limited, projects may have several goals, e.g., filling specific data gaps to support a regulation and, simultaneously, producing data to evaluate a risk assessment method. Research areas of emphasis are shaped by risk assessment needs, data gap uncertainties, and experimental design considerations. This paper discusses factors shaping EPA research strategies for chemical mixtures and presents an example of efficient research planning to investigate potential toxicity from exposure to drinking water disinfection by-products

Evaluation of a Proportional Response Addition Approach to Mixture Risk Assessment and Predictive Toxicology Using Data on Four Trihalomethanes from the U.S. EPA’s Multiple-Purpose Design Study

In this study, proportional response addition (Prop-RA), a model for predicting response from chemical mixture exposure, is demonstrated and evaluated by statistically analyzing data on all possible binary combinations of the four regulated trihalomethanes (THMs). These THMs were the subject of a multipurpose toxicology study specifically designed to evaluate Prop-RA. The experimental design used a set of doses common to all components and mixtures, providing hepatotoxicity data on the four single THMs and the binary combinations. In Prop-RA, the contribution of each component to mixture toxicity is proportional to its fraction in the mixture based on its response at the total mixture dose. The primary analysis consisted of 160 evaluations. Statistically significant departures from the Prop-RA prediction were found for seven evaluations, with three predications that were greater than and four that were less than the predicted response; interaction magnitudes (n-fold difference in response vs. prediction) ranged from 1.3 to 1.4 for the former and 2.6 to 3.8 for the latter. These predictions support the idea that Prop-RA works best with chemicals where the effective dose ranges overlap. Prop-RA does not assume the similarity of toxic action or independence, but it can be applied to a mixture of components that affect the same organ/system, with perhaps unknown toxic modes of action