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Cincinnati, OH, United States

Hertzberg R.C.,Biomathematics Consulting | Pan Y.,Emory University | Pan Y.,National Center for Environmental Health | Li R.,Emory University | And 6 more authors.

Mixture risk assessment is often hampered by the lack of dose-response information on the mixture being assessed, forcing reliance on component formulas such as dose addition. We present a four-step approach for evaluating chemical mixture data for consistency with dose addition for use in supporting a component based mixture risk assessment. Following the concepts in the U.S. EPA mixture risk guidance ( U.S. EPA, 2000a,b), toxicological interaction for a defined mixture (all components known) is departure from a clearly articulated definition of component additivity. For the common approach of dose additivity, the EPA guidance identifies three desirable characteristics, foremost of which is that the component chemicals are toxicologically similar. The other two characteristics are empirical: the mixture components have toxic potencies that are fixed proportions of each other (throughout the dose range of interest), and the mixture dose term in the dose additive prediction formula, which we call the combined prediction model (CPM), can be represented by a linear combination of the component doses. A consequent property of the proportional toxic potencies is that the component chemicals must share a common dose-response model, where only the dose coefficients depend on the chemical components. A further consequence is that the mixture data must be described by the same mathematical function ("mixture model") as the components, but with a distinct coefficient for the total mixture dose. The mixture response is predicted from the component dose-response curves by using the dose additive CPM and the prediction is then compared with the observed mixture results. The four steps are to evaluate: (1) toxic proportionality by determining how well the CPM matches the single chemical models regarding mean and variance; (2) fit of the mixture model to the mixture data; (3) agreement between the mixture data and the CPM prediction; and (4) consistency between the CPM and the mixture model. Because there are four evaluations instead of one, some involving many parameters or dose groups, there are more opportunities to reject statistical hypotheses about dose addition, thus statistical adjustment for multiple comparisons is necessary. These four steps contribute different pieces of information about the consistency of the component and mixture data with the two empirical characteristics of dose additivity. We examine this four-step approach in how it can show empirical support for dose addition as a predictor for an untested mixture in a screening level risk assessment. The decision whether to apply dose addition should be based on all four of those evidentiary pieces as well as toxicological understanding of these chemicals and should include interpretations of the numerical and toxicological issues that arise during the evaluation. This approach is demonstrated with neurotoxicity data on carbamate mixtures. © 2012 Elsevier Ireland Ltd. Source

Reichard J.F.,University of Cincinnati | Haber L.T.,Toxicology Excellence for Risk Assessment TERA
Food and Chemical Toxicology

The purpose of this work is to systematically consider the data relating to the mode of action (MOA) for the effects of industrially produced trans fatty acid (iTFA) on plasma low-density lipoprotein (LDL) levels. The hypothesized MOA is composed of two key events: increased LDL production and decreased LDL clearance. A substantial database supports this MOA, although the key events are likely to be interdependent, rather than sequential. Both key events are functions of nonlinear biological processes including rate-limited clearance, receptor-mediated transcription, and both positive and negative feedback regulation. Each key event was evaluated based on weight-of-evidence analysis and for human relevance. We conclude that the data are inadequate for a detailed dose-response analysis in the context of the evolved Bradford Hill considerations; however, the weight of evidence is strong and the overall shape of the dose-response curves for markers of the key events and the key determinants of those relationships is well understood in many cases and is nonlinear. Feedback controls are responsible for maintaining homeostasis of cholesterol and triglyceride levels and underlie both of the key events, resulting in a less-than-linear or thresholded relationship between TFA and LDL-C. The inconsistencies and gaps in the database are discussed. © 2016 Elsevier Ltd. Source

Rider C.V.,National Health Research Institute | Dourson M.L.,Toxicology Excellence for Risk Assessment TERA | Hertzberg R.C.,Biomathematics Consulting | Mumtaz M.M.,Agency for Toxic Substances and Disease Registry | And 2 more authors.
Toxicological Sciences

The role of nonchemical stressors in modulating the human health risk associated with chemical exposures is an area of increasing attention. On 9 March 2011, a workshop titled "Approaches for Incorporating Nonchemical Stressors into Cumulative Risk Assessment" took place during the 50th Anniversary Annual Society of Toxicology Meeting in Washington D.C. Objectives of the workshop included describing the current state of the science from various perspectives (i.e., regulatory, exposure, modeling, and risk assessment) and presenting expert opinions on currently available methods for incorporating nonchemical stressors into cumulative risk assessments. Herein, distinct frameworks for characterizing exposure to, joint effects of, and risk associated with chemical and nonchemical stressors are discussed. Published by Oxford University Press 2012. Source

DeBord D.G.,U.S. National Institute for Occupational Safety and Health | Burgoon L.,U.S. Environmental Protection Agency | Edwards S.W.,U.S. Environmental Protection Agency | Haber L.T.,Toxicology Excellence for Risk Assessment TERA | And 5 more authors.
Journal of Occupational and Environmental Hygiene

In a recent National Research Council document, new strategies for risk assessment were described to enable more accurate and quicker assessments.( 1 ) This report suggested that evaluating individual responses through increased use of bio-monitoring could improve dose-response estimations. Identi-fication of specific biomarkers may be useful for diagnostics or risk prediction as they have the potential to improve exposure assessments. This paper discusses systems biology, biomarkers of effect, and computational toxicology approaches and their relevance to the occupational exposure limit setting process.The systems biology approach evaluates the integration of biological processes and how disruption of these processes by chemicals or other hazards affects disease outcomes. This type of approach could provide information used in delineating the mode of action of the response or toxicity, and may be useful to define the low adverse and no adverse effect levels. Biomarkers of effect are changes measured in biological systems and are considered to be preclinical in nature. Advances in computational methods and experimental-omics methods that allow the simultaneous measurement of families of macromolecules such as DNA, RNA, and proteins in a single analysis have made these systems approaches feasible for broad application.The utility of the information for risk assessments from-omics approaches has shown promise and can provide information on mode of action and dose-response relationships. As these techniques evolve, estimation of internal dose and response biomarkers will be a critical test of these new technologies for application in risk assessment strategies. While proof of concept studies have been conducted that provide evidence of their value, challenges with standardization and harmonization still need to be overcome before these methods are used routinely. © 2015 Published with license by Taylor and Francis. Source

Effio D.G.,URS Corporation | Kroner O.,Toxicology Excellence for Risk Assessment TERA | Maier A.,Toxicology Excellence for Risk Assessment TERA | Hayes W.,Indianapolis | And 2 more authors.
Risk Analysis

State environmental agencies in the United States are charged with making risk management decisions that protect public health and the environment while managing limited technical, financial, and human resources. Meanwhile, the federal risk assessment community that provides risk assessment guidance to state agencies is challenged by the rapid growth of the global chemical inventory. When chemical toxicity profiles are unavailable on the U.S. Environmental Protection Agency's Integrated Risk Information System or other federal resources, each state agency must act independently to identify and select appropriate chemical risk values for application in human health risk assessment. This practice can lead to broad interstate variation in the toxicity values selected for any one chemical. Within this context, this article describes the decision-making process and resources used by the federal government and individual U.S. states. The risk management of trichloroethylene (TCE) in the United States is presented as a case study to demonstrate the need for a collaborative approach among U.S. states toward identification and selection of chemical risk values while awaiting federal risk values to be set. The regulatory experience with TCE is contrasted with collaborative risk science models, such as the European Union's efforts in risk assessment harmonization. Finally, we introduce State Environmental Agency Risk Collaboration for Harmonization, a free online interactive tool designed to help to create a collaborative network among state agencies to provide a vehicle for efficiently sharing information and resources, and for the advancement of harmonization in risk values used among U.S. states when federal guidance is unavailable. © 2012 Society for Risk Analysis. Source

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