Public Health Significance

People are continuously exposed to mixtures of chemical and nonchemical stressors (e.g., psychosocial stress) throughout their lifetimes, and there is clear evidence that combined exposures can have cumulative effects (e.g., asbestos and tobacco smoke on lung cancer). Because most toxicity studies and risk assessments address only single chemical exposures, the scientific community may be underestimating the effects of exposure to multiple substances on human health and disease progression.

Challenges persist in characterizing exposures to mixtures, evaluating their toxicity and hazard, and assessing associated risk. Limitations in our understanding have led to inconsistent use of available mixture methods and significant uncertainties in their application. Lack of harmonized terminology and methods comparisons complicates the synthesis of information across disciplines and impedes the use of mixtures data in decision-making.

Program Objectives

To tackle these problems in understanding the potential health effects of mixtures, the Combined Exposures and Mixtures (CEM) Program is structured around the following three objectives:

1. Develop and apply a disease-centered systems biology approach for prioritizing mixtures for toxicological and hazard characterization to inform cumulative risk evaluation. This approach starts with a disease of interest and aims to identify and evaluate the joint effects of factors that contribute to disease development; it contrasts with component-based mixtures approaches that focus exclusively on structurally or mechanistically similar chemicals.
2. Develop and apply methods for complex mixtures testing and data interpretation to inform risk assessment of whole mixtures. Methods include targeted and nontargeted chemical analyses, complex mixture read-across (i.e., determining sufficient similarity), polypharmacokinetics (i.e., pharmacokinetics of multicomponent exposures), and bioassay-guided fractionation to identify toxic constituents.
3. Apply component-based approaches by experimentally evaluating defined mixtures and using predictive modeling approaches (e.g., dose addition, response addition) and compare the results with alternative whole-mixture evaluation.

Ultimately, the CEM Program is aimed at using a systems biology approach to predict which chemicals might act additively when present in mixtures, developing and refining whole-mixture evaluation and complex mixture read-across approaches, and strengthening predictive models of mixture toxicity by decreasing uncertainty in the application of component-based models.

Background

The Division of Translational Toxicology (DTT) mixtures portfolio offers a unique opportunity to inform literature-based evaluations in addressing human health effects from exposure to mixtures and is geared toward informing decision-making related to component-based and whole-mixture risk assessment. Assessing mixtures requires collaborative engagement across scientific disciplines, and multidisciplinary team science is a core value at DTT.

Approaches for complex mixture read-across applied in the CEM Program represent leading-edge science. Broad public health implications involved in mixtures research ensure that DTT trainees involved in mixtures projects gain experience in translational research. Thus, the CEM Program is well aligned with the mission and goals of DTT to incorporate the use of predictive models and emphasize the translational nature of our research.

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