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A Framework that Considers the Impacts of Time, Cost, and Uncertainty in the Determination of the Cost Effectiveness of Toxicity-Testing Methodologies.
Regulatory agencies are required to evaluate the impacts of thousands of chemicals. Toxicological tests currently used in such evaluations are time-consuming and resource intensive; however, advances in toxicology and related fields are providing new testing methodologies that reduce the cost and time required for testing. The selection of a preferred methodology is challenging because the new methodologies vary in duration and cost, and the data they generate vary in the level of uncertainty. This article presents a framework for performing cost-effectiveness analyses (CEAs) of toxicity tests that account for cost, duration, and uncertainty. This is achieved by using an output metric-the cost per correct regulatory decision-that reflects the three elements. The framework is demonstrated in two example CEAs, one for a simple decision of risk acceptability and a second, more complex decision, involving the selection of regulatory actions. Each example CEA evaluates five hypothetical toxicity-testing methodologies which differ with respect to cost, time, and uncertainty. The results of the examples indicate that either a fivefold reduction in cost or duration can be a larger driver of the selection of an optimal toxicity-testing methodology than a fivefold reduction in uncertainty. Uncertainty becomes of similar importance to cost and duration when decisionmakers are required to make more complex decisions that require the determination of small differences in risk predictions. The framework presented in this article may provide a useful basis for the identification of cost-effective methods for toxicity testing of large numbers of chemicals.
Authors
- Price, Paul S, Price PS, Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
- Hubbell, Bryan J, Hubbell BJ, Air, Climate, and Energy Research Program, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
- Hagiwara, Shintaro, Hagiwara S, School of Mathematics and Statistics, Carleton University, Ottawa, Canada.; Risk Sciences International, Ottawa, Canada.
- Paoli, Greg M, Paoli GM, Risk Sciences International, Ottawa, Canada.
- Krewski, Daniel, Krewski D, McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada.
- Guiseppi-Elie, Annette, Guiseppi-Elie A, Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
- Gwinn, Maureen R, Gwinn MR, Sustainable and Healthy Communities Research Program, US Environmental Protection Agency, Research Triangle Park, NC, USA.
- Adkins, Norman L, Adkins NL, Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
- Thomas, Russell S, Thomas RS, Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Regulatory agencies are required to evaluate the impacts of thousands of chemicals. Toxicological tests currently used in such evaluations are time-consuming and resource intensive; however, advances in toxicology and related fields are providing new testing methodologies that reduce the cost and time required for testing. The selection of a preferred methodology is challenging because the new methodologies vary in duration and cost, and the data they generate vary in the level of uncertainty. This article presents a framework for performing cost-effectiveness analyses (CEAs) of toxicity tests that account for cost, duration, and uncertainty. This is achieved by using an output metric-the cost per correct regulatory decision-that reflects the three elements. The framework is demonstrated in two example CEAs, one for a simple decision of risk acceptability and a second, more complex decision, involving the selection of regulatory actions. Each example CEA evaluates five hypothetical toxicity-testing methodologies which differ with respect to cost, time, and uncertainty. The results of the examples indicate that either a fivefold reduction in cost or duration can be a larger driver of the selection of an optimal toxicity-testing methodology than a fivefold reduction in uncertainty. Uncertainty becomes of similar importance to cost and duration when decisionmakers are required to make more complex decisions that require the determination of small differences in risk predictions. The framework presented in this article may provide a useful basis for the identification of cost-effective methods for toxicity testing of large numbers of chemicals.
