Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Air, Climate, and Energy Research Program, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Risk Anal. 2022 Apr;42(4):707-729. doi: 10.1111/risa.13810. Epub 2021 Sep 7.
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.
监管机构需要评估数千种化学物质的影响。目前在这些评估中使用的毒理学测试既耗时又耗资源；然而，毒理学和相关领域的进步正在提供新的测试方法，这些方法可以降低测试的成本和时间。选择首选方法具有挑战性，因为新方法在持续时间和成本上有所不同，并且它们生成的数据在不确定性水平上也有所不同。本文提出了一种用于进行毒性测试成本效益分析（CEA）的框架，该框架考虑了成本、持续时间和不确定性。这是通过使用输出指标（每个正确监管决策的成本）来实现的，该指标反映了这三个要素。该框架在两个示例 CEA 中进行了演示，一个是简单的风险可接受性决策，另一个是更复杂的决策，涉及监管行动的选择。每个示例 CEA 评估了五种具有不同成本、时间和不确定性的假设毒性测试方法。结果表明，与不确定性降低五倍相比，成本或持续时间降低五倍可以更有效地选择最佳毒性测试方法。当决策者需要做出更复杂的决策，需要确定风险预测中的微小差异时，不确定性与成本和持续时间的重要性相当。本文提出的框架可能为识别大量化学品毒性测试的成本效益方法提供有用的基础。
