* The Hamner Institutes for Health Sciences, Research Triangle Park, North Carolina 27709;
Toxicol Sci. 2013 Nov;136(1):4-18. doi: 10.1093/toxsci/kft178. Epub 2013 Aug 19.
Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency.
基于现有数据和以往的工作,提出了一系列研究计划,作为毒性测试实用化早期阶段的基础。这些研究被整合到一个数据驱动的框架中,该框架通过暴露量倍数 (MOE) 作为主要指标,调用连续的测试层级。该框架的第一层整合了高通量体外检测、体外到体内外推(IVIVE)药代动力学建模和暴露建模的数据。体外检测用于根据其与生物靶标相互作用的相对选择性来分离化学品,并确定发生这些相互作用的浓度。IVIVE 建模将体外浓度转化为外部剂量,以计算起始点 (POD),并与人体暴露估计值进行比较,以得出 MOE。第二层涉及短期体内研究、扩展的药代动力学评估和更精确的人体暴露估计。第二层研究的结果提供了更准确的 POD 和 MOE 估计值。第三层包含目前用于评估化学安全性的传统动物研究。在每个层级中,选择性化学品的 POD 主要基于与提议的作用模式相关的终点,而非选择性化学品的 POD 则基于潜在的生物扰动。基于 MOE,前两层评估的大量化学品可以免于进一步测试。该框架提供了一种基于风险和节省动物的方法来评估化学安全性,广泛借鉴以往的经验,但同时也融入了技术进步以提高效率。