ABSTRACT

In vivo animal bioassays are increasingly being supplemented with in vitro assays to serve as the new standard for chemical toxicity tests. Despite this shift, investigators face challenges related to increased reliance on in vitro data. The aim of this study was to deploy a streamlined method to assess the ability of in vitro data to predict similar results as in vivo data by correlating chemical toxicity rankings obtained using Benchmark Doses and Benchmark Dose Lower Limits (BMD(L)s) derived from in vivo and in vitro assays. In vitro and in vivo assay characteristics were assessed for their impact on the predictive ability of in vitro data. Minimum best-fit BMD(L)s were calculated for chemicals using Environmental Protection Agency’s (EPA’s) Benchmark Dose Software (BMDS). Forty-one chemicals met the inclusion criteria of this study. Relative chemical toxicity rankings were assessed through Kappa statistics, Pearson correlations, and/or Ordinary Least Squares (OLS) regressions. Results illustrated likely ability of in vitro data to predict similar results as short-term in vivo data. Further, rankings derived from in vitro cytotoxicity assays, unlike stress response assays, significantly correlated with rankings derived from short-term in vivo assays. These results support the use of in vitro data as a prioritization tool within toxicity testing.

摘要

体内动物生物测定越来越多地辅以体外测定，以作为化学毒性测试的新标准。尽管有这种转变，研究人员仍面临着与越来越依赖体外数据相关的挑战。本研究的目的是部署一种简化的方法，通过关联使用基准剂量和基准剂量下限 (BMD(L)) 获得的化学毒性排名，评估体外数据预测与体内数据类似结果的能力。体内和体外测定。体外和体内评估了测定特性对体外数据预测能力的影响。使用环境保护署 (EPA) 的基准剂量软件 (BMDS) 计算化学品的最小最佳拟合 BMD(L)。41 种化学品符合本研究的纳入标准。通过 Kappa 统计、Pearson 相关和/或普通最小二乘法 (OLS) 回归评估相对化学毒性排名。结果表明体外数据可能具有预测与短期体内数据相似的结果的能力。此外，与应激反应分析不同，来自体外细胞毒性试验的排名与来自短期体内的排名显着相关化验。这些结果支持使用体外数据作为毒性测试中的优先排序工具。