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首页> 外文期刊>Toxicological sciences: An official journal of the Society of Toxicology >Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing
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Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing

机译:将高通量暴露预测与剂量测定法调整的体外生物活性相结合,以告知化学毒性测试

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We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compared against regulatory exposure estimates, providing an activity-to-exposure ratio (AER) useful for a risk-based ranking strategy. As ToxCast efforts expand (ie, Phase II) beyond food-use pesticides toward a wider chemical domain that lacks exposure and toxicity information, prediction tools become increasingly important. In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals. OEDs were compared against high-throughput (HT) exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. Environmental Protection Agency (EPA) ExpoCast program. This approach incorporated chemical-specific use and national production volume data with biomonitoring data to inform the exposure predictions. This HT exposure modeling approach provided predictions for all Phase II chemicals assessed in this study whereas estimates from regulatory sources were available for only 7% of chemicals. Of the 163 chemicals assessed in this study, 3 or 13 chemicals possessed AERs < 1 or < 100, respectively. Diverse bioactivities across a range of assays and concentrations were also noted across the wider chemical space surveyed. The availability of HT exposure estimation and bioactivity screening tools provides an opportunity to incorporate a risk-based strategy for use in testing prioritization.
机译:我们以前通过将体外生物活性浓度转换为内部达到这些水平所需的口服等效剂量(OED),将剂量测定和暴露与高通量筛选(HTS)集成在一起,以提高ToxCast HTS数据的实用性。将这些OED与监管暴露估计值进行比较,从而提供了基于风险的排名策略有用的活动暴露比(AER)。随着ToxCast的努力(即第二阶段)从食品用农药扩展到缺乏暴露和毒性信息的更广泛的化学领域,预测工具变得越来越重要。在这项研究中,对体外肝清除率和血浆蛋白结合度进行了测量,以估计一部分II期化学物质的OED。将OED与使用概率模型和美国环境保护署(EPA)ExpoCast计划生成的贝叶斯方法生成的高通量(HT)暴露预测进行比较。这种方法将特定于化学品的用途和国家生产量数据与生物监测数据结合在一起,以提供对暴露量的预测。这种HT暴露建模方法可为这项研究中评估的所有II期化学物质提供预测,而只有7%的化学物质来自监管部门的估算。在本研究评估的163种化学物质中,有3种或13种化学物质的AER分别<1或<100。在被调查的更广泛的化学领域中,还注意到了一系列测定和浓度范围内的多种生物活性。 HT暴露估算和生物活性筛选工具的可用性提供了将基于风险的策略用于测试优先级排序的机会。

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