Office of Research and Development, Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, North Carolina 27709, United States.
Office of Research and Development, National Exposure Research Laboratory, U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, Durham, North Carolina 27709, United States.
Environ Sci Technol. 2021 May 4;55(9):6505-6517. doi: 10.1021/acs.est.0c06117. Epub 2021 Apr 15.
The intrinsic metabolic clearance rate (Cl) and the fraction of the chemical unbound in plasma () serve as important parameters for high-throughput toxicokinetic (TK) models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable predictions for a diverse set of chemicals regulated under the U.S. law, including pharmaceuticals, pesticides, and industrial chemicals. As a case study to demonstrate their utility, model predictions served as inputs to the TK component of a risk-based prioritization approach based on bioactivity/exposure ratios (BERs), in which a BER < 1 indicates that exposures are predicted to exceed a biological activity threshold. When applied to a subset of the Tox21 screening library (6484 chemicals), we found that the proportion of chemicals with BER <1 was similar using either (1133/6484; 17.5%) or (148/848; 17.5%) parameters. Further, when considering only the chemicals in the Tox21 set with data, there was a high concordance of chemicals classified with either BER <1 or >1 using either or parameters (767/848, 90.4%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured TK data are lacking.
内在代谢清除率 (Cl) 和血浆中未结合的化学物质分数 () 是高通量毒代动力学 (TK) 模型的重要参数，但许多化学物质的实验数据有限。开发了这两个参数的开源定量构效关系 (QSAR) 模型，可为美国法规监管的多种化学物质提供可靠的预测，包括药物、农药和工业化学品。作为一个案例研究来证明它们的实用性，模型预测被用作基于生物活性/暴露比 (BER) 的风险优先排序方法的 TK 组件的输入，其中 BER < 1 表示预测暴露将超过生物活性阈值。当应用于 Tox21 筛选库的一个子集 (6484 种化学物质) 时，我们发现使用 (1133/6484；17.5%) 或 (148/848；17.5%) 参数，BER < 1 的化学物质比例相似。此外，当仅考虑 Tox21 集中具有 数据的化学物质时，使用 或 参数将化学物质分类为 BER < 1 或 > 1 的一致性很高（767/848，90.4%）。因此，提出的 QSAR 可用于优先考虑许多缺乏测量 TK 数据的化学物质所带来的风险。
