Quantitative structure - property relationships for predicting toxicokinetics of organic chemicals in biota

用于预测生物群中有机化学品毒代动力学的定量结构-性质关系

• 批准号: RGPIN-2015-04408
• 负责人: Krishnan, Kannan
• 金额: $ 3.57万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=630877
• 关键词: Quantitative; structure; property; relationships; predicting

The objective of this proposal is to develop new knowledge and tools for facilitating molecular structure-based prediction of the toxicokinetics of organic chemicals in dairy cattle, poultry and rats. More specifically, this proposal focuses on the development of two-tier approaches and quantitative structure-property relationships (QSPRs) for integration with physiological parameters to produce newer generation of toxicokinetic models for existing and emerging chemicals. The present project will facilitate the development of tiered approaches and QSPRs applicable for physiologically-based toxicokinetic (PBTK) modeling of a number of chemical classes (alkanes, alkenes, alkylenes, haloacetic acids, ketones, alcohols, ethers, volatile aromatics, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, dioxins, organophosphorous pesticides, as well as emerging contaminants) primarily found in air, food and/or water. The kinetic data and residue studies in cattle and chicken for a limited number of chemicals are available and those will be made use of, in the context of the present study, for calibrating the QSPRs and validating the PBTK models. Tier 1 approaches will involve the prediction of the parameters in a semi quantitative manner (ie., low, medium, high; decision-tree approach) whereas Tier 2 will require the use of more detailed considerations or predictive QSPRs. Based on the results of sensitive analysis of the Tier 1 model, Tier 2 will be conducted. The Tier-1 and Tier-2 approaches for partition coefficients and metabolism (clearance) parameters will lead to PBTK models that can provide screening-level or more precise predictions in dairy cattle and domestic fowls for a variety of environmental chemicals. The resulting models will not only facilitate molecular structure-based prediction of internal dose (i.e., residue level in tissues) of environmental chemicals in food-producing animals, but also lead to simulations of chemical concentrations in tissues, at the time when they are intended for human consumption.

该提案的目的是开发新的知识和工具，以促进基于分子结构的有机化学品在奶牛、家禽和大鼠中的毒代动力学预测。更具体地说，该提案侧重于开发两层方法和定量结构-性质关系（QSPR），以与生理参数相结合，为现有和新兴化学品产生新一代毒代动力学模型。本项目将促进分层方法和 QSPR 的开发，适用于多种化学类别（烷烃、烯烃、烯烃、卤乙酸、酮、醇、醚、挥发性芳烃、多环芳烃、多氯联苯、二恶英、 主要存在于空气、食物和/或水中的有机磷农药以及新出现的污染物。牛和鸡中有限数量的化学品的动力学数据和残留研究是可用的，在本研究的背景下，这些数据将用于校准 QSPR 和验证 PBTK 模型。第 1 层方法将涉及以半定量方式（即低、中、高；决策树方法）对参数进行预测，而第 2 层将需要使用更详细的考虑因素或预测 QSPR。根据方法 1 模型的敏感性分析结果，将进行方法 2。分配系数和代谢（清除）参数的第 1 层和第 2 层方法将产生 PBTK 模型，该模型可以为奶牛和家禽中的各种环境化学物质提供筛选水平或更精确的预测。由此产生的模型不仅有助于基于分子结构预测食用动物环境化学品的内部剂量（即组织中的残留水平），而且还可以模拟供人类食用时组织中的化学浓度。