HUMAN DOSIMETRY FOR ASSESSMENT OF EXPOSURE TO VOLATILE COMPOUNDS

用于评估挥发性化合物暴露的人体剂量测定

• 批准号: 6577765
• 负责人: DAVID A KALMAN
• 金额: $ 22.2万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-04-01 至 2003-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6577765
• 关键词: benzene; biomarker; blood tests; breath tests; chemical kinetics; clinical research; environmental contamination; environmental exposure; environmental toxicology; hazardous substances; human subject; mathematical model; methanol; method development; model design /development; pharmacokinetics; solvents; toxin metabolism; urinalysis

The objective of this project is understand the extent to which humans absorb, metabolize, and eliminate volatile organic compounds to which they may be exposed as a result of environmental contamination. Of special interest to us is the range of normal variation in these processes, and the factors which influence this variation. To better understand the underlying physiology, this project has as one of its central features the development and validation of a detailed mathematical mode of absorption, metabolism, and elimination processes in humans. Our past success in using this model to describe the operation of these processes for toluene, with very good accuracy, leads us to anticipate that this model will be able to describe the behavior of other solvents with different biological and chemical properties. Most important, the model relies on only a few readily measured individual characteristics (e.g. body fat composition, height, simple measurements of metabolic rate such as respiratory ventilation rate) to predict the individual's response. The results of this study will therefore support relatively accurate health risk assessments and epidemiologic studies, without requiring complex or detailed input data.

该项目的目的是了解人类吸收，代谢和消除挥发性有机化合物的程度，由于环境污染而可能暴露于这些化合物。我们特别感兴趣的是这些过程中正常差异的范围，以及影响这种变化的因素。为了更好地理解潜在的生理学，该项目是其中心之一的特征之一，它是人类吸收，代谢和消除过程的详细数学模式的开发和验证。 我们过去使用该模型的成功来描述这些过程的甲苯操作，其精度非常好，这使我们预计该模型将能够描述具有不同生物学和化学特性的其他溶剂的行为。最重要的是，该模型仅依赖于几个很容易测量的个体特征（例如体内脂肪组成，高度，简单测量代谢率（例如呼吸通气率））来预测个人的反应。因此，这项研究的结果将支持相对准确的健康风险评估和流行病学研究，而无需复杂或详细的输入数据。