STATISTICAL MODELS IN TOXICOLOGY AND BIOCHEMISTRY

毒理学和生物化学的统计模型

• 批准号: 3918684
• 负责人: C T PORTIER
• 金额: --
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/3918684
• 关键词: cancer risk; chemical carcinogenesis; environment related neoplasm /cancer; environmental toxicology; mathematical model; model design /development; physiology; statistics /biometry

Mathematical and statistical models are important tools in the design, analysis and interpretation of experiments in toxicology and biochemistry. However, many of the properties of the existing models are poorly understood. In addition, many of the existing models do not adequately describe current research findings in these areas. The goal of this project is to increase our understanding of the use and application of existing models in toxicology and biochemistry and to develop and implement new models to aid in explaining new research findings. One research effort concerns the use of physiologically based pharmacokinetic models in estimating carcinogenic risk from exposure to chemicals. A method was developed for incorporating all the sources of variability into the risk estimation procedure to arrive at an estimate of the overall variability. It was shown that the use of these models was likely to increase the variability of the risk estimates. In another study, the ability of carcinogenicity data to estimate parameters in a clonal two-stage model of carcinogenesis was examined. The findings indicated that the carcinogenicity data was inadequate for this purpose and additional information must be used. Research on this topic is continuing with a focus on redesigning carcinogenicity experiments to provide better information on these model parameters. Other research topics concern correcting for survival differences in animal carcinogenicity data and the potential risks from using inappropriate models in estimating risks of developmental defects from exposure to chemicals.

数学和统计模型是重要的工具 毒理学实验的设计、分析和解释 和生物化学。然而，现有的许多属性 模特们对此知之甚少。此外，许多现有的 模型不能充分描述当前的研究结果 这些区域。这个项目的目标是增加我们的 了解现有模型的使用和应用情况 毒理学和生物化学，并开发和实施新的模式 以帮助解释新的研究发现。一项研究成果 涉及基于生理学的药代动力学模型的使用 估计暴露在化学品中的致癌风险。一个 开发了一种方法来整合所有的资源 在风险评估过程中引入可变性，以得出 对总体变异性的估计。这表明，使用 这些模型可能会增加风险的可变性。 估计。在另一项研究中，致癌数据的能力 在一个克隆的两阶段模型中估计参数 观察其致癌性。调查结果显示， 致癌性数据不足以达到这一目的，并补充了 必须使用信息。对这一主题的研究仍在继续 重点是重新设计致癌实验，以提供 更好地了解这些模型参数。其他研究 关于纠正动物存活率差异的主题 致癌性数据和使用的潜在风险 估计发育缺陷风险的不适当模型 因为接触到了化学物质。