STATISTICAL MODELS IN TOXICOLOGY AND BIOCHEMISTRY

该项目旨在增加我们对使用的理解， 数学和统计模型在毒理学中的应用 生物化学和实施新的数学模型，以帮助 解释目前的研究成果。研究工作探索了一个 广泛的生物学领域，包括致癌作用，药理学， 发育生物学、神经学和免疫学。在癌症建模中， 主要成果包括：（1）两种新的致癌模型（a 皮肤癌发生的真干细胞模型和多途径， 研究结肠癌和肝癌的多阶段模型）;（2）开发 利用恶性和癌前状态数据的新方法 在建立机械模型时;（3）将机械模型应用于 癌前病变和肿瘤的数据;和（4） 开发一种用于估计肿瘤发病率的通用算法 任意复杂的多级模型。对于非癌症终点， 该小组的重点是（1）评估发展中的现有模型 毒理学，目的是寻找更好的模型;（2） 开发分析畸形学筛查的新方法， 免疫功能与宿主抗性的关系 暴露于免疫毒素。在基于生理的药代动力学中 建模，该小组已经（1）开发了TCDD的PBPK模型;（2） 建立了1-3，丁二烯的PBPK模型;（3）理论研究 受体结合和基因表达的模型和（4）探索了 本构表达式对风险估计的影响 生物标志物。在风险评估方面，该小组（l）与环境保护局合作， （2）评价了TCDD的剂量-反应关系 曲线及其与化学结构和活性的关系;（3） 开发/应用了一种致癌能力的测量方法， 校正剂量-反应形状。在神经学领域， 正在与NINDS一起应用多元平滑技术， 描述大脑区域和不同的 身体的一部分。根据《公约》的规定， 光滑样条方法估计率函数 药理学和生物化学。

This project is intended to increase our understanding of the use and application of mathematical and statistical models in toxicology and biochemistry and to implement new mathematical models to aid in explaining current research findings. The research effort explores a diverse range of biological areas including carcinogenesis, pharmacology, developmental biology, neurology and immunology. In cancer modeling, major accomplishments include (1) two new models of carcinogenesis (a model with true stem cells for skin carcinogenesis and a multipathway, multistage model for studying colon and liver cancer); (2) development of new methods for utilizing data on malignant and premalignant states when building a mechanistic model; (3) applying mechanistic models to data on premalignant lesions and tumors simultaneously; and (4) the development of a general algorithm for estimating tumor incidence from arbitrarily complicated multistage models. For non-cancer endpoints, this group has focused on (1) evaluating existing models in developmental toxicology with the intention of finding better models; and (2) developing new methods for analyzing teratology screens and modeling the relationship between immune function and host resistance following exposure to immunotoxicants. In physiologically-based pharmacokinetic modeling, this group has (l) developed a PBPK model for TCDD; (2) developed a PBPK model for 1-3, butadiene; (3) theoretically studied models for receptor binding and gene expression and (4) explored the effects of constitutive expression on risk estimates when using biomarkers. In risk assessment, this group has (l) collaborated with EPA on the reassessment of TCDD; (2) evaluated the shapes of dose-response curves and their relationship to chemical structure and activity; and (3) developed/applied a measure of carcinogenic potency which estimates and corrects for dose-response shape. In neurology, a research effort is underway with NINDS to apply multivariate smoothing techniques to characterize the relationship between areas of the brain and different parts of the body. A project was completed on the application of smoothing spline methods to the estimation of rate functions in pharmacology and biochemistry.