STATISTICAL MODELS IN TOXICOLOGY AND BIOCHEMISTRY

这个项目旨在增加我们对使用和 数学和统计模型在毒理学和生物医学中的应用 生物化学和实施新的数学模型来帮助 解释当前的研究发现。这项研究工作探索了一种 不同的生物学领域，包括致癌， 药理学、发育生物学、神经学和免疫学。在癌症中 建模，主要成果包括(1)两个新的模型 癌症发生的详细研究(一个真正的干细胞模型 皮肤癌的发生和多途径、多阶段的研究模型 (2)开发新的利用方法 在构建机械设备时有关恶性和癌前状态的数据 模型；(3)将机理模型应用于癌前病变数据 和肿瘤同步；(4)开发了一种通用算法 从任意复杂的多阶段模型估计肿瘤发病率 以及(5)开发了将PBPK模型与肿瘤发病模型联系起来的方法。 在基于生理的药代动力学模型中，这组人有(1) 对TCDD的PBPK模型进行实质性改进并将其应用于研究 TCDDS对甲状腺激素代谢的影响；以及(2)制定了 在风险评估中使用机械模型。在风险评估中，这 该小组(1)与美国环保局合作评估TCDD；(2) 开发了使用配置文件估计基准剂量的代码 很有可能。

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 were studied in detail (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; (4) the development of a general algorithm for estimating tumor incidence from arbitrarily complicated multistage models and (5) developed methods to link PBPK models to tumor incidence models. In physiologically-based pharmacokinetic modeling, this group has (1) substantially improved a PBPK model for TCDD and applied it to study TCDDs effects on thyroid hormone metabolism; and (2)developed rules for using mechanistic models in risk assessment. In risk assessment, this group has (1) collaborated with EPA on the reasessment of TCDD; (2) developed code for estimating benchmarks doses using a profile likelihood.