Concentration-time-effect modeling of agent combinations

描述：该项目的总体目标是进一步开发和验证 一个新的综合浓度-时间-效果模型范例，创建于 RRI 0742的最后3年资助期，适用于单一代理和高级订单 用于抗癌化学疗法和其它药理学的药剂的组合 新的重点是测量单个细胞 反应，细胞反应异质性定量，分子检测 目标，以及分子靶向剂的使用。最后的造型 本项目将产生一个范例，旨在弥合差距 传统的药物计量学和新时代的分子生物学 生物信息学具体目标包括：1.一种新的 数学！.统计建模范式，用于描述 单药和双药，三药， 4-试剂和5-试剂组合，将在一个充分表征， 简单的体外抗增殖试验，总生长试验（TGA）。具体 抗癌剂的组合将包括经典的临床使用的 药物和新的分子靶向信号转导抑制剂。2.一 具有自动图像分析的多路延时视频系统 将开发数字视频记录中细胞的跟踪， 细胞对抗癌剂的反应的详细分析将迅速完成。 3.增殖和细胞死亡响应的数学/统计模型 单一抗癌剂和药剂组合，其包括单独的 生长延迟、生长减慢、生长停滞、凋亡和 其他形式的细胞死亡，将提供更详细的知识 的细胞反应。4. Hill的D-最优统计设计方法 根据RR 1 0742开发的单药浓度-效应模型 浓度效应研究，将进一步开发应用于 具体目标#1和#3中的复杂研究。5.一个互联网网站将 创建给科学的公众评估：丰富的数据集产生; 开发的数据分析和建模工具;结果;以及讨论室 用于浓度-时间-效应和协同作用建模的一般主题。

DESCRIPTION: The overall aim of the project is to further develop and validate a new comprehensive concentration-time-effect modeling paradigm, created during the last 3-year funding period of RRI 0742 for single agents and for high order combinations of agents, for anticancer chemotherapy and other pharmacological applications, with new emphases on the measurement of individual cell responses, cell response heterogeneity quantification, assays of molecular targets, and the use of molecularly-targeted agents. The final modeling paradigm which will result from this project is intended to bridge the gap between traditional pharmacometrics and the new era of molecular bioinformatics. The Specific Aims include: 1. The validity and utility of a new mathematical! . statistical modeling paradigm, derived to describe concentration-time-effect phenomena for single agents and 2-agent, 3-agent, 4-agent and 5-agent combinations, will be investigated in a well-characterized, simple in vitro antiproliferation assay, the total growth assay (TGA). Specific combinations of anticancer agents will include both classic clinically-used agents and novel molecularly-targeted signal transduction inhibitors. 2. A multiplex time lapse video system (mpTLV) with automated image analysis tracking of cells in the digital video record will be developed, to allow detailed analysis of cellular response to anticancer agents to be done rapidly. 3. Mathematical/statistical models of proliferative and cell death response to single anticancer agents and combinations of agents, that include individual cell responses of growth delay, growth slow-down, growth arrest, apoptosis, and other forms of cell death, will be derived to provide a more detailed knowledge of cellular response. 4. D-optimal statistical design methodology for the Hill concentration-effect model developed under RR1 0742 for single agent concentration-effect studies, will be further developed for applications to the complex studies in Specific Aims #1 and #3. 5. An Internet Web site will be created to give the scientific public assess to: the rich data sets generated; the data analysis and modeling tools developed; results; and a discussion room for the general topic of concentration-time-effect and synergy modeling.