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 一种新的全面的集中-时间-效果建模范式，在 最近3年的RRI 0742资助期，适用于单一代理商和高级订单 用于抗癌化疗和其他药理作用的药物组合 应用，新的重点是单个细胞的测量 反应，细胞反应异质性量化，分子分析 靶标，以及分子靶标制剂的使用。最终的建模 这个项目将产生的范例旨在弥合这一差距 在传统药物计量学和分子生物学新时代之间 生物信息学。具体目标包括：1.新制度的有效性和实用性 数学！。统计建模范式，派生出来描述 单一药剂和2-药剂、3-药剂、 4-剂和5-剂组合，将在一个很好的表征， 简单的体外抗增殖试验、总生长试验(TGA)。特定的 抗癌药物的组合将包括两种经典的临床使用药物 药物和新型分子靶向信号转导抑制剂。2.A 具有自动图像分析的多路延时视频系统(MpTLV) 将开发数字视频记录中的细胞跟踪，以允许 对细胞对抗癌药物的反应的详细分析将迅速完成。 3.增殖反应和细胞死亡反应的数学/统计模型 单一抗癌剂和药物组合，包括单独的 细胞对生长延迟、生长减慢、生长停滞、细胞凋亡和 其他形式的细胞死亡，将为我们提供更详细的知识 细胞反应的结果。4.D-Hill的最优统计设计方法 在RR10742下建立的单剂浓度-效应模型 浓度效应研究将进一步发展，以应用于 针对具体目标#1和#3.5的复杂研究。一个互联网网站将是 创建的目的是让科学公众评估：生成的丰富数据集； 开发的数据分析和建模工具；结果；以及讨论室 对于浓度-时间-效应和协同模型的一般主题。

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.