DETERMINATION OF SYNERGISM, ADDITIVITY & ANTAGONISM

该项目的具体目标是完成 一种新的统一客观定量评价药物的方法 相互作用；即确定协同性、可加性和 药物和其他药剂之间的对抗。这个问题就是 提出的项目旨在解决的是评估的问题 药物相互作用：(1)是一项重要的事业 在生物医学研究中非常常见，通常在 具体地说，癌症研究；(2)与各种各样的 命名混乱；(3)缺乏一致的实验设计 方法；(4)使用各种不同的数据进行 分析方法，其中许多方法存在潜在缺陷；(5)需求 用于其执行的标准计算机软件；和(6)导致 通常不恰当或不太理想的摘要信息 使用。作为补救这种情况的一种尝试，初步工作已经 开发了一种通用的响应面方法 定量评估药物相互作用。该方法包括 指一套一致的术语；一套可扩展的 与量测相关的多层广义非线性模型 对应用药物的连续或离散影响 浓度；一套模型拟合程序，包括 交互加权非线性回归和极大值 包含交互重加权非线性的似然算法 回归和最大似然估计；以及初步的 软件实施。实现……的具体目标 完成该方法的发展：(1)理论上 和实用性质的数理统计模型和 将研究曲线拟合程序；(2)模型将被拟合 对于真实数据和模拟数据；(3)在 理论和/或实际属性将通过以下方式进行补救 方法的改变和/或扩展；(4)实验设计 将制定程序；以及(5)模型库、曲线- 装配技术、图形表示和实验 设计技术将在用户友好的计算机上实现 分发给感兴趣的科学家的软件。这个 补充方法将(1)有助于体外预测 体内和临床选择性毒性；(2)辅助筛选 简单的两种药物组合；以及(3)帮助研究 复杂的多种药物组合。通过减少总体 体外药物联合实验的有用性，并通过辅助 体内药物组合的高效设计和分析 实验。新方法将在以下方面有广泛的应用 实验性癌症研究、流行病学、毒理学、总则 药理学，以及其他生物和生物医学领域。

The specific aim of this project is to complete the development of a new unified objective approach to quantitatively assess drug interactions; i.e., to determine synergism, additivity and antagonism among drugs and other agents. The problem which the proposed project is designed to solve is that the assessment of drug interactions: (1) is an important undertaking which is performed very commonly in biomedical research in general and in cancer research specifically; (2) is associated with a wide variety of confusing nomenclature; (3) lacks consistent experimental design approaches; (4) is performed with a wide variety of different data analysis approaches, many of which have underlying flaws; (5) needs standard computer software for its execution; and (6) results in summary information which is oftentimes improperly or suboptimally used. As an attempt to remedy this situation, initial work has been done to develop a universal response surface approach for quantitatively assessing drug interactions. The approach consists of a set of consistent terminology; a set of extendable hierarchical generalized nonlinear models relating measured effects, either continuous or discrete, to applied drug concentrations; a set of model fitting procedures including interactively reweighted nonlinear regression and maximum likelihood procedures including interactively reweighted nonlinear regression and maximum likelihood estimation; and a preliminary software implementation. To accomplish the specific aim of completing the development of the approach: (1) the theoretical and practical properties of the mathematical-statistical models and curve-fitting procedures will be examined; (2) models will be fit to both real and simulated data; (3) deficiencies found in theoretical and/or practical properties will be remedied with changes and/or extensions to the approach; (4) experimental design procedures will be developed; and (5) the library of models, curve- fitting techniques, graphical representations, and experimental design techniques will be implemented in user-friendly computer software for distribution to interested scientists. The complemented approach will (1) aid in the in vitro prediction of in vivo and clinical selective toxicity; (2) aid in the screening of simple tow drug combinations; and (3) aid in the study of complex multidrug combinations. By decreasing the overall usefulness of in vitro drug combination experiments, and by aiding in the efficient design and analysis of in vivo drug combination experiments. The new approach will have extensive applications in experimental cancer research, epidemiology, toxicology, general pharmacology, and other biological and biomedical fields.