DETERMINATION OF SYNERGISM, ADDITIVITY & ANTAGONISM

本项目的具体目标是完成 一种新的统一客观的方法来定量评估药物 相互作用;即，以确定协同作用、加和性和 药物和其他药剂之间的拮抗作用。 问题是， 建议项目旨在解决的是，评估 药物相互作用：（1）是一项重要任务， 在一般生物医学研究中非常常见， 癌症研究;（2）与各种各样的 术语混乱;（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，其中许多有潜在的缺陷;（5）需要 标准的计算机软件执行;及（6）导致 摘要信息，这往往是不适当的或次优的 采用 为了纠正这种情况，初步工作已 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 分层广义非线性模型 对所用药物的连续或离散效应 浓度;一组模型拟合程序，包括 交互加权非线性回归与极大值 似然程序，包括交互式重新加权非线性 回归和最大似然估计;以及初步的 软件实现。 为了达到...的特定目的 完成方法的发展：（1）理论 和实际属性的统计模型和 将检查曲线拟合程序;（2）将拟合模型 真实的和模拟数据;（3）发现的缺陷， 理论和/或实际性质将被补救， 方法的变化和/或扩展;（4）实验设计 程序将被开发;和（5）模型库，曲线- 拟合技术、图形表示和实验 设计技术将在用户友好的计算机中实现 软件分发给感兴趣的科学家。 的 补充的方法将（1）有助于体外预测 体内和临床选择性毒性;（2）有助于筛选 简单的两种药物组合;（3）帮助研究 复杂的多种药物组合。 通过降低整体 体外药物组合实验的有用性，并通过帮助 在体内药物组合的有效设计和分析中， 实验 新方法将在以下领域得到广泛应用： 实验性癌症研究，流行病学，毒理学，一般 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.