Prichard M N, Shipman C
Department of Microbiology and Immunology, School of Medicine, University of Michigan, Ann Arbor 48109-1078.
Antiviral Res. 1990 Oct-Nov;14(4-5):181-205. doi: 10.1016/0166-3542(90)90001-n.
Nearly four generations of investigators have studied combined drug effects. Their methods of generating and analyzing data have changed dramatically over the years but the basic problem has not. This review examines the inherent difficulties in analyzing combined drug effects and evaluates modern methods of describing these interactions. Researchers have traditionally used two-dimensional (2-D) methods to approximate the actual three-dimensional (3-D) nature of drug interactions. We conclude that these 2-D methods are often inadequate when used to analyze synergistic and antagonistic drug interactions in antiviral and anticancer chemotherapy. We propose a direct and pragmatic 3-D approach to the problem, made possible by microcomputers and sophisticated graphics programs. This procedure directly elucidates the shape of the dose-response surface, identifies the regions of statistically significant synergy and antagonism, and quantitates these effects. It also greatly simplifies the problem since a 3-D surface presents complete drug interactions in a way that can be easily interpreted. We will show that understanding the shape of the resulting 3-D surface is essential to an understanding of complex drug interactions. This new method facilitates the rigorous analysis of drug-drug interactions and offers investigators powerful new tools to analyze combinations of antiviral and anticancer drugs.
近四代研究人员都在研究联合用药的效果。多年来，他们生成和分析数据的方法发生了巨大变化，但基本问题依然存在。这篇综述探讨了分析联合用药效果时存在的固有困难，并评估了描述这些相互作用的现代方法。传统上，研究人员使用二维（2-D）方法来近似药物相互作用实际的三维（3-D）性质。我们得出结论，当用于分析抗病毒和抗癌化疗中的协同和拮抗药物相互作用时，这些二维方法往往并不充分。我们针对这个问题提出了一种直接且实用的三维方法，借助微型计算机和复杂的图形程序得以实现。这个过程直接阐明了剂量反应表面的形状，确定了具有统计学显著协同和拮抗作用的区域，并对这些效应进行量化。它还极大地简化了问题，因为三维表面以一种易于解释的方式呈现了完整的药物相互作用。我们将表明，理解所得三维表面的形状对于理解复杂的药物相互作用至关重要。这种新方法有助于对药物相互作用进行严谨分析，并为研究人员提供了强大的新工具来分析抗病毒和抗癌药物的组合。
