Greco W R, Park H S, Rustum Y M
Grace Cancer Drug Center, Roswell Park Memorial Institute, New York State Department of Health, Buffalo 14263.
Cancer Res. 1990 Sep 1;50(17):5318-27.
This report describes the application of a new approach, the universal response surface approach, to the quantitative assessment of drug interaction, i.e., the determination of synergism, antagonism, additivity, potentiation, inhibition, and coalitive action. The specific drug combination and experimental growth system for this introductory application was that of 1-beta-D-arabinofuranosylcytosine (ara-C) and cisplatin with simultaneous drug exposure (1, 3, 6, 12, or 48 h) against L1210 leukemia in vitro. To quantitate the type and degree of drug interaction, a model was fitted using nonlinear regression to the data from each separate experiment, and parameters were estimated (K. C. Syracuse and W. R. Greco, Proc. Biopharm. Sect. Am. Stat. Assoc., 127-132, 1986). The parameters included the maximum cell density over background in absence of drug, the background cell density in presence of infinite drug, the 50% inhibitory concentrations and concentration-effect slopes for each drug, and a synergism-antagonism parameter, alpha. A positive alpha indicates synergism, a negative alpha, antagonism, and a zero alpha, additivity. Maximal synergy was found with a 3-h exposure of ara-C + cisplatin, with alpha = 3.08 +/- 0.96 (SE) and 2.44 +/- 0.70 in two separate experiments. Four different graphic representations of the raw data and fitted curves provide visual indications of goodness of fit of the estimated dose-response surface to the data and visual indications of the intensity of drug interaction. The universal response surface approach is mathematically consistent with the traditional isobologram approach but is more objective, is more quantitative, and is more easily automated. Although specifically developed for in vitro cancer chemotherapy applications, the universal response surface approach should prove to be useful in the fields of pharmacology, toxicology, epidemiology, and biomedical science in general.
本报告描述了一种新方法——通用响应面法在药物相互作用定量评估中的应用,即协同作用、拮抗作用、相加作用、增强作用、抑制作用和联合作用的测定。本次初步应用的具体药物组合和实验生长系统是1-β-D-阿拉伯呋喃糖基胞嘧啶(阿糖胞苷)和顺铂,同时给药(1、3、6、12或48小时),用于体外抗L1210白血病。为了定量药物相互作用的类型和程度,使用非线性回归对每个单独实验的数据进行模型拟合,并估计参数(K.C. Syracuse和W.R. Greco,《美国统计协会生物制药分会论文集》,第127 - 132页,1986年)。这些参数包括无药物时高于背景的最大细胞密度、存在无限药物时的背景细胞密度、每种药物的50%抑制浓度和浓度 - 效应斜率,以及一个协同 - 拮抗参数α。α为正值表示协同作用,α为负值表示拮抗作用,α为零表示相加作用。阿糖胞苷 + 顺铂暴露3小时时发现最大协同作用,在两个单独实验中α分别为3.08±0.96(标准误)和2.44±0.70。原始数据和拟合曲线的四种不同图形表示提供了估计的剂量 - 反应面与数据拟合优度的直观指示以及药物相互作用强度的直观指示。通用响应面法在数学上与传统的等效线图法一致,但更客观、更定量且更易于自动化。尽管通用响应面法是专门为体外癌症化疗应用开发的,但总体而言,它在药理学、毒理学、流行病学和生物医学科学领域应会证明是有用的。