To test the anticancer effect of combining two drugs targeting different biological pathways, the popular way to show synergistic effect of drug combination is a heat map or surface plot based on the percent excess the Bliss prediction using the average response measures at each combination dose. Such graphs, however, are inefficient in the drug screening process and it does not give a statistical inference on synergistic effect. To make a statistically rigorous and robust conclusion for drug combination effect, we present a two-stage Bliss independence response surface model to estimate an overall interaction index (τ) with 95% confidence interval (CI). By taking into all data points account, the overall τ with 95% CI can be applied to determine if the drug combination effect is synergistic overall. Using some example data, the two-stage model was compared to a couple of classic models following Bliss rule. The data analysis results obtained from our model reflect the pattern shown from other models. The application of overall τ helps investigators to make decision easier and accelerate the preclinical drug screening.

为了测试两种针对不同生物学途径的药物联合的抗癌作用，显示药物组合协同作用的流行方法是根据Bliss预测的过量百分比（使用每种组合剂量下的平均应答指标）得出的热图或表面图。但是，这些图形在药物筛选过程中效率低下，并且无法给出协同效应的统计推断。为了对药物联合作用做出统计学上严格而有力的结论，我们提出了一个两阶段的Bliss独立反应表面模型，以估计具有95％置信区间（CI）的总体相互作用指数（τ）。通过考虑所有数据点，具有95％CI的总体τ可以用于确定药物组合效应总体上是否具有协同作用。使用一些示例数据，根据Bliss规则，将两阶段模型与几个经典模型进行了比较。从我们的模型获得的数据分析结果反映了其他模型显示的模式。总体τ的应用有助于研究人员简化决策并加速临床前药物筛选。