Title: Optimal designs for identifying effective doses in drug combination studies Show Chinese title

Title: 药物联合研究中确定有效剂量的最佳设计

Abstract: We consider the optimal design problem for identifying effective dose combinations within drug combination studies where the effect of the combination of two drugs is investigated. Drug combination studies are becoming increasingly important as they investigate potential interaction effects rather than the individual impacts of the drugs. In this situation, identifying effective dose combinations that yield a prespecified effect is of special interest. If nonlinear surface models are used to describe the dose combination-response relationship, these effective dose combinations result in specific contour lines of the fitted response model. We propose a novel design criterion that targets the precise estimation of these effective dose combinations. In particular, an optimal design minimizes the width of the confidence band of the contour lines of interest. Optimal design theory is developed for this problem, including equivalence theorems and efficiency bounds. The performance of the optimal design is illustrated in several examples modeling dose combination data by various nonlinear surface models. It is demonstrated that the proposed optimal design for identifying effective dose combinations yields a more precise estimation of the effective dose combinations than commonly used ray or factorial designs. This particularly holds true for a case study motivated by data from an oncological dose combination study. Show Chinese abstract

Abstract: 我们研究了在药物联合研究中确定有效剂量组合的最佳设计问题，在这种研究中，会调查两种药物联合使用的效应。随着药物联合研究越来越重要，因为它们探索的是潜在的交互效应而非单一药物的影响，识别产生预设效应的有效剂量组合显得尤为重要。如果使用非线性表面模型来描述剂量-联合反应关系，这些有效剂量组合对应于拟合响应模型的特定等高线。我们提出了一种新的设计标准，旨在精确估计这些有效剂量组合。特别是，最优设计最小化了感兴趣等高线置信带的宽度。针对此问题发展了最优设计理论，包括等价定理和效率界限。在几个通过各种非线性表面模型模拟剂量组合数据的例子中展示了最优设计的表现。结果表明，所提出的用于识别有效剂量组合的最优设计比常用的射线或析因设计能更精确地估计有效剂量组合。这一点在一项由肿瘤学剂量组合研究数据启发的案例研究中尤为明显。