With increasing interest in adaptive clinical trial designs, challenges are present to drug supply chain management which may offset the benefit of adaptive designs. Thus, it is necessary to develop an optimization tool to facilitate the decision making and analysis of drug supply chain planning. The challenges include the uncertainty of maximum drug supply needed, the shifting of supply requirement, and rapid availability of new supply at decision points. In this paper, statistical simulations are designed to optimize the pre-study medication supply strategy and monitor ongoing drug supply using real-time data collected with the progress of study. Particle swarm algorithm is applied when performing optimization, where feature extraction is implemented to reduce dimensionality and save computational cost.

翻译：随着适应性临床试验设计的日益受到关注，药物供应链管理面临诸多挑战，这些挑战可能抵消适应性设计带来的优势。因此，有必要开发一种优化工具，以促进药物供应链规划的决策制定与分析。这些挑战包括所需最大药物供应量的不确定性、供应需求的动态变化，以及在决策节点快速获取新供应的要求。本文设计了统计模拟方法，用于优化试验前药物供应策略，并利用试验进度实时收集的数据对持续药物供应进行监测。优化过程中采用了粒子群算法，并通过特征提取降低维度以节省计算成本。