Recruiting candidates globally and across multiple sites in different geographic regions is necessary to speed up the enrollment of clinical trials. While patient enrollment can benefit from this globalization, initiating clinical trials has become much more complicated. In the start-up stage, the sites must be selected out of a set of potential candidates around the globe based on the specifics of those clinical trials, such as protocols, operational costs, and recruitment deadlines. Sites in one region can be very distinct from sites in another area. Yet, a common mistake in selecting sites is to rely on too little knowledge or subjective data. Poor selection decisions can lead to study delays and prolong the time to market for life-saving treatments. Thus, this paper proposes a novel framework to aid the decision-making in the (GSSP). To ensure that our framework accurately captures the uncertainty in recruitment time, we adopt a risk-based constraint that accounts for random patient enrollment. The extensive computational studies help quantify significant time-cost trade-offs as a potential solution to control the costs of conducting a trial.

中文翻译：

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具有概率约束的临床地点选择问题

为了加快临床试验的招募速度，有必要在全球范围内以及不同地理区域的多个地点招募候选人。虽然患者入组可以从这种全球化中受益，但启动临床试验却变得更加复杂。在启动阶段，必须根据这些临床试验的具体情况（例如协议、运营成本和招募截止日期）从全球范围内的一组潜在候选者中选择试验地点。一个区域中的站点可能与另一区域中的站点非常不同。然而，选择站点时的一个常见错误是依赖太少的知识或主观数据。错误的选择决策可能会导致研究延迟并延长挽救生命的治疗药物的上市时间。因此，本文提出了一个新的框架来帮助（GSSP）中的决策。为了确保我们的框架准确捕捉招募时间的不确定性，我们采用基于风险的约束来考虑随机患者招募。广泛的计算研究有助于量化重要的时间成本权衡，作为控制试验成本的潜在解决方案。