Background:

Clinical trials, conducted efficiently and with the utmost integrity, are a key component in identifying effective vaccines, therapies, and other interventions urgently needed to solve the COVID-19 crisis. Yet launching and implementing trials with the rigor necessary to produce convincing results is a complicated and time-consuming process. Balancing rigor and efficiency involves relying on designs that employ flexible features to respond to a fast-changing landscape, measuring valid endpoints that result in translational actions and disseminating findings in a timely manner. We describe the challenges involved in creating infrastructure with potential utility for shared learning.

Methods:

We have established a shared infrastructure that borrows strength across multiple trials. The infrastructure includes an endpoint registry to aid in selecting appropriate endpoints, a registry to facilitate establishing a Data & Safety Monitoring Board, common data collection instruments, a COVID-19 dedicated design and analysis team, and a pragmatic platform protocol, among other elements.

Results:

The authors have relied on the shared infrastructure for six clinical trials for which they serve as the Data Coordinating Center and have a design and analysis team comprising 15 members who are dedicated to COVID-19. The authors established a pragmatic platform to simultaneously investigate multiple treatments for the outpatient with adaptive features to add or drop treatment arms.

Conclusion:

The shared infrastructure provides appealing opportunities to evaluate disease in a more robust manner with fewer resources and is especially valued during a pandemic where efficiency in time and resources is crucial. The most important element of the shared infrastructure is the pragmatic platform. While it may be the most challenging of the elements to establish, it may provide the greatest benefit to both patients and researchers.

中文翻译：

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COVID-19 大流行中的临床试验：在快速变化的环境中持续学习的共享基础设施

 背景：

高效且高度诚信地进行的临床试验是确定解决 COVID-19 危机急需的有效疫苗、疗法和其他干预措施的关键组成部分。然而，为了产生令人信服的结果而严格启动和实施试验是一个复杂且耗时的过程。平衡严谨性和效率涉及依靠采用灵活功能的设计来应对快速变化的环境，测量有效的终点以产生转化行动并及时传播研究结果。我们描述了创建具有共享学习潜在效用的基础设施所涉及的挑战。

 方法：

我们建立了一个共享的基础设施，可以在多次试验中借用力量。该基础设施包括帮助选择适当端点的端点注册表、促进建立数据和安全监控委员会的注册表、通用数据收集工具、COVID-19 专用设计和分析团队以及务实的平台协议等。

 结果：

作者依靠共享基础设施进行了六项临床试验，他们作为数据协调中心，并拥有一个由 15 名专门研究 COVID-19 的成员组成的设计和分析团队。作者建立了一个实用的平台，可以同时研究门诊患者的多种治疗方法，并具有添加或删除治疗组的自适应功能。

 结论：

共享基础设施提供了利用更少资源以更稳健的方式评估疾病的诱人机会，在时间和资源效率至关重要的大流行期间尤其受到重视。共享基础设施最重要的要素是务实的平台。虽然它可能是最具挑战性的要素，但它可能为患者和研究人员提供最大的利益。