Abstract：
Platform trials are generally regarded as an innovative approach to address clinical valuation of early stage candidates, regardless of modality as the evidence evolves. As a type of randomized clinical trial (RCT) design construct in which multiple interventions are evaluated concurrently against a common control group allowing new interventions to be added and the control group to be updated throughout the trial, they provide a dynamic and efficient mechanism to compare and potentially discriminate new treatment candidates. Their recent use in the evaluation of new therapies for COVID-19 has spurred new interest in the approach. The paucity of platform trials is less influenced by the novelty and operational requirements as opposed to concerns regarding the sharing of intellectual property (IP) and the lack of infrastructure to operationalize the conduct in the context of IP and data sharing. We provide a mechanism how this can be accomplished through the use of a digital research environment (DRE) providing a safe and secure platform for clinical researchers, quantitative and physician scientists to analyze and develop tools (e.g., models) on sensitive data with the confidence that the data and models developed are protected. A DRE, in this context, expands on the concept of a trusted research environment (TRE) by providing remote access to data alongside tools for analysis in a securely controlled workspace, while allowing data and tools to be findable, accessible, interoperable, and reusable (FAIR), version-controlled, and dynamically grow in size or quality as a result of each treatment evaluated in the trial.
摘要：
平台试验通常被认为是解决早期候选药物临床评估的创新方法，随着证据的发展，无论模态如何。作为一种随机临床试验（RCT）设计结构，其中多种干预措施与普通对照组同时进行评估，从而允许在整个试验中添加新的干预措施并更新对照组。它们提供了一种动态和有效的机制来比较和区分新的治疗候选人。他们最近在评估COVID-19新疗法中的使用激发了人们对该方法的新兴趣。平台试验的缺乏受到新颖性和操作要求的影响较小，而不是对知识产权（IP）共享和缺乏在知识产权和数据共享背景下进行操作的基础设施的担忧。我们提供了一种机制，如何通过使用数字研究环境（DRE）来实现这一目标，为临床研究人员提供安全可靠的平台。定量和医师科学家分析和开发工具(例如，模型)在敏感数据上，并确信开发的数据和模型受到保护。DRE,在这种情况下，通过在安全控制的工作空间中提供对数据的远程访问以及分析工具，扩展了可信研究环境(TRE)的概念，在允许数据和工具可查找的同时，可访问,可互操作，和可重复使用(FAIR)，版本控制，并且由于在试验中评估的每种治疗方法而在大小或质量上动态增长。
