Zou Kelly H, Vigna Chelsea, Talwai Aniketh, Jain Rahul, Galaznik Aaron, Berger Marc L, Li Jim Z
Viatris, Canonsburg, PA, USA.
Medidata Solutions, a Dassault Systèmes Company, Boston, MA, USA.
Ther Innov Regul Sci. 2024 May;58(3):443-455. doi: 10.1007/s43441-024-00627-4. Epub 2024 Mar 25.
Conducting clinical trials (CTs) has become increasingly costly and complex in terms of designing and operationalizing. These challenges exist in running CTs on novel therapies, particularly in oncology and rare diseases, where CTs increasingly target narrower patient groups. In this study, we describe external control arms (ECA) and other relevant tools, such as virtualization and decentralized clinical trials (DCTs), and the ability to follow the clinical trial subjects in the real world using tokenization. ECAs are typically constructed by identifying appropriate external sources of data, then by cleaning and standardizing it to create an analysis-ready data file, and finally, by matching subjects in the external data with the subjects in the CT of interest. In addition, ECA tools also include subject-level meta-analysis and simulated subjects' data for analyses. By implementing the recent advances in digital health technologies and devices, virtualization, and DCTs, realigning of CTs from site-centric designs to virtual, decentralized, and patient-centric designs can be done, which reduces the patient burden to participate in the CTs and encourages diversity. Tokenization technology allows linking the CT data with real-world data (RWD), creating more comprehensive and longitudinal outcome measures. These tools provide robust ways to enrich the CT data for informed decision-making, reduce the burden on subjects and costs of trial operations, and augment the insights gained for the CT data.
就设计和实施而言，开展临床试验（CTs）的成本越来越高，难度也越来越大。在开展针对新型疗法的临床试验时，这些挑战尤为突出，特别是在肿瘤学和罕见病领域，临床试验越来越多地针对更狭窄的患者群体。在本研究中，我们描述了外部对照臂（ECA）以及其他相关工具，如虚拟化和去中心化临床试验（DCTs），以及使用令牌化技术在现实世界中跟踪临床试验受试者的能力。ECA通常通过识别合适的外部数据源来构建，然后对其进行清理和标准化，以创建一个可供分析的数据文件，最后，将外部数据中的受试者与感兴趣的CT中的受试者进行匹配。此外，ECA工具还包括受试者层面的荟萃分析和用于分析的模拟受试者数据。通过应用数字健康技术和设备、虚拟化以及DCTs方面的最新进展，可以将CTs从以站点为中心的设计重新调整为虚拟、去中心化和以患者为中心的设计，这减轻了患者参与CTs的负担，并鼓励了多样性。令牌化技术允许将CT数据与真实世界数据（RWD）相链接，从而创建更全面和纵向的结果测量。这些工具提供了强大的方法来丰富CT数据，以便做出明智的决策，减轻受试者的负担和试验运营成本，并增强从CT数据中获得的见解。
