The Next Horizon of Drug Development: External Control Arms and Innovative Tools to Enrich Clinical Trial Data.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ACS Applied Bio Materials Pub Date : 2024-05-01 Epub Date: 2024-03-25 DOI:10.1007/s43441-024-00627-4
Kelly H Zou, Chelsea Vigna, Aniketh Talwai, Rahul Jain, Aaron Galaznik, Marc L Berger, Jim Z Li
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引用次数: 0

Abstract

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.

Abstract Image

药物开发的下一个地平线:丰富临床试验数据的外部控制臂和创新工具。
开展临床试验(CT)的成本越来越高,设计和操作也越来越复杂。这些挑战存在于新型疗法的临床试验中,尤其是在肿瘤学和罕见病领域,因为这些领域的临床试验越来越多地针对范围较窄的患者群体。在本研究中,我们介绍了外部对照臂(ECA)和其他相关工具,如虚拟化和分散临床试验(DCT),以及利用标记化技术跟踪真实世界中临床试验受试者的能力。ECA 通常是通过确定适当的外部数据源来构建的,然后对其进行清理和标准化,以创建可用于分析的数据文件,最后将外部数据中的受试者与相关 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模拟受试者数据分析。通过实施数字医疗技术和设备、虚拟化和 DCT 的最新进展,可以将 CT 从以病例为中心的设计重新调整为虚拟、分散和以患者为中心的设计,从而减轻患者参与 CT 的负担并鼓励多样性。令牌化技术可将 CT 数据与真实世界数据(RWD)联系起来,创建更全面的纵向结果测量。这些工具为丰富 CT 数据以进行知情决策、减轻受试者负担和降低试验运营成本以及增强 CT 数据的洞察力提供了有力的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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