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Digitizing clinical trials.
npj Digital Medicine ( IF 12.4 ) Pub Date : 2020-07-31 , DOI: 10.1038/s41746-020-0302-y
O T Inan 1 , P Tenaerts 2 , S A Prindiville 3 , H R Reynolds 4 , D S Dizon 5 , K Cooper-Arnold 6, 7 , M Turakhia 8 , M J Pletcher 9 , K L Preston 10 , H M Krumholz 11, 12, 13 , B M Marlin 14 , K D Mandl 15 , P Klasnja 16 , B Spring 17 , E Iturriaga 18 , R Campo 18 , P Desvigne-Nickens 18 , Y Rosenberg 18 , S R Steinhubl 19 , R M Califf 20, 21
Affiliation  

Clinical trials are a fundamental tool used to evaluate the efficacy and safety of new drugs and medical devices and other health system interventions. The traditional clinical trials system acts as a quality funnel for the development and implementation of new drugs, devices and health system interventions. The concept of a “digital clinical trial” involves leveraging digital technology to improve participant access, engagement, trial-related measurements, and/or interventions, enable concealed randomized intervention allocation, and has the potential to transform clinical trials and to lower their cost. In April 2019, the US National Institutes of Health (NIH) and the National Science Foundation (NSF) held a workshop bringing together experts in clinical trials, digital technology, and digital analytics to discuss strategies to implement the use of digital technologies in clinical trials while considering potential challenges. This position paper builds on this workshop to describe the current state of the art for digital clinical trials including (1) defining and outlining the composition and elements of digital trials; (2) describing recruitment and retention using digital technology; (3) outlining data collection elements including mobile health, wearable technologies, application programming interfaces (APIs), digital transmission of data, and consideration of regulatory oversight and guidance for data security, privacy, and remotely provided informed consent; (4) elucidating digital analytics and data science approaches leveraging artificial intelligence and machine learning algorithms; and (5) setting future priorities and strategies that should be addressed to successfully harness digital methods and the myriad benefits of such technologies for clinical research.



中文翻译:

数字化临床试验。

临床试验是用于评估新药和医疗器械以及其他卫生系统干预措施的有效性和安全性的基本工具。传统的临床试验系统充当新药、设备和卫生系统干预措施的开发和实施的质量漏斗。“数字临床试验”的概念涉及利用数字技术来改善参与者的访问、参与、试验相关的测量和/或干预措施,实现隐蔽的随机干预分配,并有可能改变临床试验并降低其成本。2019年4月,美国国立卫生研究院(NIH)和美国国家科学基金会(NSF)举办了研讨会,汇集了临床试验、数字技术和数字分析领域的专家,讨论在临床试验中实施数字技术的策略同时考虑潜在的挑战。本立场文件以本次研讨会为基础,描述了数字化临床试验的最新技术,包括(1)定义和概述了数字化试验的组成和要素;(2) 使用数字技术描述招聘和保留;(3) 概述数据收集要素,包括移动健康、可穿戴技术、应用程序编程接口 (API)、数据数字传输,以及考虑数据安全、隐私和远程提供知情同意的监管监督和指导;(4) 阐明利用人工智能和机器学习算法的数字分析和数据科学方法;(5) 制定未来的优先事项和战略,以成功利用数字方法和此类技术对临床研究的无数好处。

更新日期:2020-07-31
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