Technology-Enabled Clinical Trials

Abstract

The complexity and costs associated with traditional randomized, controlled trials have increased exponentially over time, and now threaten to stifle the development of new drugs and devices. Nevertheless, the growing use of electronic health records, mobile applications, and wearable devices offers significant promise for transforming clinical trials, making them more pragmatic and efficient. However, many challenges must be overcome before these innovations can be implemented routinely in randomized, controlled trial operations. In October of 2018, a diverse stakeholder group convened in Washington, DC, to examine how electronic health record, mobile, and wearable technologies could be applied to clinical trials. The group specifically examined how these technologies might streamline the execution of clinical trial components, delineated innovative trial designs facilitated by technological developments, identified barriers to implementation, and determined the optimal frameworks needed for regulatory oversight. The group concluded that the application of novel technologies to clinical trials provided enormous potential, yet these changes needed to be iterative and facilitated by continuous learning and pilot studies.

Precision Medicine in TAVR: How to Select the Right Device for the Right Patient

“…8 Ubiquitous availability of electronic health records and other technologies should be leveraged to facilitate the conduct of large, pragmatic, technology-enabled, comparativeeffectiveness, randomized trials incorporating streamlined operational processes. 9 For example, the National Patient-Centered Clinical Research Network (PCORnet), an electronic health record data infrastructure standardized into interoperable common data models, has been used to conduct a randomized controlled trial of 15,000 participants in the United States at a fraction of the usual cost. The investigators of the Aspirin Dosing-A Patient-centric Trial Assessing Benefits and Long-term Effectiveness (ADAPTABLE) trial capitalized on the availability of electronic health records, online study platforms, and health plan claims to evaluate the comparative effectiveness of 2 doses of aspirin in the secondary prevention of atherosclerotic cardiovascular disease.…”

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“…A BDA está sendo usada para inscrever indivíduos em estudos clínicos, fornecendo plataformas on-line que coletam informações detalhadas de estudos phase of RCTs termed "technology-enabled clinical trials", and streamline research efforts using innovative approaches. 48 The most recent example of such a trial has been the Apple Heart study, which enrolled a large number of patients over a very short period of time without any on-site visits, and was able to successfully identify patients at risk for atrial fibrillation. 16 Similarly, another study, HEARTLINE, is currently underway, which aims to enroll patients using the Apple Watch to detect atrial fibrillation as well as study its impact on reducing stroke.…”

“…47 Grupos de diversas partes interessadas colaboraram para destacar a próxima fase dos estudos clínicos randomizados, denominados "estudos clínicos habilitados para tecnologia" e agilizar os esforços de pesquisa usando abordagens inovadoras. 48 O exemplo mais recente desse tipo de estudo foi o Apple Heart, que inscreveu um grande número de pacientes por um período muito curto, sem visitas ao centro, e conseguiu identificar com sucesso pacientes com risco de fibrilação atrial. 16 Há outro estudo em andamento, o HEARTLINE, que visa inscrever pacientes usando o Apple Watch para detectar fibrilação atrial, bem como estudar seu impacto sobre redução do AVC.…”

Feasibility of Incorporating Voice Technology and Virtual Assistants in Cardiovascular Care and Clinical Trials

“…These costs are driven by increasing trial sizes, globalization of recruitment, study monitoring, and administrative staff costs. Numerous initiatives have been proposed to combat these rising costs, such as a reduction in the complexity of trial design by reducing study visits and minimizing manual data collection [ 4 ] and by the development of innovative endpoint capture strategies [ 5 ••].…”