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Improving Participant Recruitment in Clinical Trials: Comparative Analysis of Innovative Digital Platforms.

作者信息

Bikou Alexia Georgia, Deligianni Elena, Dermiki-Gkana Foteini, Liappas Nikolaos, Teriús-Padrón José Gabriel, Beltrán Jaunsarás Maria Eugenia, Cabrera-Umpiérrez Maria Fernanda, Kontogiorgis Christos

机构信息

Department of Medicine, Democritus University of Thrace, Alexandroupolis, Greece.

Life Supporting Technologies (LifeSTech), Superior Technical School of Telecommunication Engineers, Universidad Politécnica de Madrid (UPM), Madrid, Spain.

出版信息

J Med Internet Res. 2024 Dec 18;26:e60504. doi: 10.2196/60504.


DOI:10.2196/60504
PMID:39693619
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11694053/
Abstract

BACKGROUND: Pharmaceutical product development relies on thorough and costly clinical trials. Participant recruitment and monitoring can be challenging. The incorporation of cutting-edge technologies such as blockchain and artificial intelligence has revolutionized clinical research (particularly in the recruitment stage), enhanced secure data storage and analysis, and facilitated participant monitoring while protecting their personal information. OBJECTIVE: This study aims to investigate the use of novel digital platforms and their features, such as e-recruitment, e-consent, and matching, aiming to optimize and expedite clinical research. METHODS: A review with a systematic approach was conducted encompassing literature from January 2000 to October 2024. The MEDLINE, ScienceDirect, Scopus, and Google Scholar databases were examined thoroughly using a customized search string. Inclusion criteria focused on digital platforms involving clinical trial recruitment phases that were in English and had international presence, scientific validation, regulatory approval, and no geographic limitations. Literature reviews and unvalidated digital platforms were excluded. The selected studies underwent meticulous screening by the research team, ensuring a thorough analysis of novel digital platforms and their use and features for clinical trials. RESULTS: A total of 24 digital platforms were identified that supported clinical trial recruitment phases. In general, most of them (n=22, 80%) are headquartered and operating in the United States, providing a range of functionalities including electronic consent (n=14, 60% of the platforms), participant matching, and monitoring of patients' health status. These supplementary features enhance the overall effectiveness of the platforms in facilitating the recruitment process for clinical trials. The analysis and digital platform findings refer to a specific time frame when the investigation took place, and a notable surge was observed in the adoption of these novel digital tools, particularly following the COVID-19 outbreak. CONCLUSIONS: This study underscores the vital role of the identified digital platforms in clinical trials, aiding in recruitment, enhancing patient engagement, accelerating procedures, and personalizing vital sign monitoring. Despite their impact, challenges in accessibility, compatibility, and transparency require careful consideration. Addressing these challenges is crucial for optimizing digital tool integration into clinical research, allowing researchers to harness the benefits while managing the associated risks effectively.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4cc/11694053/0764ef1b8728/jmir_v26i1e60504_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4cc/11694053/0764ef1b8728/jmir_v26i1e60504_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4cc/11694053/0764ef1b8728/jmir_v26i1e60504_fig1.jpg

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Improving Participant Recruitment in Clinical Trials: Comparative Analysis of Innovative Digital Platforms.

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本文引用的文献

[1]
The Digital Platform and Its Emerging Role in Decentralized Clinical Trials.

J Med Internet Res. 2024-9-3

[2]
Optimizing Clinical Trial Eligibility Design Using Natural Language Processing Models and Real-World Data: Algorithm Development and Validation.

JMIR AI. 2024-7-29

[3]
Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

PLoS One. 2024-3-11

[4]
Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design.

Pharmaceutics. 2023-7-10

[5]
Applying Systems Thinking to Inform Decentralized Clinical Trial Planning and Deployment.

Ther Innov Regul Sci. 2023-9

[6]
Artificial Intelligence Applied to clinical trials: opportunities and challenges.

Health Technol (Berl). 2023

[7]
Digitally enabled decentralised research: opportunities to improve the efficiency of clinical trials and observational studies.

BMJ Evid Based Med. 2023-10

[8]
Patient-Centric Product Development: A Summary of Select Regulatory CMC and Device Considerations.

J Pharm Sci. 2023-4

[9]
Electronic Consent at US Cancer Centers: A Survey of Practices, Challenges, and Opportunities.

JCO Clin Cancer Inform. 2023-1

[10]
Assessing the Financial Value of Decentralized Clinical Trials.

Ther Innov Regul Sci. 2023-3

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