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Data Validation and Verification Using Blockchain in a Clinical Trial for Breast Cancer: Regulatory Sandbox
Author(s) -
Tomonobu Hirano,
Tomomitsu Motohashi,
Kosuke Okumura,
Kentaro Takajo,
Taiyo Kuroki,
Daisuke Ichikawa,
Yutaka Matsuoka,
Eisuke Ochi,
Taro Ueno
Publication year - 2020
Publication title -
journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/18938
Subject(s) - sandbox (software development) , breast cancer , clinical trial , blockchain , computer science , medicine , medical physics , cancer , computer security , software engineering
Background The integrity of data in a clinical trial is essential, but the current data management process is too complex and highly labor-intensive. As a result, clinical trials are prone to consuming a lot of budget and time, and there is a risk for human-induced error and data falsification. Blockchain technology has the potential to address some of these challenges. Objective The aim of the study was to validate a system that enables the security of medical data in a clinical trial using blockchain technology. Methods We have developed a blockchain-based data management system for clinical trials and tested the system through a clinical trial for breast cancer. The project was conducted to demonstrate clinical data management using blockchain technology under the regulatory sandbox enabled by the Japanese Cabinet Office. Results We verified and validated the data in the clinical trial using the validation protocol and tested its resilience to data tampering. The robustness of the system was also proven by survival with zero downtime for clinical data registration during a Amazon Web Services disruption event in the Tokyo region on August 23, 2019. Conclusions We show that our system can improve clinical trial data management, enhance trust in the clinical research process, and ease regulator burden. The system will contribute to the sustainability of health care services through the optimization of cost for clinical trials.

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