Article
Version 1
Preserved in Portico This version is not peer-reviewed
Blockchain-Enabled Quality Improvement Digital Twin for Clinical Trials
Version 1
: Received: 23 May 2023 / Approved: 24 May 2023 / Online: 24 May 2023 (04:46:13 CEST)
How to cite: Vatankhah Barenji, R.; Ebrahimi Hariry, R. Blockchain-Enabled Quality Improvement Digital Twin for Clinical Trials. Preprints 2023, 2023051693. https://doi.org/10.20944/preprints202305.1693.v1 Vatankhah Barenji, R.; Ebrahimi Hariry, R. Blockchain-Enabled Quality Improvement Digital Twin for Clinical Trials. Preprints 2023, 2023051693. https://doi.org/10.20944/preprints202305.1693.v1
Abstract
Clinical trials are research studies performed on people that are aimed at evaluating a medical, surgical, or behavioural intervention. It is a primary way that researchers find out if a new treatment, like a new drug or diet, or medical device is safe and effective in people. In this paper blockchain technology is embedded in a digital twin aiming to improve the quality of clinical trials through the boost of data integrity among the quality-related activities, and to promote participants' safety. First, a blockchain-embedded quality-enabled digital twin is proposed and the interactions among the enablers and peers are highlighted. Then, a prototype of the proposed system is developed, and the data of a pilot trial is used to justify the applicability of the system. The results showed that the proposed system is efficient, and hence it is feasible to adopt into a clinical trial. With the successful development of the proposed system, it is promising to provide effective data integration and knowledge management for improving participant safety.
Keywords
Digital twin; Clinical trials; Quality by Design; Blockchain technology; Drug development
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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