Blockchain-based Clinical Trials: A Meta-Model Framework for Enhancing Security and Transparency with a Novel Algorithm

Aymen Anwar, S. B. Goyal, Tony Jan

Research output: Contribution to journalArticlepeer-review

Abstract

Clinical trials are crucial to medication research, but data security, transparency, and integrity issues often arise. Blockchain technology offers a decentralized, tamper-proof framework for clinical trial data management, promising to overcome these issues. Current blockchain-based clinical trial platforms lack scalability, interoperability, and integrity. A meta-model paradigm for blockchain-based clinical trial security and transparency addresses these constraints. The system employs a unique algorithm with smart contracts and consensus procedures to protect data privacy, reduce redundancy, and promote platform compatibility. The algorithm aims to maximize resource consumption and reduce computational overhead while ensuring security and trust. To improve security and transparency, we analyze the proposed meta-model framework utilizing performance, scalability, and security metrics and benchmarks. We observed that the meta-model framework and algorithm are efficient, scalable, and safe, laying the groundwork for future research. In particular, the framework can minimize clinical trial costs and time while improving data quality, traceability, and accountability. The suggested meta-model framework and algorithm can improve blockchain-based clinical trial security and transparency, making data management more trustworthy and efficient.

Original languageEnglish
Pages (from-to)1380-1392
Number of pages13
JournalInternational Journal of Technology
Volume14
Issue number6
DOIs
Publication statusPublished - 2023

Keywords

  • Blockchain
  • Clinical trials
  • Data privacy
  • Smart contracts
  • Transparency

Fingerprint

Dive into the research topics of 'Blockchain-based Clinical Trials: A Meta-Model Framework for Enhancing Security and Transparency with a Novel Algorithm'. Together they form a unique fingerprint.

Cite this