Optimizing Drug Safety and Compliance in Real-Time by Using Block chain and Artificial Intelligence for Integrated Clinical Data Management and Pharmacovigilance

Optimizing Drug Safety and Compliance in Real-Time by Using Block chain and Artificial Intelligence for Integrated Clinical Data Management and Pharmacovigilance | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 13 May 2025 V1 Latest version Share on Optimizing Drug Safety and Compliance in Real-Time by Using Block chain and Artificial Intelligence for Integrated Clinical Data Management and Pharmacovigilance Author : Darshan Gowda B.S 0009-0003-4891-1655 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174713055.59099529/v1 193 views 96 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Pharmacovigilance (PV) and clinical data management (CDM) are essential for ensuring drug safety, efficacy, and regulatory compliance. However, traditional methods face significant challenges, including fragmented data, delayed adverse event reporting, and limited system interoperability. The integration of artificial intelligence (AI) and blockchain technology offers a transformative approach to addressing these limitations. AI-driven solutions, such as machine learning and natural language processing, enable real-time data validation, anomaly detection, and predictive analytics, improving the accuracy and efficiency of pharmacovigilance processes. Meanwhile, blockchain provides a secure, immutable, and transparent framework for clinical trial data storage, ensuring data integrity and compliance with regulatory standards. This review explores the synergistic application of AI and blockchain in CDM and PV, highlighting their potential to streamline workflows, reduce redundancies, and enhance global drug safety monitoring. While promising, widespread adoption faces obstacles such as scalability, regulatory adaptation, and organizational resistance. Addressing these challenges through collaborative efforts, regulatory harmonization, and technological refinements will be key to realizing the full potential of AI-blockchain integration in drug safety management. Supplementary Material File (pds-25-0331-file001.docx) Download 2.17 MB Information & Authors Information Version history V1 Version 1 13 May 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence (ai) blockchain technology clinical data management (cdm) drug safety monitoring pharmacovigilance (pv) real-time data Authors Affiliations Darshan Gowda B.S 0009-0003-4891-1655 [email protected] Dayananda Sagar University College of Pharmaceutical Sciences View all articles by this author Metrics & Citations Metrics Article Usage 193 views 96 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Darshan Gowda B.S. Optimizing Drug Safety and Compliance in Real-Time by Using Block chain and Artificial Intelligence for Integrated Clinical Data Management and Pharmacovigilance. Authorea . 13 May 2025. 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