Automation and Data Integrity in Regulatory Submissions: Innovations for Decentralized Clinical Trials
DOI:
https://doi.org/10.32628/CSEIT251112105Keywords:
Decentralized Clinical Trials (DCTs), Regulatory Automation, Data Integrity, AI-driven Monitoring, Blockchain TraceabilityAbstract
This article explores the evolving landscape of regulatory submissions in clinical trials, with a particular focus on the challenges and opportunities presented by decentralized clinical trials (DCTs). It examines the role of automation in streamlining regulatory document preparation and validation processes, highlighting the benefits of improved accuracy, enhanced productivity, and accelerated timelines. The article delves into the unique data integrity challenges posed by DCTs, including the integration of diverse data sources such as wearables, mobile applications, and remote monitoring tools. It discusses innovative solutions for ensuring regulatory compliance, such as AI-driven monitoring systems, blockchain technology for audit trails, and automated query resolution workflows. The importance of traceability in regulatory submissions is emphasized, along with its role in enhancing reproducibility and accountability in clinical research. The article also addresses the impact of these changes on statistical programming, outlining the challenges faced by programmers and strategies for regulatory-compliant data processing. Finally, it looks toward future directions in automation and data integrity, exploring the potential of AI/ML integration for adaptive workflows and the development of seamless connections between clinical programming tools and regulatory platforms. Throughout, the article underscores the industry's ongoing efforts to balance technological advancement with regulatory compliance and data integrity in the pursuit of more efficient and effective clinical trials.
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