Leveraging Artificial Intelligence for Data Integrity, Transparency, and Security in Technology-enabled Improvements to Clinical Trial Data Management in Healthcare
Abstract
INTRODUCTION
The management of clinical trial data is an essential component of medical research, where accuracy, security, and transparency directly impact the validity of outcomes. However, conventional methods often face challenges in maintaining data integrity and compliance with regulatory standards. The transformative role of Artificial Intelligence (AI) in enhancing these aspects by leveraging machine learning and analytics offers promising capabilities to improve data validation, detect inconsistencies, and secure sensitive information, thereby increasing credibility among researchers, participants, and regulators. The aim of this study is to explore the transformative potential of artificial intelligence in enhancing clinical trial data management. It specifically investigates whether AI can improve data integrity, transparency, and security, thus making the results credible to the researcher, participant, and regulatory bodies involved.
METHODS
The study employs machine learning algorithms and advanced analytics to investigate the role of AI in identifying data anomalies, verifying the accuracy of information, and validating data processes. Case studies and real-world applications are presented to highlight how AI enables real-time monitoring, reporting, and verification of regulatory compliance. It also analyzes encryption and access control systems powered by AI, ensuring that sensitive clinical trial data is protected against breaches and unlawful access.…
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