AI in Protecting Clinical Trial Data from Cyber Threats

Abstract

As the reliance on digital platforms in clinical trials increases, so does the vulnerability of sensitive research data to cyber threats. This paper explores the application of Artificial Intelligence (AI) in enhancing the security of clinical trial data, focusing on its role in ensuring the integrity and confidentiality of research findings. By leveraging machine learning algorithms, anomaly detection systems, and natural language processing, AI can identify potential security breaches in real time, assess risks, and automate responses to threats. Additionally, AI-driven predictive analytics can facilitate proactive measures to safeguard data throughout the clinical trial lifecycle. This paper discusses various AI techniques, case studies demonstrating their effectiveness, and the potential challenges in implementation, offering insights into best practices for integrating AI into clinical trial data protection strategies.