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@article{182358,
        author = {Venkata Swamy Karam and Pete Boldingh},
        title = {Optimizing Clinical Data Management with Artificial Intelligence: Challenges and Opportunities},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {1762-1769},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182358},
        abstract = {Artificial Intelligence (AI) emerges as a transformative force in clinical data management (CDM), offering opportunities to improve efficiency, quality, and compliance in an increasingly complex regulatory landscape. This paper explores the integration of AI into clinical data workflows, focusing on data collection, electronic data capture, intelligent edit checks, data integrity, regulatory alignment, and study record management. Drawing on real-world practices and industry trends, we examine both the operational benefits and implementation challenges that face sponsors, CROs, and technology providers aiming to modernize data processes while maintaining GxP, the guidelines and regulations designed to ensure the quality, safety and efficacy of goods produced in regulated industries, compliance.},
        keywords = {NLP, AI, Clinical Data, Health},
        month = {July},
        }