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@article{197466,
        author = {Shankar Rameshwar Godve and Shubham Sudhakar Mante and Sayli Sadanand Taktode and Shital Kailash Raut},
        title = {AI-Based Pharmacovigilance: Future of Drug Safety Monitoring},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {6530-6534},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197466},
        abstract = {Pharmacovigilance (PV) is a critical component of healthcare systems aimed at ensuring drug safety through the detection, assessment, and prevention of adverse drug reactions (ADRs). Traditional PV systems are limited by underreporting, delayed signal detection, and the inability to process large datasets efficiently. Artificial Intelligence (AI) has emerged as a transformative technology capable of addressing these limitations. AI techniques such as machine learning (ML), natural language processing (NLP), and deep learning (DL) enable automated data processing, early signal detection, and real-time monitoring. Studies have shown that AI-based systems improve ADR detection accuracy and significantly reduce processing time. This review discusses the applications, advantages, challenges, and future prospects of AI in pharmacovigilance.},
        keywords = {Pharmacovigilance, Artificial Intelligence, Adverse Drug Reactions, Machine Learning, Drug Safety.},
        month = {April},
        }