Paper Title
Use of artificial intelligence in pharmacovigilance -a systematic review
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Registration ID: IJNRD_305491
Published ID: IJNRD2504307
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Keywords
pharmacovigilance,adverse drug reaction, signal detection, artificial intiliigance, automation,machine learning.
Abstract
This systematic review examines the applications, effectiveness, challenges, and future prospects of artificial intelligence (AI) in pharmacovigilance. The study was motivated by the exponential growth in drug safety data volume and complexity, which has increasingly challenged traditional pharmacovigilance approaches that rely on manual review and statistical methods. Key findings reveal significant advancements in AI applications across multiple pharmacovigilance domains. AI-enhanced signal detection demonstrated 15-30% higher sensitivity in identifying adverse drug reactions and 20-40% reduction in false positives compared to traditional methods, with signals detected 2-6 months earlier. Natural language processing systems achieved >90% recall in literature screening and 85-95% concordance with expert assessments. Implementation analysis showed that 78% of surveyed pharmaceutical companies use at least one AI application in pharmacovigilance, with NLP for case processing being the most mature (62% implementation rate). The review identifies several challenges including data quality issues, workflow disruption, technical infrastructure requirements, and evolving regulatory frameworks. Cost-benefit analysis indicates implementation costs of $0.8-3.2 million with substantial efficiency gains, including 30-70% reduction in case processing time. Ethical considerations surrounding privacy, algorithmic fairness, transparency, and global equity are also highlighted. This research provides valuable insights for pharmaceutical companies, regulatory authorities, and healthcare systems seeking to enhance pharmacovigilance through AI technologies, ultimately improving patient safety through more timely and accurate adverse event detection.
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How To Cite (APA)
Swapnil shivaji shinde, Vyankatesh.R.Dharanguttikar, Parag Sunil Shinde, Ketan.B.Ghare, & Pratik damodar shitole (April-2025). Use of artificial intelligence in pharmacovigilance -a systematic review . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 10(4), c701-c716. https://ijnrd.org/papers/IJNRD2504307.pdf
Issue
Volume 10 Issue 4, April-2025
Pages : c701-c716
Other Publication Details
Paper Reg. ID: IJNRD_305491
Published Paper Id: IJNRD2504307
Research Area: Life Sciences All
Author Type: Indian Author
Country: Satara, Maharashtra , India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2504307.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2504307
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