Applications of Artificial Intelligence in Pharmacovigilance: Emerging Trends & Future Perspectives

Pharmacological vigilance is essential for maintaining public health because it monitors, evaluates, and stops adverse drug reactions at every stage of a medication's life cycle. Traditional approaches to drug safety monitoring are no longer sufficient due to the increasing growth of healthcare data and the complexity of treatments. With its sophisticated features including data analysis, automated signal recognition, case management, and real-time monitoring, artificial intelligence (AI) is becoming a potent tool to handle these issues. Methods like natural language processing, machine learning, and predictive analytics facilitate quicker safety issue detection, enhance risk-benefit analyses, and facilitate more effective regulatory decisions. By facilitating continuous monitoring and tailored risk assessment using wearable technology, social media insights, and electronic health records, AI also improves patient-centric care. Notwithstanding its advantages, adopting AI is fraught with difficulties, such as ethical issues, algorithm openness, data protection, and regulatory compliance. Effective collaborations between regulators, physicians, IT businesses, and pharmaceutical firms are necessary to meet these problems. Pharmacovigilance is anticipated to improve further with the use of emerging technologies like blockchain, explainable AI, generative AI, and the application of real-world evidence. AI has the ability to revolutionize drug safety systems into a proactive, open, and internationally coordinated network that safeguards patients and builds public confidence if used properly.