INTEGRATING SOCIAL MEDIA IN TO PHARAMCOVIGILANCE SYSTEMS: A REVIEW OF TOOLS, TRENDS, AND REGULATORY PERSPECTIVES

In recent years, social media has emerged as a novel and promising data source for pharmacovigilance (PV), enabling the real-time collection of patient-generated health experiences. Traditional PV systems, although robust, often suffer from underreporting, time lags, and limited representation of real-world perspectives. Social media platforms such as Twitter, Facebook, Reddit, and health forums provide unstructured yet valuable data that can aid in the early detection of adverse drug reactions (ADRs), off-label usage, and medication misuse. This review explores the integration of social media into existing PV frameworks, highlighting its advantages—such as faster signal detection, broader patient coverage, and insights into patient sentiment—as well as its limitations, including data quality concerns, privacy issues, and regulatory challenges. Advanced techniques like natural language processing (NLP), machine learning (ML), and ontology-based methods are increasingly employed to process and interpret the vast and noisy data. Case studies like MedWatcher Social, Web-RADR, and COVID-19 vaccine surveillance underscore the practical utility of social media in pharmacovigilance. However, ethical and legal concerns regarding data privacy and consent remain significant. To fully leverage social media for pharmacovigilance, global harmonization of data standards, robust AI-driven analytics, and transparent regulatory policies are essential. This integration represents a significant step toward more patient-centric, responsive, and data-driven drug safety monitoring in the digital age.