This dissertation explores the effectiveness of automated Medical Dictionary for Regulatory Activities (MedDRA) coding systems in enhancing the efficiency and accuracy of pharmacovigilance case processing in India. Employing a quantitative approach, the study collected responses from 95 pharmacovigilance professionals across various pharmaceutical organizations in India through a structured survey. The primary focus was on comparing the accuracy of automated versus manual MedDRA coding processes, evaluating the time efficiency of automated systems, and assessing user satisfaction. The results demonstrated that automated systems significantly improved the speed of coding adverse events. Professionals reported a noticeable reduction in the time required to process cases with automated systems compared to manual methods. Similarly, there was a marked improvement in the accuracy of coding with fewer errors and discrepancies noted in automated coding versus manual processes. User satisfaction with automated systems was also high, with participants appreciating the ease of use and the consistent results provided by these systems. The study concludes that integrating automated MedDRA coding systems could enhance pharmacovigilance practices in India by streamlining operations, reducing the likelihood of errors, and improving the overall quality of data. These improvements suggest that automated systems are beneficial for pharmacovigilance activities, supporting their wider adoption within the industry to bolster drug safety monitoring and regulatory compliance.