Year: 2025
Type: article
Abstract: Pharmacovigilance (PV) is a data-driven process to identify medicine safety issues at the earliest by processing suspected adverse event (AE) reports and extraction of health data. The PV case processing cycle starts with data collection, data entry, initial checking completeness and validity, coding, medical assessment for causality, expectedness, severity, and seriousness, subsequently submitting report, quality checking followed by data storage and maintenance. This requires a workforce and technical expertise and therefore, is expensive and time- consuming. There has been exponential growth in the number of suspected AE reports in the PV database due to smart collection and reporting of individual case safety reports, widening the base by increased awareness and participation by health-care professionals and patients. Theprimary goal of pharmacovigilance, the cornerstone of public health, is to track and evaluate adverse drug reactions in order to guarantee patient safety. Conventional approaches suffer from biases in human error, inefficiency, and scalability problems. A new era in pharmacovigilance is being ushered in by the introduction of artificial intelligence (AI), which holds the promise of vast data analysis, automated procedures, and enhanced safety signal detection
Source: Journal of Integral Sciences
Author: Talluri, Poojitha
Language: English
Subfield: Toxicology
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W7217600073