Assessing the Effectiveness of AI-Powered Drug Recall Systems

DOI: https://doi.org/10.63345/ijrmp.v12.i2.2

Arshdeep Kaur

Independent Researcher

Delhi, India

Abstract

In recent years, the pharmaceutical industry has experienced rapid technological advancements, particularly in the integration of artificial intelligence (AI) into critical operations such as drug recall management. This study evaluates the effectiveness of AI-powered drug recall systems by examining their capacity to enhance recall speed, accuracy, and overall regulatory compliance. By synthesizing a literature review up to 2022, the manuscript outlines historical challenges and contemporary solutions in drug recall management, provides a detailed methodology for assessing system performance, and presents results from case studies and simulation models. The findings reveal that AI-powered systems improve recall precision and operational efficiency, though challenges remain regarding data integration and ethical oversight. The paper concludes with recommendations for further research and industry best practices, as well as an exploration of the scope and limitations inherent in current AI solutions for drug recalls.

Keywords

AI-powered drug recall systems; pharmaceutical safety; recall efficiency; regulatory compliance; machine learning; simulation; operational efficiency

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