Overview of AI Agent Applications in Hospital Pharmacy Operations

Abstract

Abstract: The rapid emergence of Large Language Models (LLMs) has catalyzed significant opportunities for digital transformation in healthcare. However, existing chatbot tools remain constrained by their passive nature and inability to execute complex, multi-step tasks. This paper provides a comprehensive overview of the paradigm shift from passive Artificial Intelligence (AI) to AI Agents and ultimately to autonomous AI, a system capable of self-reliance, reasoning, and using tools to solve problems without constant human intervention. In the field of hospital pharmacy, AI Agents are driving breakthroughs through proactive supply chain management, autonomous robotic systems, and, most notably, support for drug information and clinical pharmacy activities. Advanced frameworks such as TxAgent and Multi-Agent Systems (MAS) have demonstrated superior performance in optimizing therapeutic regimens, personalizing dosages, and automating pharmacovigilance workflows compared to standalone models. Despite this potential, implementation in Vietnam faces critical challenges regarding data standardization, technical infrastructure, and regulatory frameworks. The paper concludes that while AI Agents will become indispensable assistants to pharmacists, a strategic investment and structured training approach are essential to fully realize their potential in clinical settings.

Keywords: Artificial Intelligence, AI Agent, Autonomous Agent, Multi-Agent system, hospital pharmacy, clinical pharmacy.