Artificial intelligence in pharmaceutical administration and clinical pharmacy: A comprehensive review of advancements, challenges, and future directions

Abstract

The integration of artificial intelligence (AI) into healthcare is reshaping medical disciplines, with hospital pharmacy undergoing a significant paradigm shift from a labor-intensive model to an intelligence-driven one. This comprehensive review examines the transformative role of AI in pharmaceutical administration and clinical pharmacy, synthesizing recent advancements, identifying key challenges, and projecting future directions. In pharmacy management, AI optimizes procurement through intelligent platforms, enhances dispensing accuracy and safety via automated systems and robotic technologies, and revolutionizes pharmacovigilance by shifting from spontaneous reporting to proactive, data-driven signal detection using machine learning (ML) and natural language processing (NLP). In clinical practice, AI-powered clinical decision support systems (AI-CDSS) augment clinician judgment by enabling real-time data analysis and improving therapeutic outcomes, while human-AI collaborative pre-prescription review systems significantly enhance medication safety. Furthermore, AI facilitates personalized medicine through the integration of pharmacogenomics and leverages large language models (LLMs) to improve patient engagement and medication adherence. Crucially, this review argues that AI is not a replacement for pharmacists but a catalyst for redefining their professional roles, elevating them from dispensers to clinical decision-makers and multidisciplinary collaborators. Despite its vast potential, the widespread adoption of AI faces significant hurdles, including poor data quality and interoperability, algorithmic “black-box” issues that undermine trust, ethical and privacy concerns, lagging regulatory frameworks, and a lack of long-term economic validation. Looking ahead, the future of intelligent pharmacy will be shaped by the integration of LLMs with knowledge graphs, the rise of explainable AI (XAI), the implementation of federated learning for secure data sharing, and the establishment of end-to-end digital ecosystems. Ultimately, AI is poised to become an indispensable collaborator in pharmacy, fostering a more efficient, intelligent, and patient-centered ecosystem.

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