Prescribing the Future: The Role of Artificial Intelligence in Pharmacy

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Detalles Bibliográficos
Publicado en:	Information vol. 16, no. 2 (2025), p. 131
Autor principal:	Allam, Hesham
Publicado:	MDPI AG
Materias:	Medical records Medical research Trend analysis Trends Patient compliance Chronic illnesses Drug development Pharmaceutical industry Drug stores Automation Research & development > R&D Pharmacists Data collection Pharmaceuticals Efficiency Clinical outcomes Literature reviews Disease management Machine learning Patient safety Artificial intelligence Health care Cost reduction Clinical trials Clinical decision making Algorithms Graphical representations Natural language processing Cost control Patient education
Acceso en línea:	Citation/Abstract Full Text + Graphics Full Text - PDF
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Descripción
Resumen:	Integrating artificial intelligence (AI) into pharmacy operations and drug discovery represents a groundbreaking milestone in healthcare, offering unparalleled opportunities to revolutionize medication management, accelerate drug development, and deliver truly personalized patient care. This review examines the pivotal impact of AI in critical domains, including drug discovery and development, drug repurposing, clinical trials, and pharmaceutical productivity enhancement. By significantly reducing human workload, improving precision, and shortening timelines, AI empowers the pharmaceutical industry to achieve ambitious objectives efficiently. This study delves into tools and methodologies enabling AI implementation, addressing ongoing challenges such as data privacy, algorithmic transparency, and ethical considerations while proposing actionable strategies to overcome these barriers. Furthermore, it offers insights into the future of AI in pharmacy, highlighting its potential to foster innovation, enhance efficiency, and improve patient outcomes. This research is grounded in a rigorous methodology, employing advanced data collection techniques. A comprehensive literature review was conducted using platforms such as PubMed, Semantic Scholar, and multidisciplinary databases, with AI-driven algorithms refining the retrieval of relevant and up-to-date studies. Systematic data scoping incorporated diverse perspectives from medical, pharmaceutical, and computer science domains, leveraging natural language processing for trend analysis and thematic content coding to identify patterns, challenges, and emerging applications. Modern visualization tools synthesized the findings into explicit graphical representations, offering a comprehensive view of the key role of AI in shaping the future of pharmacy and healthcare.
ISSN:	2078-2489
DOI:	10.3390/info16020131
Fuente:	Advanced Technologies & Aerospace Database