Abstract

A REVIEW ON IMPACT OF ARTIFICIAL INTELLIGENCE ON PHARMACY PRACTICE

Shital S. Rathod*, Snehal S. Rathod, Vaishnavi D. Rokade, Pragati P. Nade, Miss. Aishwarya Dhole, Miss. Sabafarin H. Shaikh

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Abstract

Artificial intelligence (AI) is transforming pharmacy practice by bringing about major improvements in patient care, accuracy, and efficiency. Pharmacists can now use data-driven, automated methods instead of traditional, manual ones because to artificial intelligence (AI) technology like robots, machine learning, and natural language processing. This paper examines how AI is affecting medication management, drug discovery, patient counseling, and clinical decision-making, among other facets of pharmacy practice. Artificial Intelligence (AI) is revolutionizing pharmacy practice by enhancing precision, efficiency, and patient-centered care. Through advanced technologies such as machine learning, robotics, and natural language processing, AI has transformed traditional pharmacy operations into data-driven, automated systems. This review explores the multifaceted role of AI across various domains— drug discovery, clinical decision support, personalized therapy, medication management, and pharmaceutical manufacturing. AI applications like predictive analytics and automated dispensing have strengthened medication safety by minimizing errors and anticipating drug interactions. Additionally, AI aids in optimizing inventory systems, accelerating drug development, and facilitating individualized treatment regimens through pharmacogenomic data. While the integration of AI offers enormous potential for innovation and improved health outcomes, its adoption also presents challenges, including data privacy, ethical considerations, and regulatory compliance. Overall, AI stands as a transformative force shaping the future of pharmacy practice toward more intelligent, precise, and patient-focused healthcare.

Keywords: Artificial Intelligence; Pharmacy Practice; Machine Learning; Drug Discovery; Clinical Decision Support; Predictive Analytics; Personalized Medicine; Medication Safety; Automation; Pharmacogenomics.