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The Role of Artificial Intelligence in Pharmacy Practice and Patient Care: Innovations and Implications

Aftab Alam, Syed Sikandar Shah, Syed Arman Rabbani, Mohamed El‐Tanani

2025BioMedInformatics5 citationsDOIOpen Access PDF

Abstract

Artificial Intelligence (AI) is reshaping pharmacy practice by enhancing decision-making, personalizing therapy, and improving medication safety. AI applications now span drug discovery, clinical decision support, and adherence monitoring. This narrative review explores key innovations, practical applications, and the implications of AI integration in pharmacy practice, with a focus on emerging tools, pharmacist roles, and ethical considerations. The review was conducted using literature from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar. Thematic synthesis included AI-based drug interaction checkers, Clinical Decision Support Systems (CDSS), telepharmacy, pharmacogenomics, and predictive analytics. AI enhances clinical decision-making, reduces medication errors, and supports precision medicine. AI tools support pharmacists and healthcare professionals in optimizing care. However, data privacy, algorithmic bias, and workflow integration continue to pose challenges. AI holds transformative potential in pharmacy, though its integration requires overcoming ethical and workflow-related challenges. Ethical and regulatory vigilance, coupled with pharmacist training and interdisciplinary collaboration, is essential to realize the full potential of AI.

Topics & Concepts

Transformative learningWorkflowPharmacy practicePharmacyHealth careThematic analysisPharmacistClinical pharmacyMedicineMedical educationClinical decision support systemApplications of artificial intelligenceKnowledge managementHealth professionalsPatient careClinical PracticePsychologyNarrativeDecision support systemEngineering ethicsMEDLINENursingEthical issuesArtificial intelligenceReflective practiceHealthcare systemComputer scienceBest practiceHealthcare deliveryArtificial Intelligence in Healthcare and EducationMachine Learning in HealthcareElectronic Health Records Systems
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