Artificial Intelligence in Pharmaceutical Sciences: A Mini Review

ABSTRACT:Artificial intelligence (AI) has emerged as a transformative technology in pharmaceutical sciences andpharmacy practice, enabling the transition from conventional trial-and-error approaches to data-driven,predictive, and personalized healthcare solutions. This review critically examines the applications of AIthroughout the pharmaceutical and pharmacy continuum, encompassing drug discovery, formulationdevelopment, pharmacokinetic and pharmacodynamic modeling, clinical decision support, supply chainmanagement, pharmacovigilance, and patient-centered care. Advanced AI methodologies, including machinelearning, deep learning, natural language processing, large language models, and computer vision, facilitatethe analysis of complex biomedical datasets, accelerate target identification, optimize molecular design,predict absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, and supportprecision medicine initiatives. In clinical and community pharmacy settings, AI-driven systems enhancemedication safety, automate dispensing processes, improve inventory management, strengthen adverse drugreaction surveillance, and promote medication adherence through intelligent monitoring technologies and telepharmacy services. Despite these advantages, significant challenges remain, including data quality andinteroperability issues, algorithmic bias, limited model interpretability, concerns regarding privacy andcybersecurity, and evolving regulatory and ethical considerations. These barriers highlight the need for robustgovernance frameworks, transparent and explainable AI models, and rigorous validation strategies.Furthermore, AI is redefining the role of pharmacists by shifting professional responsibilities toward clinicaldecision-making, data analytics, multidisciplinary collaboration, and continuous patient care management.Future developments are expected to focus on explainable AI, federated learning, edge computing, hybridintelligence systems, and the integration of AI competencies into pharmacy education. Overall, the successfulimplementation of AI, coupled with human expertise and ethical oversight, has the potential to enhance theefficiency, safety, and personalization of pharmaceutical development and healthcare delivery, ultimatelyimproving patient outcomes and advancing the future of intelligent pharmacy practice.