Integration of Artificial Intelligence in the Pharmaceutical Sector: From Drug Discovery, Clinical Care, Manufacturing, to Market Delivery—A Review

Artificial Intelligence (AI) is revolutionizing the pharmaceutical industry by enhancing efficiency, precision, and personalization in drug discovery, development, and patient care. This review explores the diverse applications of AI in pharmacy, including drug discovery, formulation development, target identification, hit discovery, and lead optimization. The review explains the clinical trial design and predictive modeling in the crucial implementation of AI. Clinical care for diagnosis, medical image analysis, and early disease detection with sharp clinical decisions are the new directives of AI, as explained. Personalized medicine and pharmacovigilance also include AI to improve outcomes. Community and hospital pharmacies use AI to check treatment plans and drug interactions, as highlighted. Pharma manufacturing uses AI for process optimization, quality management, and supply chain management, resulting in better output. Pharma marketing also uses AI to predict trends and analyze the market. Sales forecasting and compliance monitoring are additional areas in which AI is increasingly being applied. Academic research has also benefited from AI applications. However, regulatory compliance and cultural barriers remain important challenges to AI adoption. Future research directions and emerging opportunities have the potential to further advance the pharmaceutical sector. The challenges associated with AI across these domains are discussed to provide a balanced perspective. This review provides an integrated overview of AI applications across the pharmaceutical sector and the associated challenges.