Abstract
Background: The pharmaceutical sector is a critical component of healthcare, driving innovation in drug discovery, development, and delivery. With the increasing integration of artificial intelligence (AI), digital health technologies, and biotechnology, the industry is transforming rapidly. This review examines the key areas of the pharmaceutical industry and highlights the growing impact of AI in enhancing various processes, from drug discovery to clinical trials. To explore the applications of AI in drug discovery, development, manufacturing, clinical trials, personalized medicine, and regulatory compliance. This review also addresses the challenges, such as data privacy and interoperability, that accompany the adoption of AI in the pharmaceutical sector. Methods: A comprehensive review of existing literature and case studies on the application of AI in pharmaceutical research and operations was conducted. Key areas of focus include AI's role in predictive analytics, target identification, manufacturing, supply chain management, clinical trial optimization, and pharmacovigilance. Results: AI significantly enhances drug discovery by improving target identification, predictive modeling, and high-throughput screening. It optimizes manufacturing through real-time quality control and process automation. In clinical trials, AI facilitates patient recruitment and adaptive trial designs, while in personalized medicine, it enables biomarker discovery and treatment optimization. AI also supports regulatory compliance through automated monitoring and risk assessment. Conclusion: AI is transforming the pharmaceutical sector, making processes more efficient, precise, and tailored to individual patients. However, challenges such as data privacy, ethical considerations, and interoperability must be addressed to fully harness AI's potential. Standardization and collaboration will be essential in driving the next phase of innovation in pharmaceutical development and healthcare delivery.
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