Artificial Intelligence Integration and Administration into Pharmaceutical Manufacturing Execution Systems: Assessing Potentials and Challenges for Process Optimization

This study investigates the benefits and challenges of integrating Artificial Intelligence (AI) technologies into the Manufacturing Execution System (MES), specifically in the pharmaceutical industry. The main objective of this paper is to use various AI methodologies, such as machine and deep learning, to refine manufacturing processes and assess their effectiveness. Moreover, the study suggests that AI has the potential to improve process efficiency, reduce costs, and enhance decision-making processes. However, successful implementation requires addressing challenges such as data integration, algorithm selection, and workforce upskilling. In essence, this research underscores the imperative for a comprehensive and nuanced approach to AI integration into MES within the pharmaceutical domain. By acknowledging both the opportunities and challenges this integration presents, organizations can lay the groundwork for a future where AI-driven manufacturing optimization becomes synonymous with industry success and innovation. Thus, understanding these complexities is crucial, and this research provides valuable insights for manufacturers and researchers alike.