Quality Control (QC) and Quality Assurance (QA) are key elements in the pharmaceutical sector. They help to ensure the safety, efficacy and consistency of medicines. This article discusses the purpose of QC and QA for pharmaceutical manufacturing in the modern era and outlines their development, principles and problems relating to the application of technology and universal quality standards. The article reaffirms the need for continuous and seamless improvement in the maintenance of quality system improvements that are responsible for global health standards and that can be applied to licensed drugs in a wide range of settings, ensuring the effectiveness of medicines delivered to patients in a sustainable manner. QC and QA are important components in pharmaceutical production. Their combined function is to ensure that all products are safe, efficient and reliable. As the industry evolves and moves toward digitalization, automation and data-centric systems, QC and QA evolve from reactive functions to predictive and preventive tools. Continuous improvements, regulatory compliance and the adoption of technology will shape the future of pharmaceutical quality. This paper also analyzes the beneficial use of Artificial Intelligence (AI) within the pharmaceutical sector throughout all phases, from drug discovery to drug development, as well as in various departments. Besides necessitating less human labor, it also improves the efficacy of clinical research and pharmaceutical output while diminishing the likelihood of mistake. The report examines the existing challenges in the implementation of AI within the pharmaceutical sector. Furthermore, it evaluates existing challenges and proposes remedies.
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Keywords
Artificial intelligence
Pharmaceutical manufacturing
Predictive quality analytics
Quality assurance
Quality by design
Quality control
Regulatory compliance
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