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@article{173029,
        author = {Aniket Sharad Salunke and Sakshi R. Kulkarni and Komal S. Zade and Mrunali K Ahirrao and Madhuri R. Shirsath},
        title = {AUTOMATION & AI IN PHARMACEUTICAL QUALITY ASSURANCE : A REVIEW},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {1744-1748},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173029},
        abstract = {The pharmaceutical industry faces increasing pressure to enhance product quality, ensure compliance with regulatory standards, and streamline production processes. The integration of automation and artificial intelligence (AI) in pharmaceutical quality assurance (QA) has emerged as a transformative solution to address these challenges. This review examines the applications, benefits, and limitations of AI and automation technologies in pharmaceutical QA. Automation systems, such as robotic process automation (RPA), automated testing platforms, and data monitoring tools, are being employed to reduce human error, improve efficiency, and ensure consistent product quality. AI technologies, including machine learning (ML), natural language processing (NLP), and predictive analytics, are enabling more accurate data analysis, real-time decision-making, and predictive maintenance. 
innovations have led to reduced operational costs, faster time to market, and enhanced regulatory compliance. However, challenges such as high implementation costs, integration with legacy systems, and regulatory concerns remain. The future of AI and automation in pharmaceutical QA promises further advancements, including AI-driven quality control and blockchain integration for traceability.},
        keywords = {Pharmaceutical Quality Assurance, Automation, Artificial Intelligence, Machine Learning, Robotic Process Automation, Predictive Analytics, Regulatory Compliance, Quality Control, Data Analytics, AI in Pharmaceuticals, Process Optimization, Pharmaceutical Manufacturing, Automated Testing, AI-driven Decision Making, Industry 4.0.},
        month = {February},
        }