Digital twin in pharma manufacturing enhancing QMS with virtual simulations - V.VIDYA; Dr. KELLA ALEKHYA S; Dr. MANIMARAN (The Bioscan, 2025)
Digital twin technology is swiftly becoming a groundbreaking advancement in pharmaceutical manufacturing, propelling the sector toward Pharma 4.0. A digital twin serves as a dynamic, digital replica of physical systems, facilitating continuous surveillance, modelling, and optimization of intricate processes. This technology tackles essential challenges in the medicinal products sector, including the preservation of data integrity, the assurance of product quality, the enhancement of process oversight, and the fulfilment of rigorous regulatory standards. Utilizing IoT, the use of AI, and big data statistical analysis, digital twins improve decision-making, facilitate predictive maintenance, and reduce variability in production.Digital twins provide many advantages, as shown in several case studies from different industries. In the midst of the COVID-19 pandemic, Pfizer used digital twin models to speed up vaccine production, while Novartis and GSK used facility-wide digital replicas to enhance quality assurance, decrease failures, and increase batch uniformity. These achievements prove that digital twins may improve efficiency, follow regulations, and ultimately benefit patients. There are obstacles to adoption, notwithstanding its advantages. Problems with data harmonization, cybersecurity, and the intricacy of complying with rules like FDA 21 CFR Part 11 persist as major obstacles. To get around this, pharmaceutical firms need to beef up their cybersecurity, establish consistent data governance practices, and establish a scalable IT infrastructure. If digital transformation is to be a success, it is equally critical to encourage a culture of constant improvement and cooperation across departments.In the future, digital twins will be much more powerful when combined with blockchain technology to provide supply chain visibility, internet of things (IoT) to track metrics in real-time, and deep learning to boost quality continuously. The establishment of uniform standards and best practices will need close cooperation between pharmaceutical companies, technology suppliers, and regulatory bodies. In the end, digital twin technology might completely change the way pharmaceuticals are made. It could lead to better healthcare solutions that are safer, more effective, and focused on the patient. Plus, it could assure conformance and operational excellence.