| description abstract | Abstract. The United States (US) national directive has identified the supply chain (SC) resilience of the biopharmaceutical (BP) manufacturing industry as an important key economic and national security performance. Research has indicated that digital twins (DTs), a virtual representation of a physical object or system with bidirectional communication and actions, have been used successfully to enhance SC resilience in other industries such as aerospace, smart city, and automotive manufacturing. In this article, we investigated the opportunity to use and the gap to realize DT in the BP manufacturing industry. The article first documented the current state and challenges of BPSCs, classifying them into global supply risks, traceability needs, transitioning to continuous manufacturing, decentralized production, complex cold chain logistics, and supply-demand uncertainty. Through a comprehensive literature review, we explored various aspects of DT definitions and prior SC applications. As a result, three key DT functionalities, including real-time monitoring, simulations, and optimizations, were identified and then analyzed to determine how they may apply to BPSC challenges. The analysis reveals potential benefits, such as enhanced SC visibility, more accurate demand prediction, risk mitigation, and increased responsiveness to disruptions. However, current DT adoption in the BP sector was found to be minimal. This may be due to both general and sector-specific barriers. Our research identifies three critical, sector-specific gaps that must be addressed for effective implementation: (1) data quality and interoperability challenges stemming from fragmented BP-specific standards; (2) data privacy and security concerns of proprietary manufacturing data and patient information; and (3) tools to help assess the return on investment (ROI) given the high regulatory compliance and validation requirements. This research contributes to understanding how DT can transform BPSC management and provide practical insights for advancing DT adoption. | |
