Abstract Digital twin (DT) holds promises for enhancing manufacturing and supply chain performances in the biopharmaceutical (BP) manufacturing industry. DT has been used successfully in adjacent industries. Supply chain resilience is one of the key performances identified in the United States (US) national directive, particularly for the BP industry. The objective of this paper is to examine the opportunities of using DT in addressing challenges in the US BP supply chains and to identify gaps in realizing such opportunities. The paper first documents current state and challenges of BP supply chains, 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 explore the definition of the supply chain DT and analyze how a full deployment of a bidirectional supply chain DT and supporting technologies may address these challenges through three key DT functionalities, including real-time monitoring, simulations, and optimizations. The analysis shows potential benefits from these functionalities, such as enhancement in supply chain visibility, more accurate demand prediction, risks mitigation, and increased responsiveness to disruptions. However, current DT adoption in the BP sector is minimal. To that end, three gaps and respective future research that must be addressed for an effective implementation are identified, namely data quality and accessibility, data privacy and security, and tools to help assess the return on investment. This research contributes to understanding how DT can transform BP supply chains and provides practical insights for advancing DT adoption.
Charoenwut et al. (2026) studied this question.