The pharmaceutical sector is part of a complex and heavily regulated global supply chain, in which the provision of essential medicines and therapeutic products on a timely and consistent basis is crucial for public health and clinical results. Traditional pharmaceutical supply chain models have nonetheless been demonstrated to have systemic deficiencies, particularly in the context of escalation events such as the coronavirus disease 2019 (COVID-19) pandemic, geopolitical turmoil, limited access to raw materials, cybersecurity attacks, and climate-induced incidents. These challenges have expanded the importance of a new kind of digital supply chain, one that is more dynamic, data-driven, and less static – one that can anticipate disruption and act proactively. The role of this paper, therefore, is to suggest an integrated strategy development framework for a future-ready pharmaceutical supply chain, one that is predictive, resilient, sustainable, secure, and digitally intelligent. This study begins with a review of the existing literature, which highlights several significant trends in the pharmaceutical supply chain over the past decade, including digital twin modeling, blockchain traceability, machine learning-based demand sensing, and decentralized manufacturing. The survey includes cases of multinational pharmaceutical companies and data from regulatory agencies, such as the US FDA and the EMA, to identify existing gaps and potential solutions. Adopting a mixed-methods approach, the study's findings, based on qualitative analysis (expert interviews and thematic synthesis), are complemented by quantitative analysis of metrics (frequency of supply disruptions, variability in lead times, and production post-recovery rates) to unveil strategic dimensions for modernization.
Gupta et al. (Fri,) studied this question.