Real-time health supply chain optimization using digital twin technology

Khan, Sameer and Tabasum, Saira (2025) Real-time health supply chain optimization using digital twin technology. International Journal of Science and Research Archive, 15 (2). pp. 1275-1289. ISSN 2582-8185

Real-time optimization of health supply chains is fundamental to achieving global health security and equity. Digital twin technology—a virtual representation of physical processes—offers a transformative solution for enhancing visibility, forecasting disruptions, and improving decision-making within complex supply chain networks. This paper investigates the role of digital twins in revolutionizing health supply chains, particularly in predictive analytics, risk management, and real-time resource optimization. By integrating real-time data from IoT devices with predictive analytics driven by artificial intelligence, digital twins can simulate various scenarios, predict potential disruptions, and recommend optimal interventions. This paper presents key pilot projects demonstrating the successful implementation of digital twins in vaccine logistics, hospital inventory management, and pharmaceutical manufacturing, highlighting measurable improvements in operational efficiency, cost reduction, and risk mitigation. The findings emphasize the critical role of digital twin technology in building adaptive and resilient health supply chains capable of addressing future global health challenges.