BLOODSURE

The Blood Supply Chain (BSC) faces significant challenges due to the perishable nature of blood components, with limited shelf life and high variability in supply and demand. These challenges are further exacerbated by disruptions such as natural disasters, human-made crises, and health emergencies. Ensuring a sustainable and resilient BSC is critical for saving lives, particularly during such crises. Despite these challenges, existing research often oversimplifies practical complexities of the BSC, while holistic, real-time, scalable, and practically grounded decision-support solutions remain scarce. This project proposes a collaborative initiative combining optimisation models and AI-based algorithms, leveraging real-time data to address BSC challenges across European and international partner organisations. The interdisciplinary team, comprising academic experts, technology firms, and stakeholders from various BSC levels (e.g., Red Cross, blood banks, hospitals), will identify critical issues and develop tailored solutions to enhance sustainability and resilience. The project aims to bridge the gap between academic insights and real-world applications by employing optimisation techniques and AI-based algorithms to manage complexity, risk, and uncertainty in BSC operations. Stakeholders will be engaged in reciprocal knowledge transfer to define and prioritise BSC challenges and apply effective optimisation and AI-based approaches, including real-time uncertainty management through online optimisation, descriptive and predictive analytics for forecasting donations and demand, prescriptive analytics for decision support, and AI-driven scenario generation. A digital twin system will be developed as a proof of concept in collaboration with technology firms, demonstrating how these approaches can enhance BSC sustainability, efficiency, and resilience in both day-to-day operations and high-pressure scenarios, such as resource shortages or disasters.