MIT SCM Symposium 2024

The logistics supporting life-saving Cell & Gene Therapy treatments, such as autologous CAR-T, face significant challenges due to strict constraints like time sensitivity, temperature control, and regulatory compliance. These constraints make the supply chain vulnerable to disruptions that could result in the loss or damage of these delicate, high-value therapies during global shipments handled by white-glove third-party couriers. To address this issue, a study was conducted to analyze historical shipment data from a qualitative and quantitative perspective. The goal was to create a model that could predict possible disruptions by calculating "validation points" throughout the shipment process and updating them continuously for each new input. As a result, the sponsors' planning team is informed in advance of any potential disruptions, allowing them to proactively reach out to their couriers for immediate action. Although still in its early stages, the model is providing more visibility into current processes and laying the foundation for a scalable solution to be implemented in the sponsor operating system. Additionally, this study has allowed the sponsor to review their current process with their couriers and identify areas for improvement in terms of process, data gathering, and data quality. A proposal for a roadmap is also included, outlining possible enhancements that could leverage Machine Learning and AI techniques.