Assessment of intermediate storage and distribution nodes in personalised medicine. (January 2022)

• Record Type: Journal Article
• Authors: Bernardi, Andrea; Sarkis, Miriam; Triantafyllou, Niki; Lakelin, Matthew; Shah, Nilay; Papathanasiou, Maria M
• Is Part Of: Computers & chemical engineering. Volume 157(2022)
• Publication Date: 2022-01
• Subjects: Personalised medicine -- Supply chain -- Optimisation; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2021.107582
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Mixed Integer Linear Programming formulation to describe current supply chain networks in personalised medicine. Assessment of storage as means to increase network flexibility. Assessment of therapy manufacturing time on cost and responsiveness of the network. Abstract: Chimeric Antigen Receptor (CAR) T cell therapies are a type of patient-specific cell immunotherapy demonstrating promising results in the treatment of aggressive blood cancer types. CAR T cells follow a 1:1 business model, translating into manufacturing lines and distribution nodes being exclusive to the production of a single therapy, hindering volumetric scale up. In this work, we address manufacturing capacity bottlenecks via a Mixed Integer Linear Programming (MILP) model. The proposed formulation focuses on the design of candidate supply chain network configurations under different demand scenarios. We investigate the effect of an intermediate storage upstream of the network to: (a) debottleneck manufacturing lines and (b) increase facility utilisation. In this setting, we assess cost-effectiveness and flexibility of the supply chain and we evaluate network performance with respect to: (a) average production cost and (b) average response treatment time. The trade-off between cost-efficiency and responsiveness is examined and discussed.