Optimization of CAR T-cell therapies supply chains. (4th August 2020)

• Record Type: Journal Article
• Authors: Karakostas, Panagiotis; Panoskaltsis, Nicki; Mantalaris, Athanasios; Georgiadis, Michael C.
• Is Part Of: Computers & chemical engineering. Volume 139(2020)
• Publication Date: 2020-08-04
• Subjects: CAR T-Cell therapies -- Supply chain optimization -- Healthcare supply chains -- Metaheuristic techniques; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2020.106913
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: A novel patient-centric representation of CAR T-cell Therapies Supply Chains. A new MILP model considering both design and operational decisions. A General Variable Neighborhood Search efficient solution algorithm. Applications in computationally complex problem instances. Significant insight into the key factors affecting the design and operation of the supply chain network. Abstract: This work presents a new modelling framework and an efficient solution approach for the optimization of supply chain for CAR T-cell therapies. The proposed supply chain structure is patient-centric, as the administration of CAR T-cell therapies is performed in local treatment facilities located close to patients' sites. Cells are re-engineered in a set of available manufacturing centres, the selection of which is to be decided. A limited number of specialized hospitals operate as coordinators of the overall therapy process. Mobile medical units are considered for delivering therapies from manufacturing centres to local treatment facilities. The underlying problem is formulated as a mixed-integer linear programming model. However, due to the computational complexity, solutions using state-of-the-art solvers such as CPLEX, are obtained only for small and rather unrealistic problem cases. To tackle more realistic-sized problem cases, a General Variable Neighborhood Search (GVNS) algorithm is proposed. The algorithm is tested on 20 new, randomly generated, large problem instances. Solutions were compared with those obtained by CPLEX. Finally, extensive numerical analyses were performed to derive useful insights for the key factors affecting design and operation of CAR T-cell therapies supply chains.