EURO 2024 Copenhagen
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2292. Decision-support tool for resilient biopharmaceutical supply chains

Invited abstract in session TD-53: Resilient Networks, stream Sustainable and Resilient Systems.

Tuesday, 14:30-16:00
Room: 8007 (building: 202)

Authors (first author is the speaker)

1. Miriam Sarkis
Imperial College London
2. Nilay Shah
Imperial College London
3. Maria Papathanasiou
Imperial College London

Abstract

Supply chain resilience is a growing priority in the biopharmaceutical sector. In recent years, the industry has seen the market boom of next generation therapies against life-threatening diseases and the urgent demand for vaccines during the pandemic. Manufacturers catering for these markets reported shortages and delays due to unforeseen demand trends combined with uncertainty in manufacturing capabilities for platforms still under development. We present a decision-support tool that can help assess supply chain resilience a priori for networks that require rapid scale-up to commercialisation and operate under supply-demand uncertainty. Firstly, the propagation of underlying manufacturing uncertainty to scale dependent throughput-related and cost-related KPIs of manufacturing at the investment level is assessed via uncertainty analysis and global sensitivity analysis. Secondly, a stochastic mixed-integer linear problem is formulated for the optimisation of investment planning under process and demand uncertainty. Finally, we introduce a scenario-based supply-demand chance constraint, which quantifies manufacturing supply robustness in meeting target demands. Solution feasibility is tested via Monte Carlo based simulation. Candidate investment plans for single-product and multi-product systems are assessed and cost-resilience Pareto frontiers are constructed via the ɛ-constraint method to support decision-makers allocate resources to reliable manufacturing systems.

Keywords

Status: accepted

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