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@inbook{Sarkis:2022:10.1016/B978-0-323-95879-0.50156-9,
author = {Sarkis, M and Tak, K and Chachuat, B and Shah, N and Papathanasiou, MM},
booktitle = {Computer Aided Chemical Engineering},
doi = {10.1016/B978-0-323-95879-0.50156-9},
pages = {931--936},
title = {Towards Resilience in Next-Generation Vaccines and Therapeutics Supply Chains},
url = {http://dx.doi.org/10.1016/B978-0-323-95879-0.50156-9},
year = {2022}
}

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TY  - CHAP
AB  - Recent clinical outcomes of Advanced Therapy Medicinal Products (ATMPs) highlight promising opportunities in the prevention and cure of life threatening diseases. ATMP manufacturers are asked to tackle engineering product and process-related challenges, whilst scaling up production under demand uncertainty; this highlights the need for tools supporting supply chain planning under uncertainty. This study presents a computer-aided modelling and optimisation framework for viral vector supply chains. A methodology for the characterisation of process-related uncertainties is presented; the impact of input demand and process bottlenecks on optimal supply chain configurations and capacity allocations is assessed. A trade-off between cost and scalability emerges, larger costs incurring at higher input demands, whilst ensuring improved flexibility under demand uncertainty. Furthermore, bottlenecks uncertainty drives the optimisation to alternative strategic decisions, highlighting the need for a systematic integration within the framework.
AU  - Sarkis,M
AU  - Tak,K
AU  - Chachuat,B
AU  - Shah,N
AU  - Papathanasiou,MM
DO  - 10.1016/B978-0-323-95879-0.50156-9
EP  - 936
PY  - 2022///
SP  - 931
TI  - Towards Resilience in Next-Generation Vaccines and Therapeutics Supply Chains
T1  - Computer Aided Chemical Engineering
UR  - http://dx.doi.org/10.1016/B978-0-323-95879-0.50156-9
ER  -

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