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@inbook{Wang:2018:10.1016/B978-0-444-64241-7.50351-7,
author = {Wang, X and Kong, Q and Papathanasiou, MM and Shah, N},
booktitle = {Computer Aided Chemical Engineering},
doi = {10.1016/B978-0-444-64241-7.50351-7},
pages = {2137--2142},
title = {Precision healthcare supply chain design through multi-objective stochastic programming},
url = {http://dx.doi.org/10.1016/B978-0-444-64241-7.50351-7},
year = {2018}
}

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TY  - CHAP
AB  - Following the FDA's historic approval of the first cell-based, autologous, cancer therapy in 2017, there has been an increasing growth in the personalized cell therapy market. Both the personalized character as well as the sensitive nature of these therapies, has increased the complexity of their supply chain design and optimisation. In this work, we have addressed key issues in the cyclic supply chain for simultaneous design of the supply chain and the manufacturing plan. A comprehensive optimisation based methodology through both deterministic and stochastic programming is presented and applied to study the Chimeric Antigen Receptor (CAR) T cell therapies. Multiple objectives including maximisation of the overall net present value (NPV) and minimisation of the average response time of all patients are evaluated, while accounting the uncertainties in patients’ demand distribution. Results indicate that the total benefits from the optimized supply chain management are significant compared with the current global market.
AU  - Wang,X
AU  - Kong,Q
AU  - Papathanasiou,MM
AU  - Shah,N
DO  - 10.1016/B978-0-444-64241-7.50351-7
EP  - 2142
PY  - 2018///
SP  - 2137
TI  - Precision healthcare supply chain design through multi-objective stochastic programming
T1  - Computer Aided Chemical Engineering
UR  - http://dx.doi.org/10.1016/B978-0-444-64241-7.50351-7
ER  -

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