Clinical trial supply chain design based on the Pareto-optimal trade-off between time and cost

被引:4
|
作者
Zhao, Hui
Wu, Kan
Huang, Edward
机构
[1] School of Mechanical & Aerospace Engineering, Nanyang Technological University
[2] Department of Systems Engineering and Operations Research, George Mason University, Fairfax, VA
关键词
Health care; network design; clinical trial; site selection; STOCHASTIC-PROGRAMMING APPROACH; SAMPLE AVERAGE APPROXIMATION; DRUG DEVELOPMENT; NETWORK DESIGN; MULTIOBJECTIVE OPTIMIZATION; PRODUCT DEVELOPMENT; GENETIC ALGORITHM; FACILITY LOCATION; RISK-MANAGEMENT; THE-ART;
D O I
10.1080/24725854.2017.1395978
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Long duration and high cost are two key characteristics of clinical trials. Since the clinical trial duration is part of the limited patent life and determines the time to market, its reduction is of critical importance. Although the duration can be reduced through increasing the number of clinical sites in the supply chain, the total enrollment and operational costs are also increased. Hence, Pareto-optimal supply chain configurations are used to improve clinical trial efficiency. In this study, we propose a multi-objective clinical site selection model that considers the trade-off between time and cost of clinical trials. An efficiency curve representing the Pareto-optimal trade-off is provided for decision makers to design the supply chain. To identify all Pareto-optimal supply chain configurations efficiently, we develop an algorithm based on proposed propositions. The optimality cuts are derived to improve the solving efficiency of this problem.
引用
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页码:512 / 524
页数:13
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