IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v50y2018i6p512-524.html
   My bibliography  Save this article

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

Author

Listed:
  • Hui Zhao
  • Kan Wu
  • Edward Huang

Abstract

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.

Suggested Citation

  • Hui Zhao & Kan Wu & Edward Huang, 2018. "Clinical trial supply chain design based on the Pareto-optimal trade-off between time and cost," IISE Transactions, Taylor & Francis Journals, vol. 50(6), pages 512-524, June.
    • Handle: RePEc:taf:uiiexx:v:50:y:2018:i:6:p:512-524
    DOI: 10.1080/24725854.2017.1395978
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24725854.2017.1395978
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/24725854.2017.1395978?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ninh, Anh & Bao, Yunhong & McGibney, Daniel & Nguyen, Tuan, 2024. "Clinical site selection problems with probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 316(2), pages 779-791.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:uiiexx:v:50:y:2018:i:6:p:512-524. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.