IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-319-09075-7_10.html
   My bibliography  Save this book chapter

Portfolio Optimization of Therapies and Their Predictive Biomarkers

In: Optimization of Pharmaceutical R&D Programs and Portfolios

Author

Listed:
  • Robert A. Beckman

    (University of California at San Francisco
    Oncology Clinical Research, Daiichi Sankyo Pharmaceutical Development)

  • Cong Chen

    (Biostatistics and Decision Research Sciences, Merck Research Laboratories)

Abstract

The future of oncology drug development depends on the identification of predictive biomarkers that can identify subsets of patients who will benefit from the therapy. When predictive biomarkers work, they increase the value of therapies, and decrease the risk and potentially the cost of therapeutic development. However, predictive biomarkers do not always work, and when they do not, they add cost, time, and complexity to development. This chapter describes methods to adaptively integrate predictive biomarkers into oncology clinical development in a data-driven manner that invests in a predictive biomarker in proportion to its proven ability to predict therapeutic efficacy. This not only increases the value of associated therapeutics but also optimizes the investment in predictive biomarkers by managing the uncertainty in their predictive ability. At the end of the chapter, we discuss a global view of portfolios as a group of putative therapies and putative predictive biomarkers competing for limited resources. In modern drug development, portfolio optimization should ultimately be performed across both of these asset categories as an integrated whole.

Suggested Citation

  • Robert A. Beckman & Cong Chen, 2015. "Portfolio Optimization of Therapies and Their Predictive Biomarkers," Springer Books, in: Zoran Antonijevic (ed.), Optimization of Pharmaceutical R&D Programs and Portfolios, edition 127, chapter 0, pages 155-180, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-09075-7_10
    DOI: 10.1007/978-3-319-09075-7_10
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:sprchp:978-3-319-09075-7_10. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.