IDEAS home Printed from https://ideas.repec.org/p/bep/jhubio/1059.html
   My bibliography  Save this paper

Optimal Sampling Times in Bioequivalence Studies Using a Simulated Annealing Algorithm

Author

Listed:
  • Leena Choi

    (Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics)

  • Brian Caffo

    (Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics)

  • Charles Rohde

    (Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics)

Abstract

In pharmacokinetic (PK) studies, blood samples are taken over time on subjects after the administration of a drug to measure the time-course of the plasma drug concentrations. In bioequivalence studies, the trapezoidal rule on the sampled time points is often used to estimate the area under the plasma concentration-time curve, a quantity of principle interest. This manuscript investigates the choice of sampling time points to estimate the area under the curve. In particular, we explore the relative merits of several objective functions, those functions which are minimized with respect to the sampling times to obtain an optimal study design. We propose an objective function which overcomes some of the deficits of existing choices. We also present a simulated annealing algorithm to perform the minimization. The main benefits of the simulated annealing algorithm are the ease in which it can handle constraints on the sampling schedules and its ability to accommodate a variety of models and objective functions. The manuscript presents optimal sampling times for some key examples of true underlying models.

Suggested Citation

  • Leena Choi & Brian Caffo & Charles Rohde, 2004. "Optimal Sampling Times in Bioequivalence Studies Using a Simulated Annealing Algorithm," Johns Hopkins University Dept. of Biostatistics Working Paper Series 1059, Berkeley Electronic Press.
  • Handle: RePEc:bep:jhubio:1059
    Note: oai:bepress.com:jhubiostat-1059
    as

    Download full text from publisher

    File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1059&context=jhubiostat
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Mohamad Belouni & Karim Benhenni, 2015. "Optimal and Robust Designs for Estimating the Concentration Curve and the AUC," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 453-470, June.

    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:bep:jhubio:1059. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.bepress.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.