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Biostatistics Advance Access originally published online on October 9, 2006
Biostatistics 2007 8(3):595-608; doi:10.1093/biostatistics/kxl031
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© 2006 The Authors
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Screening designs for drug development

David Rossell

Department of Biostatistics & Applied Mathematics, The University of Texas, M. D. Anderson Cancer Center, Houston, TX 77030, USA and Department of Statistics, Rice University, Houston, TX 77005, USA

Peter Müller* and Gary L. Rosner

Department of Statistics, Rice University, Houston, TX 77005, USA pmueller{at}mdanderson.org

* To whom correspondence should be addressed.

We propose drug screening designs based on a Bayesian decision-theoretic approach. The discussion is motivated by screening designs for phase II studies. The proposed screening designs allow consideration of multiple treatments simultaneously. In each period, new treatments can arise and currently considered treatments can be dropped. Once a treatment is removed from the phase II screening trial, a terminal decision is made about abandoning the treatment or recommending it for a future confirmatory phase III study. The decision about dropping treatments from the active set is a sequential stopping decision. We propose a solution based on decision boundaries in the space of marginal posterior moments for the unknown parameter of interest that relates to each treatment. We present a Monte Carlo simulation algorithm to implement the proposed approach. We provide an implementation of the proposed method as an easy to use R library available for public domain download (http://www.stat.rice.edu/~rusi/ or http://odin.mdacc.tmc.edu/~pm/).

Keywords: backward induction; bayesian optimal design; clinical trial design; forward simulation; utility function

Received April 25, 2005; revised September 1, 2006; accepted for publication October 3, 2006.


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