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Practical considerations for optimal designs in clinical dose finding studies

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  • Bretz, Frank
  • Dette, Holger
  • Pinheiro, José

Abstract

Determining an adequate dose level for a drug and, more broadly, characterizing its dose response relationship, are key objectives in the clinical development of any medicinal drug. If the dose is set too high, safety and tolerability problems are likely to result, while selecting too low a dose makes it difficult to establish adequate efficacy in the confirmatory phase, possibly leading to a failed program. Hence, dose finding studies are of critical importance in drug development and need to be planned carefully. In this paper we focus on practical considerations for establishing efficient study designs to estimate target doses of interest. We consider optimal designs for both the estimation of the minimum effective dose (MED) and the dose achieving 100p% of the maximum treatment effect (EDp). These designs are compared with D-optimal designs for a given dose response model. Extensions to robust designs accounting for model uncertainty are also discussed. A case study is used to motivate and illustrate the methods from this paper.

Suggested Citation

  • Bretz, Frank & Dette, Holger & Pinheiro, José, 2008. "Practical considerations for optimal designs in clinical dose finding studies," Technical Reports 2008,22, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200822
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    References listed on IDEAS

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    1. F. Bretz & J. C. Pinheiro & M. Branson, 2005. "Combining Multiple Comparisons and Modeling Techniques in Dose-Response Studies," Biometrics, The International Biometric Society, vol. 61(3), pages 738-748, September.
    2. K. Strassburger & F. Bretz & H. Finner, 2007. "Ordered Multiple Comparisons with the Best and Their Applications to Dose–Response Studies," Biometrics, The International Biometric Society, vol. 63(4), pages 1143-1151, December.
    3. Dette, Holger & Pepelyshev, Andrey & Wong, Weng Kee, 2008. "Optimal designs for dose finding experiments in toxicity studies," Technical Reports 2008,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Dette, Holger & Bretz, Frank & Pepelyshev, Andrey & Pinheiro, José, 2008. "Optimal Designs for Dose-Finding Studies," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1225-1237.
    5. Miller, Frank & Dette, Holger & Guilbaud, Olivier, 2007. "Optimal designs for estimating the interesting part of a dose-effect curve," Technical Reports 2007,21, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    6. Stefanie Biedermann & Holger Dette & Philipp Hoffmann, 2009. "Constrained optimal discrimination designs for Fourier regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 143-157, March.
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    Cited by:

    1. Jiajing Xu & Guosheng Yin & David Ohlssen & Frank Bretz, 2016. "Bayesian two-stage dose finding for cytostatic agents via model adaptation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(3), pages 465-482, April.
    2. Holger Dette & Laura Hoyden & Sonja Kuhnt & Kirsten Schorning, 2017. "Optimal designs for thermal spraying," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 53-72, January.

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