Literature DB >> 20213708

Practical considerations for optimal designs in clinical dose finding studies.

Frank Bretz1, Holger Dette, Jose C Pinheiro.   

Abstract

A key objective in the clinical development of a medicinal drug is the determination of an adequate dose level and, more broadly, the characterization of its dose response relationship. 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 relevant target doses. We consider optimal designs for estimating both the minimum effective dose and the dose achieving a certain percentage of the maximum treatment effect. 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.

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Year:  2010        PMID: 20213708      PMCID: PMC3852432          DOI: 10.1002/sim.3802

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  11 in total

1.  Multiple-objective designs in a dose-response experiment.

Authors:  W Zhu; W K Wong
Journal:  J Biopharm Stat       Date:  2000-02       Impact factor: 1.051

2.  Combining multiple comparisons and modeling techniques in dose-response studies.

Authors:  F Bretz; J C Pinheiro; M Branson
Journal:  Biometrics       Date:  2005-09       Impact factor: 2.571

3.  Design and analysis of dose-finding studies combining multiple comparisons and modeling procedures.

Authors:  José Pinheiro; Björn Bornkamp; Frank Bretz
Journal:  J Biopharm Stat       Date:  2006       Impact factor: 1.051

4.  Adaptive designs for dose-finding studies based on sigmoid Emax model.

Authors:  Vladimir Dragalin; Francis Hsuan; S Krishna Padmanabhan
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

5.  Optimal designs for estimating the interesting part of a dose-effect curve.

Authors:  Frank Miller; Olivier Guilbaud; Holger Dette
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

6.  Innovative approaches for designing and analyzing adaptive dose-ranging trials.

Authors:  Björn Bornkamp; Frank Bretz; Alex Dmitrienko; Greg Enas; Brenda Gaydos; Chyi-Hung Hsu; Franz König; Michael Krams; Qing Liu; Beat Neuenschwander; Tom Parke; José Pinheiro; Amit Roy; Rick Sax; Frank Shen
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

7.  Ordered multiple comparisons with the best and their applications to dose-response studies.

Authors:  K Strassburger; F Bretz; H Finner
Journal:  Biometrics       Date:  2007-05-08       Impact factor: 2.571

Review 8.  Dose finding - a challenge in statistics.

Authors:  Frank Bretz; Jason Hsu; José Pinheiro; Yi Liu
Journal:  Biom J       Date:  2008-08       Impact factor: 2.207

9.  Two-stage design for dose-finding that accounts for both efficacy and safety.

Authors:  Vladimir Dragalin; Valerii V Fedorov; Yuehui Wu
Journal:  Stat Med       Date:  2008-11-10       Impact factor: 2.373

10.  Multiple test procedures for dose finding.

Authors:  A C Tamhane; Y Hochberg; C W Dunnett
Journal:  Biometrics       Date:  1996-03       Impact factor: 2.571

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  12 in total

1.  An example of optimal phase II design for exposure response modelling.

Authors:  Alan Maloney; Marloes Schaddelee; Jan Freijer; Walter Krauwinkel; Marcel van Gelderen; Philippe Jacqmin; Ulrika S H Simonsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-09-25       Impact factor: 2.745

2.  Statistical Methods for Selecting Maximum Effective Dose and Evaluating Treatment Effect When Dose - Response is Monotonic.

Authors:  Maiying Kong; Shesh N Rai; Roberto Bolli
Journal:  Stat Biopharm Res       Date:  2014-01-02       Impact factor: 1.452

3.  Optimizing Dose-Finding Studies for Drug Combinations Based on Exposure-Response Models.

Authors:  Theodoros Papathanasiou; Anders Strathe; Rune Viig Overgaard; Trine Meldgaard Lund; Andrew C Hooker
Journal:  AAPS J       Date:  2019-07-29       Impact factor: 4.009

4.  Implementing Optimal Designs for Dose-Response Studies Through Adaptive Randomization for a Small Population Group.

Authors:  Yevgen Ryeznik; Oleksandr Sverdlov; Andrew C Hooker
Journal:  AAPS J       Date:  2018-07-19       Impact factor: 4.009

5.  Web-based tools for finding optimal designs in biomedical studies.

Authors:  Weng Kee Wong
Journal:  Comput Methods Programs Biomed       Date:  2013-06-24       Impact factor: 5.428

6.  An Algorithm and R Program for Fitting and Simulation of Pharmacokinetic and Pharmacodynamic Data.

Authors:  Jijie Li; Kewei Yan; Lisha Hou; Xudong Du; Ping Zhu; Li Zheng; Cairong Zhu
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-06       Impact factor: 2.441

7.  Optimal designs based on the maximum quasi-likelihood estimator.

Authors:  Gang Shen; Seung Won Hyun; Weng Kee Wong
Journal:  J Stat Plan Inference       Date:  2016-07-15       Impact factor: 1.111

8.  Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels.

Authors:  Seung Won Hyun; Weng Kee Wong
Journal:  Int J Biostat       Date:  2015-11       Impact factor: 0.968

9.  Optimal designs for frequentist model averaging.

Authors:  K Alhorn; K Schorning; H Dette
Journal:  Biometrika       Date:  2019-07-13       Impact factor: 3.028

10.  Bayesian designs of phase II oncology trials to select maximum effective dose assuming monotonic dose-response relationship.

Authors:  Beibei Guo; Yisheng Li
Journal:  BMC Med Res Methodol       Date:  2014-07-29       Impact factor: 4.615

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