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Adaptive clinical trials: progress and challenges.

Christopher S Coffey1, John A Kairalla

  • 1Department of Biostatistics, School of Public Health, University of Alabama Birmingham, Birmingham, Alabama, USA.

Drugs in R&D
|July 1, 2008
PubMed
Summary
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Adaptive designs offer clinical trial flexibility but face hesitation due to definitional confusion, sample size re-estimation controversies, and logistical hurdles. Clarifying these issues is crucial for wider adoption in drug development.

Area of Science:

  • Clinical Trial Design
  • Biostatistics
  • Drug Development

Background:

  • Adaptive designs allow for trial modifications during interim stages, promising increased efficiency in drug development.
  • Hesitation to adopt adaptive designs stems from definitional ambiguity, controversies in sample size re-estimation, and logistical challenges.
  • Recent advancements have led to confusion regarding the definition and acceptance of various adaptive design methodologies.

Purpose of the Study:

  • To clarify the definition of adaptive designs and differentiate between acceptable and controversial methods.
  • To examine controversies surrounding sample size re-estimation in adaptive trials, distinguishing between methods based on treatment effect versus nuisance parameters.
  • To identify and discuss logistical barriers hindering the implementation of adaptive designs in existing clinical trial frameworks.

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Main Methods:

  • Review and synthesis of existing literature on adaptive trial designs.
  • Categorization of adaptive designs based on their methodologies and statistical underpinnings.
  • Analysis of controversies, particularly focusing on sample size re-estimation techniques like internal pilot designs.

Main Results:

  • Significant confusion exists regarding the definition of adaptive designs, leading to the avoidance of acceptable methods.
  • Controversy primarily centers on sample size re-estimation, with a need to differentiate between methods based on revised treatment effects and those using nuisance parameters.
  • Logistical barriers, rather than statistical limitations, are the primary hindrance to adaptive design implementation.

Conclusions:

  • Clarifying the distinctions between various adaptive designs is essential for their broader acceptance and utilization.
  • Education and dialogue involving statisticians, clinicians, funding bodies, and regulatory agencies are needed to overcome implementation barriers.
  • Addressing definitional ambiguities and controversies will facilitate the realization of adaptive designs' potential for efficient drug development.