Practical Considerations and Strategies for Executing Adaptive Clinical Trials

Practical Considerations and Strategies for Executing Adaptive Clinical Trials. He, W., Kuznetsova, O. M., Harmer, M., Leahy, C., Anderson, K., Dossin, N., Li, L., Bolognese, J., Tymofyeyev, Y., & Schindler, J. Drug Info J, 46(2):160-174, 2012.
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There is great potential for clinical trials designed with adaptive features to result in more efficient decision making within a drug development program. However, clinical trials with adaptive features are more complex to implement than traditional designs such as fixed-sample or group sequential. Workarounds and/or inefficiencies in adaptive design (AD) trial execution may result in human and material wastes. Further, they may result in the introduction of operational biases that may potentially negate any gains in designing an AD trial and may even render trial results not interpretable. In this article, we present and share our experience and best practices in AD trial implementation in the areas of resource planning, randomization considerations including the importance of randomization schemes on clinical supply, Interactive Voice Randomization System vendor capability assessment and quality control, clinical supply strategy considerations, enrollment management and patient enrollment modeling and simulation, data quality and interim analysis planning, managing blinding and unblinding, and the use of a data monitoring committee.

@article{he12pra,
  title = {Practical {{Considerations}} and {{Strategies}} for {{Executing Adaptive Clinical Trials}}},
  volume = {46},
  abstract = {There is great potential for clinical trials designed with adaptive features to result in more efficient decision making within a drug development program. However, clinical trials with adaptive features are more complex to implement than traditional designs such as fixed-sample or group sequential. Workarounds and/or inefficiencies in adaptive design (AD) trial execution may result in human and material wastes. Further, they may result in the introduction of operational biases that may potentially negate any gains in designing an AD trial and may even render trial results not interpretable. In this article, we present and share our experience and best practices in AD trial implementation in the areas of resource planning, randomization considerations including the importance of randomization schemes on clinical supply, Interactive Voice Randomization System vendor capability assessment and quality control, clinical supply strategy considerations, enrollment management and patient enrollment modeling and simulation, data quality and interim analysis planning, managing blinding and unblinding, and the use of a data monitoring committee.},
  number = {2},
  journal = {Drug Info J},
  doi = {10.1177/0092861512436580},
  author = {He, Weili and Kuznetsova, Olga M. and Harmer, Mark and Leahy, Cathy and Anderson, Keaven and Dossin, Nicole and Li, Lina and Bolognese, James and Tymofyeyev, Yevgen and Schindler, Jerald},
  year = {2012},
  keywords = {rct,adaptive},
  pages = {160-174},
  eprint = {http://dij.sagepub.com/content/46/2/160.full.pdf+html},
  citeulike-article-id = {13265925},
  citeulike-linkout-0 = {http://dx.doi.org/10.1177/0092861512436580},
  citeulike-linkout-1 = {http://dij.sagepub.com/content/46/2/160.abstract},
  posted-at = {2014-07-14 14:10:07},
  priority = {0}
}

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