Literature DB >> 30235997

DIA's Adaptive Design Scientific Working Group (ADSWG): Best Practices Case Studies for "Less Well-understood" Adaptive Designs.

Eva Miller1, Paul Gallo2, Weili He3, Lisa A Kammerman4, Kenneth Koury3, Jeff Maca5, Qi Jiang6, Marc K Walton7, Cunshan Wang8, Katherine Woo7, Cynthia Fuller9, Yannis Jemiai10.   

Abstract

Adaptive design (AD) clinical trials use accumulating subject data to modify the parameters of the design of an ongoing study, without compromising the validity and integrity of the study. The 2010 US Food and Drug Administration (FDA) Draft Guidance on Adaptive Design Clinical Trials described a subset of 7 primary design types as "less well-understood." FDA defined these designs as those with limited regulatory experience. To better understand the properties of these less well-understood ADs and to promote their use when applicable, the Best Practices Subteam for DIA's Adaptive Design Scientific Working Group conducted an extensive nonsystematic search and reviewed trials from multiple sponsors who had employed these designs. Here, we review 10 specific case studies for which less well-understood ADs were employed and share feedback about their challenges and successes, as well as details about the regulatory interactions from these trials. We learned that these designs and associated statistical methodologies can make difficult research situations more amenable for study and, therefore, are needed in our toolbox. While they can be used to study many diseases, they are particularly valuable for rare diseases, small populations, studies involving terminal illnesses, and vaccine trials, in which it is important to find efficient ways to bring effective treatments to market more rapidly. It is imperative, however, that these methodologies be utilized appropriately, which requires careful planning and precise operational execution.

Entities:  

Keywords:  2010 FDA Adaptive Design guidance; adaptive dose selection; adaptive trials; data monitoring committee; phase IIB/III trial designs; sample size re-estimation

Year:  2016        PMID: 30235997     DOI: 10.1177/2168479016665434

Source DB:  PubMed          Journal:  Ther Innov Regul Sci        ISSN: 2168-4790            Impact factor:   1.778


  3 in total

1.  The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design.

Authors:  Munyaradzi Dimairo; Philip Pallmann; James Wason; Susan Todd; Thomas Jaki; Steven A Julious; Adrian P Mander; Christopher J Weir; Franz Koenig; Marc K Walton; Jon P Nicholl; Elizabeth Coates; Katie Biggs; Toshimitsu Hamasaki; Michael A Proschan; John A Scott; Yuki Ando; Daniel Hind; Douglas G Altman
Journal:  BMJ       Date:  2020-06-17

Review 2.  Adaptive Designs: Lessons for Inflammatory Bowel Disease Trials.

Authors:  Ferdinando D'Amico; Silvio Danese; Laurent Peyrin-Biroulet
Journal:  J Clin Med       Date:  2020-07-23       Impact factor: 4.241

3.  The adaptive designs CONSORT extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design.

Authors:  Munyaradzi Dimairo; Philip Pallmann; James Wason; Susan Todd; Thomas Jaki; Steven A Julious; Adrian P Mander; Christopher J Weir; Franz Koenig; Marc K Walton; Jon P Nicholl; Elizabeth Coates; Katie Biggs; Toshimitsu Hamasaki; Michael A Proschan; John A Scott; Yuki Ando; Daniel Hind; Douglas G Altman
Journal:  Trials       Date:  2020-06-17       Impact factor: 2.279

  3 in total

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