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How to get the regulatory green light for your adaptive design?


As a group, Cytel had over 40 successful regulatory interactions last year, many of which supported approvals for innovative trial design approaches.  In this blog we look at some of the key success factors for regulatory interactions regarding adaptive designs.

The FDA notes in its Guidance for Industry Adaptive Design Clinical Trials for Drugs and Biologics that at later stages of clinical development it has a more extensive role assessing study design than at early stages, and its remit includes ‘ensuring that studies performed at this stage contain plans for assessment of safety and efficacy that will result in data of sufficient quality and quantity to inform a regulatory decision’ . 

For adaptive designs, the FDA will be looking at a number of critical aspects including:

  • The sponsor should be able to justify the adaptation – i.e. present a convincing reason for choosing the adaptive design versus a conventional approach
  •  In a confirmatory setting control of the Type I error is paramount and this should be robustly demonstrated. For ‘well-understood designs’, Type I error control is mpre straightforward and frequently can be easily demonstrated analytically. For 'less well understood designs' it can be a more complex matter to demonstrate Type 1 error control. 
  • How will operational bias be avoided? Mitigations such as adequate firewalls, the robust definition of adaptations in advance and the procedure for interim monitoring are all critical.  

Read more about less-well understood designs here

Below we outline 4 key Success Factors:

  • Strong Preparation of the original documentation

This is really building the foundations for success. Providing a briefing document along with the Statistical Analysis Plan to the agency  is crucially important together with a robust justification of why the adaptive approach is necessary .  The statistical methodology needs to be described in detail along with the mechanism for control of the type 1 error. Simulation results under various scenarios should also be provided together with any DMC Charter and evidence that robust teams, processes, technology are in place to minimize any operational bias. This documentation provides a solid foundation for subsequent regulatory discussion.  

  • Planning responses

The FDA responses will typically arrive the day (or even the evening) before a Type B meeting so preparation is key. It is important to be prepared and flexible enough to respond in writing to maximize the value of the meeting.  Indeed, even if comments initially appear negative towards the sponsor proposals it is critical to be able to defend the position, or offer alternative solutions which can be addressed during the meeting.  Remember that this is an iterative process of  discussion between the sponsor and the agency.

  • Teamwork with non-statistical colleagues

The statistician will be part of a wider multidisciplinary team and therefore there is a wider accountability to overall clinical strategy beyond any specific technical issues being resolved.

  • Communication

Well planned comminunication is key.  Dialogue should be initiated with the health authority as early as possible before the planned start of the study.  Within the regulatory meeting itself, the statistician needs to be adept at communicating their position clearly and concisely in a pressured environment. Outside of this immediate environment, it’s vitally important to be able to effectively manage communication with a range of stakeholders.


Cytel experts have designed over 80 adaptive clinical trials in this last 3 years, over 40 of which were for confirmatory studies.  To find out more about how we help our clients click below:

How we help

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Related Publications by Cytel authors below:


He, W., Gallo, P., Miller, E., Jemiai, Y., Maca, J., Koury, K., Fan, X.F., Jiang, Q., Wang, C. and Lin, M. (2017) ‘Addressing challenges and opportunities of “Less Well-Understood” Adaptive designs’, Therapeutic Innovation & Regulatory Science, 51(1), pp. 60–68. doi: 10.1177/2168479016663265.

Bhatt, D.L. and Mehta, C. (2016) ‘Adaptive designs for clinical trials’, New England Journal of Medicine, 375(1), pp. 65–74. doi: 10.1056/nejmra1510061.


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