1. David Manner JSM Presentation July 29, 2019
How the 2018 FDA Adaptive Design Draft Guidance can help to increase the use of adaptive designs in industry
David Manner
JSM Presentation
July 29, 2019

2. Outline Brief History 2010 Draft Guidance on Adaptive designs
Usage of Adaptive Designs
2018 Draft Guidance on Adaptive designs
Highlights from Guidance
Key additions
Implications to industry

3. In 2010, FDA issued the Adaptive Design draft guidance
Brief History
In 2010, FDA issued the Adaptive Design draft guidance
Assist sponsors in designing and conducting adaptive designs and facilitate with efficient FDA review
Terminology and concepts provided
Highlighted general concerns with adaptive designs in drug development and advised caution on their use
Well-understood adaptive designs
Less well-understood adaptive designs
Use of trial simulation in evaluating Type 1 error is controversial and not well understood

4. Survey of the Usage of Adaptive Designs
% of Adaptive Designs by Phase of Development
2012: 52%Exploratory Phase; 48% Confirmatory Phase
2016: 57% Exploratory Phase; 43% Confirmatory Phase
Source: Hartford, et al. TIRS 2018

5. Perceived and persistent barriers to adoption (2000-2015)
Education (lack of team knowledge about methodology)
Statistical tools (lack of validated software available)
Change management (team preference/greater comfort with traditional approach)
Pre-planning (lack of time to conduct clinical trial simulations that are necessary for doing AD)
Regulatory acceptance (risk of not obtaining agency approval due to the use of an AD)
Negative experience
Recommendations to Overcoming these Barriers
Emphasize the Regulatory agencies are generally open to discussing adaptive approaches but early engagement recommended
Dr. Alun Bedding DIA ADSWG JSM 2017

6. PDUFA VI (2018 – 2022) Complex Innovative Designs (CID)
Objective: To facilitate the advancement and use of complex adaptive, Bayesian, and other novel clinical trial designs through
Conducting a pilot program
Convening a public workshop
Publishing draft guidance
Adaptive Designs
Master Protocols for Oncology
Developing or update policies and procedures

7. Quotes from FDA
“The adoption of novel clinical trial designs and methods for analyzing data are a key to advancing innovation in the development of drug and biologics for hard to treat medical conditions.” (Scott Gottlieb. MD, former FDA commissioner, August 2018)
“The aim is to develop more efficient strategies to assess the safety and efficacy of medical products earlier in the development process and to adopt innovative techniques that help make clinical trials more cost efficient and flexible, enabling innovators to advance new approaches to care.” (Scott Gottlieb. MD August 2018)
FDA Announcement Aug 2018: Complex Innovative Designs Pilot Meeting Program

8. 2018 FDA Draft Guidance Adaptive Designs for Clinical Trials
FDA’s new guidance focuses much more on potential advantages of AD’s
Statistical Efficiency
Ethical Considerations
Improved understanding of drug effects
Acceptability to stakeholders (sponsors and patients)
Several Motivating Examples, including:
PARADIGM-HF study (Group Sequential Design)
HPV vaccine (Adaptive Dose Selection)
PREVAIL II (Bayesian Adaptive Design)

9. 2018 AD Draft Guidance Possible Limitations of Adaptive Designs
Require certain analytical methods to avoid increasing chance of erroneous conclusions and introducing bias to estimates
Gains in efficiency in one aspect may be offset by loss in another
Opportunity for efficiency gains may be limited by important scientific constraints
Potential challenges in interpretability

10. 2018 AD Draft Guidance 4 Key Principles for Adaptive Designs
Controlling the Chance of Erroneous Conclusions
Estimating Treatment Effects
Trial Planning
Maintaining Trial Conduct and Integrity

11. 2018 AD Draft Guidance Using Non-Comparative vs Comparative Data
Adaptive Designs based upon Non-Comparative Data
E.g. Blinded SSR
Adaptive Designs based upon Comparative Data
Group Sequential Designs (OBF, Pocock)
Adaptations to:
Sample size (Unblinded SSR)
Patient Population
Treatment Arm Selection (special case is platform trial)
Patient Allocation (response adaptive randomization)
Endpoint Selection

12. 2018 AD Draft Guidance Simulations in Adaptive Design Planning
Highlights the importance of trial simulations
Comparison of alternative trial designs
Decisions on number and timing of interim analyses
Estimation of trial operating characteristics
Facilitates team discussions on trial design
Particularly useful for complex adaptive designs
Estimate Type 1 error probability on a grid of plausible values

13. 2018 AD Draft Guidance Simulations in Adaptive Design Planning
Guidance on precision of simulated operating characteristics
100,000 iterations ensures a 95% CI for estimate Type 1 error probability with a width of approximately ± 0.1% (possible to use fewer iterations)
Different random seeds
Precision of Type 1 error probability is higher than for other operating characteristics such as power

14. 2018 AD Draft Guidance Bayesian Adaptive Designs
Highlight Bayesian design features:
Use of predictive modeling incorporating information external to the trial to govern timing and decision rules for interim analyses
Explicitly borrowing external sources
Use of posterior probability distributions to define trial success criteria
Need to use simulations to estimate trial operating characteristics
Special considerations on type 1 error probability estimation when a trial borrows external information via an informative prior

15. 2018 AD Draft Guidance Early-Phase Exploratory Trials
“The flexibilities offered by adaptive designs may be particularly useful in this exploratory period of development by allowing initial evaluation of a broad range of choices“
Examples of learning:
Dose selection
Dosing frequency/regimen
Patient population
Endpoints
Concomitant treatments

16. 2018 AD Draft Guidance Maintaining Trial Integrity
Comparative interim results should be shown to limited number of individuals who are not involved with conducting & managing the trial
Protects against possible perception that a protocol amendment was motivated by seeing interim results
Provides greatest assurance of quality trial conduct
Key Components for maintaining trial integrity
Rigorous planning (deciding who will see interim results upfront)
Careful implementation (understand data flow and adhere to it)
Comprehensive documentation (including pre-specification of adaption rules, meeting minutes)

17. 2018 AD Draft Guidance Regulatory Considerations
To facilitate interactions with FDA, the sponsor should provide details on:
Possible adaptations used in design
Justification that the chance of erroneous conclusions are adequately controlled
The reliability of the treatment effect estimates
How trial integrity will be maintained

18. 2018 AD Draft Guidance Regulatory Considerations
Additional documentation:
Provide details on operating characteristics for proposed design and alternative designs
Simulation Report
Data access plan that details how trial integrity will be maintained
Recent Publication on Simulation Report contents
[Mayer, et al. (2019) Simulation Practices for Adaptive Trial Designs in Drug and Device Development, Statistics in Biopharmaceutical Research.]

19. Implications to Industry
Practical guidance for industry
Simulations
Bayesian Adaptive Designs
Regulatory Considerations
Maintaining Trial Integrity
Facilitate discussions internally
Facilitate discussions with FDA

20. References FDA Guidance Documents:
Adaptive Designs for Clinical Trials of Drugs and Biologics: Guidance for Industry (draft guidance) Sept
Adaptive Designs for Clinical Trials of Drugs and Biologics: Guidance for Industry (draft guidance) Feb 2010.
Master Protocols: Efficient Clinical Trial Design Strategies to Expedite Development of Oncology Drugs and Biologics Oct 2018 (
Bedding, A. (2017). Perception and Use of Adaptive Designs in Industry and Academia: Comparison of the Four DIA Adaptive Design Scientific Working Group Surveys Conducted from 2000 Through 2015 DIA ADSWG. JSM 2017.
Hartford, A. et. al. (2018). Therapeutic Innovation and Regulatory Science ( )
Mayer, et al. (2019) Simulation Practices for Adaptive Trial Designs in Drug and Device Development, Statistics in Biopharmaceutical Research, DOI: /