Health Canada regulates clinical trials and drug approvals. Adaptive clinical trial designs are increasing and can modify aspects of ongoing trials using accumulating data. Health Canada's main concerns are appropriate scientific questions, error control, and avoiding bias. Examples seen include adaptive randomization, sample size changes, and seamless phase 2/3 designs. Case studies demonstrate increased complexity, new statistical methods, and more simulation use. Health Canada recommends early consultation and education on adaptive designs.

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Adaptive Clinical Trial Designs:
Health Canada’s Regulatory
Perspective
Celia Lourenco, PhD
Bureau of Gastroenterology, Infection
And Viral Diseases

2. Health Canada - HPFB
• Reviews and authorises clinical trial applications for
pharmaceuticals, biologics, radiopharmaceuticals,
medical devices, and natural health products
• Reviews and authorises for sale pharmaceuticals,
biologics, radiopharmaceuticals, medical devices, and
natural health products
• Carries out pharmacovigilance in clinical trials and post-
market
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Main regulatory concerns
• Design should be appropriate to answer the scientific
question of interest
• Sponsor must demonstrate control of Power and Type I
error rate over the entire clinical trial
• Operational bias – appropriate pre-planning and
measures are implemented to avoid operational bias
(e.g., randomization, blinding, secure electronic
systems, independent DSMBs, blinded steering
committees, etc.)

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Adaptive Designs
• On Health Canada’s radar for several years (HC working
group formed in 2008)
• Many seen in clinical trial applications (CTAs)
• Some in new drug submissions (NDSs)

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HC WG definition of
adaptive design
• An adaptive clinical trial design is a study design
planned prospectively that uses accumulating
data to decide how to modify aspects of an
ongoing study and that uses pre-specified,
validated, methodological approaches to
preserve the validity and integrity of the trial

6. Some examples in CTAs
• Adaptive randomization, drop or add arms
– Mainly in phase 2 trials
– Use of modeling and simulation
• Sample size re-estimation: phase 2 or 3
• Seamless design: phase 2/3, two-stage dose
selection
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9. Some examples in NDSs
• Indacaterol: for treatment of COPD - Trial B2335S, a
26-week seamless adaptive design trial that included
an initial 2 week dose-ranging phase
• Gardasil 9: a vaccine indicated for the prevention of
infection caused by the Human Papillomavirus (HPV)
types 6, 11, 16, 18, 31, 33, 45, 52 and 58
– A Randomized, International, Double-Blinded (With In-
House Blinding), Controlled With GARDASIL™, Dose-
Ranging, Tolerability, Immunogenicity, and Efficacy Study of
a Multivalent Human Papillomavirus (HPV) L1 Virus-Like
Particle (VLP) Vaccine Administered to 16- to 26-Year-Old
Women
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B2335s Trial Design

11. Gardasil 9 design
• From FDA’s review on FDA’s website:
– Phase 2b/3, with two parts
– Part A: ~1240 subjects were enrolled, equally randomized to
3 dose formulations of 9vHPV or qHPV
– Part B: one dose formulation of 9vHPV was selected for Part
B based on interim immunogenicity results, with ~13,380
subjects enrolled in Part B and equally randomized to the
selected dose formulation of 9vHPV or qHPV
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12. Conclusion from case-studies
• Adaptive designs present increased complexity
• May be difficult to interpret, and make use of new
statistical tests/procedures
• Increase in use of Bayesian statistics, which involves a
different approach in statistical inference
• Increase use of simulation – time consuming to
validate and can be difficult to interpret what the results
mean
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• Simulation provides the operating characteristics of the
trial design
• That is the description (a picture) of the likelihood
(probabilities) of how the trial will progress down the
different paths (planned possible adaptations) to
eventual completion or termination of the trial
Why and What of Simulation

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• The sponsors should provide that picture
• Usually in well designed and planned trials, yes
• The question is should regulators look behind the picture
and actually check that it was done right?
– That means try to duplicate the simulation results
– Ask to submit codes, and check/replicate
Seeing that Picture

15. Conclusions & recommendations
• Continue to monitor adaptive designs, expect that the
topic will continue to evolve
• Pre-submission meetings are encouraged
• Optimize biostatistics and IT resources to deal with
emerging trends such as use of Bayesian statistics
• Provide support and encourage attendance of courses
and seminars on adaptive design
• Biostatistics consult sought (early) for pivotal Adaptive
Design trials in submissions
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16. THANK YOU!