1. Adaptive Multi-Combination Platform Trials in Oncology; Considerations for Study Designs
Jennifer Gauvin, Group Head and Director
Stuart Bailey, Global Head and Vice President
JSM 2018 Vancouver
August 1, 2018

2. Disclosure
The views expressed in these slides are those of the authors and not necessarily of Novartis.
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3. Agenda Platform study Motivation Example Benefits
Design considerations
Next steps
Conclusions
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4. What is a platform study?
Woodcock and LaVange, 2017
An umbrella trial
Comparing multiple experimental treatments
To a common control
Within a single disease
Allow new treatments to enter across the life of the study
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5. Motivation Answer many questions in one study
In drug development we adapt and react to what is observed on the trial and the emerging treatment landscape
Study population: one disease: one type of cancer
Heterogeneous population
Multiple genetic markers or biomarkers
What decision(s) do we want to make?
Find the treatment that shows the greatest improvement over standard of care? Find the best treatment for the population?
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6. Example Consider an example in early development
Find a ‘better’ treatment regimen
Assume the combination of medicines A+B is active and safe. Assuming the combination with X is safe, tolerable and feasible, explore the addition of X, i.e. A+B+X.
A+B vs A+B+X
Suppose instead we have X1, X2, X3, X4, X5 potential combination partners! What do we explore? Where do we invest? How do we decide?
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7. Platform trial Treatments enter and leave the trial
Multiple interim analyses
Duration of trial
Control (A+B)
A+B+X1
A+B+X2
A+B+X3
A+B+X4
A+B+X5
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8. Benefits of the platform trial
Answer more questions with greater efficiency
One master protocol
One trial with one database
consistent data collection across all treatment arms
pooling data within one trial
Add and remove new combination partners without closing the trial or opening a new trial
Allow early decisions to halt ineffective treatments
One control arm (A+B)
more than one control arm may be needed, over time
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9. What could the platform trial look like?
Design considerations (I)
One disease: one type of cancer
Biomarker assay
Is prescreening needed
Prevalence of biomarker in the study population
Subgroup by biomarker status
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10. What could the platform trial look like?
Design considerations (II)
Endpoints of interest
Response rate
PFS
Duration of response
Considerations
Time to response
Indirect comparisons between experimental arms
Timing of disease assessments
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11. What could the platform trial look like?
Design considerations (III)
Total study duration
Over time, the treatment landscape may change as new therapies become available
Patients who enter the study later may receive prior therapies that weren’t available to patients who entered the study earlier
Does the response to the control change over time
Switch control mid-study
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12. What could the platform trial look like?
Design considerations (IV)
Multiple interim analyses needed
Minimum number of patients, overall and by treatment arm, included in first interim analysis
Timing of interim analyses
Decision rules for stopping an ineffective treatment
Decision rules for progressing an effective treatment
Impact on the standard of care arm
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13. Next steps Generate hypotheses for next trials?
Assess treatment landscape
Refine biomarker strategy?
Apply learnings to inform future platform trials
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14. Conclusions
Extensive discussions are needed in advance of designing the study
What decisions do we want to make by running the platform trial
Consider the benefits of the platform trial
Weigh the challenges of the platform trial
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15. References
Saville, BR and Berry, SM. (2016) Efficiencies of platform clinical trials: A vision of the future. Clinical Trials, Vol 13(3)
Woodcock, J and LaVange, LM. (2017) Master Protocols to Study Multiple Therapies, Multiple Diseases, or Both. The New England Journal of Medicine, 377:
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