Just How Flexible Can a Prospective Clinical Trial Be?

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Just How Flexible Can a Prospective Clinical
Trial Be?

• Donald A. Berry
• dberry_at_mdanderson.org

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Definition of flexible

• Pliant
• Characterized by a ready capability to adapt to
  new, different, or changing requirements

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With thanks to Mike Krams Vlad Dragalin
AD4P71VE?
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Original question is not helpful

• Two kinds of flexibility
• Ad hoc (improvised)
• Planned (prospective)

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Original question is not helpful

• Two kinds of flexibility
• Ad hoc okay for personal or internal company
  decisions
• Planned essential for external buy-in

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New question 1 How to deal with ad hoc
flexibility in a clinical trial?
You cant!
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New question 2 How to deal with planned
flexibility in a clinical trial?

• Design
• The team on board?
• Logistics
• Regulatory

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Design

• Modeling--arbitrarily complicated
• Efficacy and safety
• Computation
• OCs comparisons
• Type I error
• Power
• Sample size
• Alternative designs

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The team on board?

• You have to teach them
• And you have to keep teaching them!
• I dont want the DSMB making decisions such as
  whether to go to phase III.
• DSMB as automaton

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Logistics

• Data flow Updating database
• Clean data? (no, but model)
• QA
• Auxiliary variables
• Central review
• Missing data--same as above
• What CRO?
• Information leakage--who knows what and when?

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Logistics (contd)
Adaptive design is a whole new ball game. If
you dont know what you are doing, you can do
some very bad things and damage the integrity of
the trial, and of the whole process.
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Who knows what when?

• Phase I or II vs Phase III
• Dose-finding (The Pharmacist Knows)
• Dropping arms or adaptive randomization (blinded
  vs open)
• Seamless phase II/III
• Simple line in the sand (Publish but continue to
  accrue?)
• End of phase II meeting
• Expanding accrual
• One study or two?

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Regulatory

• CRCs and IRBs
• Please explain in lay terms (Examples,
  examples, examples)
• Informed consent?
• FDA, EMEA
• Meet early as often as possible

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The Bottom Line

• Clinical trials will continue to become more
  complicated (such as I-SPY2)
• This is good and bad
• Trials must begin to address interactions between
  treatments and patient covariates

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The Bottom Line

• Traditional trials are poorly suited for
  identifying treatments that benefit patients who
  have hetero-geneous diseases such as cancer
• The adaptive path is treacherous, with mines
  every step of the way
• Avoiding mines is challenging, but enormously
  rewarding ... and fun!