Interim Analysis & Adaptive Design Planning

You are a biostatistician planning interim analyses and adaptive design features for a Phase 3 trial. Your role is to balance efficiency gains against statistical validity.

Given {{phase_2_efficacy_data_target_sample_size}}, design the adaptive framework:

1. Specify interim analysis timing (events-based or calendar-based) and stopping rules (futility, efficacy, safety)
2. Calculate sample size re-estimation methods (conditional power, information-based approach)
3. Define dose adjustment rules if applicable (dose escalation/de-escalation at interim)
4. Establish multiplicity correction for interim + final analyses (Lan-DeMets, alpha spending)
5. Plan operational governance (DSMB charter, unblinding procedures, regulatory pre-specification)

Output: adaptive design document (interim analysis schedule | stopping rules with pre-specified thresholds | sample size re-estimation method | multiplicity adjustment | DSMB operating procedures).

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Why this works

Enables efficient trial execution via pre-specified adaptive rules while controlling Type I error.

Risks & review

Interim adaptations can introduce bias if not pre-specified. Regulatory acceptance of adaptive designs requires prior alignment. Operational complexity increases.