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ADDPLAN® PE provides simulation and analysis functionality for adaptive enrichment designs including population selection, sample size re-estimation and early stopping for efficacy or futility using adaptive group sequential design approaches. The inverse normal and Fisher’s p-value combination testing strategies, several multiple testing procedures and many alternative subpopulation(s) selection rules may be used for the evaluation of study design options.

ADDPLAN® PE was the first validated software for adaptive confirmatory studies with population enrichment.

  • Simulate Design: Calculation of operating characteristics for studies including multiple populations
    • Control of family-wise error rate
    • Early success/futility stopping
    • Sample size re-estimation based on conditional power
    • Wide range of subgroup (population) selection rules
    • Simulation settings allowing easy power examination for prevalence and efficacy scenarios
    • Simulation of population selection based on surrogate endpoints for survival data ADDPLAN® PE manual provides insight into the applied methodology and worked examples
    • Simulation of treatment selection based on surrogate endpoints for survival data
  • Adaptive Analysis: Interim & final analysis of adaptive population enrichment study designs including:
    • Flexible dropping of populations
    • Sample size re-estimation based on observed or assumed effects
    • Conditional power calculation based on the remaining total sample size
    • Repeated confidence intervals taking possible early stopping into account.



Design Your Trial

All Relevant Group Sequential Designs


Compare Your Effect Size

Ready-to-Use Text Modules


Visualize Your Decision Boundaries

Simulate Your Trial Design


Compare Test Strategies

Assess Survival Assumptions


Dose-Response Shape

Assess Treatment Arm Selection Rules


Produce Your Own Charts and Tables

Analyze Your Data


Seamless Phase II/III Combinations

Enrichment Designs


Visualize Your Trial's Progress

Recalculate the Sample Size


Demonstrate the Conditional Power

Redesign Your Trial


Audit Trial Information