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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

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A Flexible Seamless Phase 2/3 Design With Biomarker-Driven Subgroup Enrichment and Sample Size Re-Estimation.

Zizhong Tian¹, Liwen Wu², Rachael Liu²

¹Department of Public Health Sciences, The Pennsylvania State University, Hershey, Pennsylvania, USA.

Pharmaceutical Statistics

|August 1, 2025

Summary

This study introduces a flexible seamless phase 2/3 adaptive design for drug development. It optimizes sample size and uses surrogate endpoints to improve efficiency and power, especially for patient subgroups.

Keywords:

adaptive design sample size re‐estimation seamless phase 2/3 design subgroup enrichment design surrogate endpoint

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Area of Science:

Clinical trial design
Biostatistics
Pharmaceutical development

Background:

Seamless phase 2/3 designs are increasingly used for expedited drug development.
Incorporating subgroup enrichment in adaptive designs is appealing but complex for sample size planning.
Balancing development timelines, risks, and subgroup uncertainties is crucial.

Purpose of the Study:

To propose a flexible seamless phase 2/3 adaptive design framework.
To enable population selection and sample size re-estimation using surrogate endpoints.
To address challenges in sample size planning for complex adaptive trials.

Main Methods:

Developed a flexible seamless phase 2/3 design with population selection and sample size re-estimation.
Utilized early surrogate endpoints for phase switching decisions.
Elucidated type I error patterns and proposed a control approach.
Conducted extensive simulation studies and a case study.

Main Results:

The proposed design offers advantages over fixed-sample designs in efficiency, power, and timeline saving.
Demonstrated effective control of the overall type I error.
The framework successfully integrates subgroup enrichment and adaptive sample size adjustments.

Conclusions:

The proposed flexible seamless phase 2/3 design framework enhances drug development efficiency and power.
This adaptive design effectively manages risks and uncertainties associated with subgroup effects.
The approach is illustrated with a practical case study in multiple myeloma treatment.