Adaptive Phase 2/3 Design with Dose Optimization

TL;DR

This paper addresses the challenge of controlling Type I error in adaptive Phase 2/3 oncology trial designs with dose optimization, proposing methods to improve efficiency and adherence to FDA's Project Optimus.

Contribution

It introduces new methods that explicitly estimate and incorporate the probability of selecting a better dose, reducing sample size inflation and improving trial efficiency.

Findings

Improved control of Type I error in adaptive dose selection.

Reduced sample size and trial duration.

Enhanced adherence to FDA's Project Optimus initiative.

Abstract

FDA's Project Optimus initiative for oncology drug development emphasizes selecting a dose that optimizes both efficacy and safety. When an inferentially adaptive Phase 2/3 design with dose selection is implemented to comply with the initiative, the conventional inverse normal combination test is commonly used for Type I error control. However, indiscriminate application of this overly conservative test can lead to substantial increase in sample size and timeline delays, which undermines the appeal of the adaptive approach. This, in turn, frustrates drug developers regarding Project Optimus. The inflation of Type I error depends on the probability of selecting a dose with better long-term efficacy outcome at end of the study based on limited follow-up data at dose selection. In this paper, we discuss the estimation of this probability and its impact on Type I error control in realistic settings. Incorporating it explicitly into the two methods we have proposed result in improved designs, potentially motivating drug developers to adhere more closely to an initiative that has the potential to revolutionize oncology drug development.