Application of Group Sequential Methods to the 2-in-1 Design and Its Extensions for Interim Monitoring

Abstract

The 2-in-1 adaptive design (Chen et al. 2018) allows seamless expansion of an ongoing Phase 2 trial into a Phase 3 trial to expedite a drug development program. Under a mild assumption expected to generally hold in practice, as Slepian’s lemma guarantees, the trial can be tested at the full alpha level with or without expansion, sacrificing no statistical power. The endpoint used for expansion decisions can be the same as or different from the primary endpoints, and there is no restriction on the expansion threshold. Due to its flexibility and robustness, it has drawn immediate attention from academic researchers and industry practitioners. The design has been substantially extended in the literature and successfully implemented in multiple trials.

Group sequential methods are a cornerstone in trial monitoring. A preliminary investigation (Chen, Li, and Deng) suggests that it can be naturally incorporated into the 2-in-1 design without providing formal mathematical proof. In this article, we fill the gap by providing a sufficient condition that is expected to generally hold in practice to unlock the full potential of the 2-in-1 design and pave the way for its broader applications. In practice, the condition can be verified with trial data as needed using simulation studies per the FDA guideline on adaptive designs. We also discuss a special case that guarantees the validity without the need for any simulation checking.

KEYWORD:

• Adaptive design
• Clinical trials
• Group sequential design
• Seamless phase 2/3 2-in-1 design
• Slepian’s lemma

Disclosure Statement

Dr. Cong Chen is an employee of Merck & Co. Inc and a stockholder of biopharmaceutical companies, who may benefit from the publication.

Additional information

Funding

This research was enabled in part by computing resources support provided by WestGrid and Compute Canada. Dr. Xuekui Zhang is supported by Canada Research Chair [CRC-2021-00232] and Michael Smith Foundation for Health Research – Scholar Program [SCH-2022- 2553], Dr. Li Xing is supported by NSERC Discovery grants [RGPIN-2021-03530].