RESTART trial design: two-stage seamless transition design with operational considerations
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Published on: June 9, 2020
Min Yi1, Bin Zhuo2, Freda Cooner3
1Arrowhead Pharmaceuticals Inc., Biostatistics, Pasadena, CA, USA.
Abstract:
Oncology/hematology is a competitive therapeutic area where the landscape is constantly evolving. With regulatory support, many drug developers have spent a lot of resources on the operationalization of innovative clinical trial designs, for example, adaptive Bayesian designs in confirmatory clinical trial settings. While overall survival is considered the gold standard in these designs, it is often not a viable choice in identifying treatment efficacy at a reasonable pace, especially for early-stage therapies. In recent years, several binary response surrogate endpoints have been used for accelerated or conditional approval of novel cancer therapies. Utilizing surrogate endpoints in the study design to predict objective clinical outcomes, such as overall survival, is particularly fundamental in cancer treatment clinical development. This manuscript will investigate logistic and statistical considerations of our proposed RESTART design, a new two-stage, seamless, single- to double-arm Bayesian design. This design could be used for single-arm dose expansion to a randomized confirmatory study. The operating characteristics of the RESTART design are evaluated based on simulations. Future directions and further modifications of this design will also be elaborated.
Insights
The RESTART design offers a novel Bayesian approach for oncology clinical trials, enabling faster evaluation of early-stage therapies using surrogate endpoints instead of overall survival. This adaptive design facilitates seamless transitions from single-arm to randomized confirmatory studies.
Area of Science:
- Oncology and Hematology Clinical Trials
- Biostatistics and Clinical Trial Design
- Drug Development and Regulatory Science
Background:
- The oncology/hematology field demands innovative clinical trial designs due to its competitive and rapidly evolving nature.
- Traditional overall survival endpoints can be slow for evaluating early-stage therapies, necessitating alternative approaches.
- Surrogate endpoints are increasingly utilized for accelerated approval of novel cancer treatments.
Purpose of the Study:
- To investigate the logistic and statistical considerations of the proposed RESTART design.
- To introduce a new two-stage, seamless, single- to double-arm Bayesian adaptive design for oncology trials.
- To evaluate the operating characteristics of the RESTART design through simulations.
Main Methods:
- The study proposes the RESTART design, a Bayesian adaptive framework.
- This design facilitates a seamless transition from single-arm dose expansion to a randomized confirmatory study.
- Simulations are used to assess the operating characteristics of the RESTART design.
Main Results:
- The RESTART design is a viable Bayesian approach for oncology trials.
- The design allows for efficient evaluation of novel cancer therapies.
- Simulations demonstrate the feasibility and characteristics of the RESTART design.
Conclusions:
- The RESTART design offers a flexible and efficient adaptive strategy for oncology drug development.
- This Bayesian approach can accelerate the evaluation of early-stage cancer therapies.
- Further research will explore modifications and future directions for the RESTART design.
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