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W-31: An Adaptive Seamless Phase II/III Design in Drug Development for Binary Endpoints





Poster Presenter

      Lien-Cheng Chang

      • Senior Secretary, Department of Intellectual Property and Technology Transfer
      • Academia Sinica
        Taiwan

Objectives

To use adaptive methodology to combine separated phase II and phase III clinical trials into a single trial

Method

We propose an adaptive seamless phase II/III design based on dichotomous data with controlling overall type I and II error rates. Sample sizes and critical values for each stage will also be determined.

Results

Drug development is risky, complex, time-consuming and costly, often taking more than 10 years and costing over 800 million US dollars from start to regulatory approval for marketing. The current drug development paradigm may not be suitable today. New concepts, strategies, and methodologies are needed to encourage growth and investment in the pharmaceutical industry. We propose a seamless, adaptive phase II/III design for clinical trials with binary endpoints. In the phase II stage patients are randomly assigned to either receive one of several doses of the test drug or to the control group, If one or more doses are found more superior than the control group these doses are selected for the phase III stage. Patients of the selected dose groups and control group continue through to the confirmation stage. New patients recruited randomly receive a selected dose of either group. Critical value is found at each stage to determine whether the treatment should continue. Then traditional phase II and III trials are combined into a single trial. Data collected from phase II will be included in the final analysis, thus sample size reduction and time saving may be possible.

Conclusion

This design could be used in regions with similar ethnicity, e.g. the greater Chinese area. Then the phase II stage can be conducted in one region, whereas the phase III stage can be conducted in all regions. This may help in harmonizing clinical trial data from all regions, and save time and money for drug development.

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