|
Abstract:
|
The aspect of one-size-fits-all conventional design which only contains fixed term study duration has recently been challenged, particularly when the diseases (e.g. oncology) may be heterogeneous due to observable clinical characteristics and/or unobservable underlying the biologic/genomic characteristics. The use of Bayesian techniques, in particular for the design and interpretation of clinical trials, offers several substantial advantages over the classical statistical approach. Bayesian statistics in clinical trial design and trial implementation can either supplement or replace classical statistics and potentially improve the development of a oncology drug for unmet medical need, while providing better treatment to cancer patients involved in these trials. Using Bayesian framework, we propose an adaptive design that allows us to expand an ongoing Phase II trial into a Phase III trial based on Go/No Go decision-Making to expedite a drug development program with fewer patients in early stage of oncology drug development.
|
