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In clinical development with biologics, PoC is a critical step that motivates later stage trials and profoundly impacts the CMC process. Early claim of PoC may save valuable time for the drug development. A new type of clinical trial called basket trial emerged recently. In the setting of oncology, experimental treatment targets an oncogenic pathway hypothesized to modulate the tumor growth and/or metastasis, and patients with the same genetic or molecular aberration but potentially multiple cancer types are enrolled. The problem of preliminary PoC is complicated with the early phase basket trials due to small sample size and large number of cancer types.
In this poster, we propose an approach for the assessment of preliminary PoC in early phase oncology basket trials under a Bayesian hierarchical modeling framework. We categorize cancer types into either an "active group" or an "inactive group", depending on observed response rates. We assess the preliminary PoC by the posterior probability that at least one cancer type is responsive. Simulation results are presented.
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