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Abstract:
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Selecting patients using a potential predictive biomarker is a challenging question facing oncology developers in early stage of development when the amount of data concerning the biomarker’s predictivity to treatment response in patients is limited. In this presentation, we will discuss a method we developed that incorporated limited understanding of biomarker predictivity, assay performance and biomarker prevalence in targeted population to estimate the response rate of BRAF inhibitors in BRAF mutant melanoma patients. We were able to model the limited understanding of the biomarker with a probabilistic distribution to quantify the uncertainty associated with the estimate of clinical response rate. Finally, we demonstrate the model’s potential utility using preclinical biomarker data from a CRSPR screening, which enabled an early clinical oncology program to make challenging decisions on selecting a predictive biomarker for clinical development.
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