Abstract
Understanding of the efficacy of an investigated compound in early drug development often relies on assessment of a biomarker or multiple biomarkers that are believed to be correlated with the intended clinical outcome. The biomarker of interest may require enough duration of time to show its satisfactory response to drug effect. Meanwhile, many drug candidates in the portfolio of a pharmaceutical company may compete for the limited resources available. Thus decisions based on assessment of the biomarker after a prolonged duration may be inefficient. One solution is that longitudinal measurements of the biomarker be measured during the expected duration, and analysis be conducted in the middle of the trial, so that the interim measurements may help estimate the measurement at the intended time for interim decision making. Considering the small trial size nature of early drug development and convenience in facilitating interim decisions, we applied Bayesian inference to interim analysis of biomarkers.
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Wang, MD., Li, G.Y. (2013). Bayesian Interim Inference of Probability of Clinical Trial Success. In: Hu, M., Liu, Y., Lin, J. (eds) Topics in Applied Statistics. Springer Proceedings in Mathematics & Statistics, vol 55. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7846-1_12
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DOI: https://doi.org/10.1007/978-1-4614-7846-1_12
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