Statistics and Data Science Seminar: Integrating Translational Data and Statistical Innovation, by Nan Xi
April 16, 2025
4:00 PM - 4:50 PM
Nan Xi (AbbVie): Integrating Translational Data and Statistical Innovation
Combination drug therapies hold significant promise in enhancing treatment efficacy, particularly in fields such as oncology, immunotherapy, and infectious diseases. However, designing clinical trials for these regimens poses unique challenges due to multiple hypothesis testing, shared control groups, and overlapping treatment components that induce complex correlation structures. In this work, we develop a novel statistical framework tailored for early-phase translational combination therapy trials, with a focus on platform trial designs. Our methodology introduces a generalized DunnettÂ’s procedure that controls false positive rates by accounting for the correlations between treatment arms. Additionally, we propose strategies for power analysis and sample size optimization that leverage preclinical data to estimate effect sizes, synergy parameters, and inter-arm correlations. Simulation studies demonstrate that our approach not only controls various false positive metrics under diverse trial scenarios but also informs optimal allocation ratios to maximize power. A real-data application further illustrates the practical integration of translational preclinical insights into the clinical trial design process. Overall, our framework provides practical and statistically robust guidance for the design of early-phase combination therapy trials, enhancing the efficiency of the bench-to-bedside transition.
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Date posted
Apr 14, 2025
Date updated
Apr 14, 2025
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