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12/7/2016 (Wednesday) 8:30 AM - 11:45 AM
Session I: Simulation-based approaches to clinical trial design and analysis
Dr. Alex Dmitrienko, Mediana Inc.
Moderator: Alfred Balch
This half-day course focuses on a broad class of statistical problems related to simulation-based assessment of optimal trial designs and analysis strategies in Phase II and III trials (Dmitrienko and Pulkstenis, 2017). This general topic has attracted much attention across the clinical trial community due to increasing pressure to reduce implementation costs and shorten timelines. The Clinical Scenario Evaluation (CSE) framework (Benda et al., 2010) will be described in this short course to formulate a general approach to optimal decision making in clinical trials. The CSE framework facilitates a comprehensive comparison of competing options for clinical development programs and clinical trial designs/analyses. The concept includes three different elements, namely, the set of underlying assumptions (data models), the options to be assessed (analysis models) and the metrics used for the assessment (evaluation models).
A comprehensive assessment of candidate designs and analysis methods makes heavy use of clinical trial simulations. Simulation-based approaches to evaluating trial designs and analysis methods will be discussed based on the general CSE approach. Simulation-based approaches will be illustrated using a number of problems that often arise in Phase II and III clinical trials. This includes optimal selection of analysis strategies that involve multiplicity adjustments (Dmitrienko et al., 2009; Dmitrienko, D’Agostino and Huque, 2013), selection of design elements in adaptive clinical trials (Dmitrienko et al., 2016) and selection of patient subgroups in enrichment designs. Practical solutions that the participants can quickly apply to address real-life challenges in clinical trials will be emphasized throughout this short course.
Multiple case studies based on real Phase II and III trials will be used, e.g., clinical trials with multiple endpoints and dose-placebo comparisons, trials with adaptive and enrichment designs. Software tools for applying the simulation-based CSE approaches will be presented, including R software (Mediana package) and Windows application with a graphical user interface (MedianaPro application).
- Benda, N., Branson, M., Maurer, W., Friede, T. (2010). Aspects of modernizing drug development using clinical scenario planning and evaluation. Drug Information Journal. 44, 299-315, 2010.
- Dmitrienko, A., Tamhane, A.C., Bretz, F. (editors) (2009). Multiple Testing Problems in Pharmaceutical Statistics. Chapman and Hall/CRC Press, New York.
- Dmitrienko, A., D’Agostino, R.B., Huque, M.F. (2013). Key multiplicity issues in clinical drug development. Statistics in Medicine. 32, 1079-1111.
- Dmitrienko, A., Paux, G., Pulkstenis, E., Zhang, J. (2016). Tradeoff-based optimization criteria in clinical trials with multiple objectives and adaptive designs. Journal of Biopharmaceutical Statistics. 26, 120-140.
- Dmitrienko, A., Pulkstenis, E. (editors). Clinical Trial Optimization Using R. Chapman and Hall/CRC Press, New York (to be published in 2017).
Alex Dmitrienko, PhD, is Founder and President of Mediana Inc. Dr. Dmitrienko has been involved in pharmaceutical statistics for 20 years and, prior to founding Mediana, worked at Quintiles (Vice President, Innovation Unit) and at Lilly (Research Advisor, Advanced Analytics). He has been actively involved in biostatistical research and has published over 80 papers on key topics in clinical trial statistics, including multiple comparisons, subgroup analysis, adaptive designs and analysis of safety data. He has authored/edited two SAS Press books (Analysis of Clinical Trials Using SAS, Pharmaceutical Statistics Using SAS) and a Chapman and Hall/CRC Press book (Multiple Testing Problems in Pharmaceutical Statistics). Dr. Dmitrienko has served as an Associate Editor for The American Statistician, Biometrics and Statistics in Medicine, and is a Fellow of the American Statistical Association.
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