Clinical trial simulations

Clinical trial simulations and Clinical Scenario Evaluation

Clinical trial simulations play a key role in developing efficient approaches to designing, conducting and analyzing trials, especially late-stage trials that utilize complex designs and analysis strategies where analytical evaluation approaches are typically not available. Thanks to simulations, trial sponsors can perform a comprehensive quantitative assessment of available options under a large number of treatment effect scenarios. Clinical Scenario Evaluation is an efficient quantitative approach to simulation-based evaluation of clinical trials that has found multiple applications across the biopharmaceutical industry.

Working group

Biopharmaceutical Software Working Group organized by the Biopharmaceutical Section of the American Statistical Association.

Key publications

  • Dmitrienko, A., Paux, G., Brechenmacher, T. (2016). Power calculations in clinical trials with complex clinical objectives. Journal of the Japanese Society of Computational Statistics. 28, 15-50.
  • 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). (2017). Clinical Trial Optimization Using R. Chapman and Hall/CRC Press, New York.
  • Paux, G., Dmitrienko, A. (2018). Penalty-based approaches to evaluating multiplicity adjustments in clinical trials: Traditional multiplicity problems. Journal of Biopharmaceutical Statistics. 28, 146-168.
  • Paux, G., Dmitrienko, A. (2018). Penalty-based approaches to evaluating multiplicity adjustments in clinical trials: Advanced multiplicity problems. Journal of Biopharmaceutical Statistics. 28, 169-188.

Software tools

Mediana package (R package for general simulation-based power and sample size calculations in fixed-sample trials).
Mediana Designer (free Windows-based software tool for traditional and simulation-based power/sample size calculations in fixed-sample and group-sequential trials).