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MSToolkit An R library for the Simulation of Clinical Trials

MSToolkit An R library for the Simulation of Clinical Trials. Andy Nicholls anicholls@mango-solutions.com. Agenda. Clinical Trial Simulation What is MSToolkit ? What can it do? Low Level Usage High Level Usage How to get it?. Clinical Trial Simulation. Andy Nicholls

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MSToolkit An R library for the Simulation of Clinical Trials

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  1. MSToolkitAn R library for the Simulation of Clinical Trials Andy Nicholls anicholls@mango-solutions.com

  2. Agenda • Clinical Trial Simulation • What is MSToolkit? • What can it do? • Low Level Usage • High Level Usage • How to get it?

  3. Clinical Trial Simulation Andy Nicholls anicholls@mango-solutions.com

  4. “I have always considered it more desirable to kill computer-generated patients than real ones while calibrating design parameters”Peter Thall, MD Anderson Cancer Centre, Houston, TX

  5. Population Treatment Adapt Treatments Dropout Response Mathematical Model What to Simulate?

  6. What is MSToolkit? Andy Nicholls anicholls@mango-solutions.com

  7. MSToolkit History • In 2008, Pfizer asked Mango to design and develop simulation software • R selected, since available on their grid • SAS execution was a nice to have • Needed to appeal to 2 audiences: • Those who can code in R • Those who cannot, and just want to “do it”

  8. What is MSToolkit Today? • A free R library • Backed by Mango (validated, tests) • Functionality: • Set of “low level” functions to perform basic tasks • “High level” functions for those who want to simply “run > tweak > run > tweak” • Uses cluster (if available) to enhance performance • Can use SAS (if available) for analysis

  9. What can MSToolkit do? Andy Nicholls anicholls@mango-solutions.com

  10. MSToolkit: Low Level Usage • Suite of “Low Level” Functions • Aimed at R programmers • Can be used to enhance your scripts

  11. Low Level Components • Generate possible treatments • Allocate subjects to treatment arms • Generate parameters (fixed and random) • Generate covariates • Add missingness • Add dropout • Allocate subjects to interims • Generate responses • Analyze a dataset • Summarise a dataset • Apply an interim decision • Perform macro evaluation

  12. Low Level Components • createTreatments • allocateTreatments • createParameters • createCovariates • createMCAR • createDropout • createInterims • createResponse • analyzeData • compileSummary • interimAnalysis • macroEvaluation

  13. Generate Treatments

  14. Allocate Treatments

  15. Image Size Generate Covariates

  16. Creating Parameters

  17. Response + Resid. Error

  18. Allocate to Interims

  19. Recap

  20. MSToolkit: High Level Usage • 2 “Wrappers” for Low Level Functions • Generate simulated data (generateData) • Analyzes the data (analyzeData) • Aimed at those who don’t want to code • Allows standard definition of CTS

  21. Population generateData analyzeData Treatment Dropout Response Mathematical Model What to Simulate? Adapt Treatments

  22. Generating Data

  23. Generating Data

  24. Simulating the Analysis Image Size

  25. The analyzeDataFunction • Key Arguments: • analysisCode: R function, R script or SAS script containing analysis code • interimCode: Optional function that performs “interim” analyses • macroCode: R function that transforms an analysis into a single “success” flag

  26. analysisCode macroCode

  27. analysisCode analysisCode + interimCode macroCode

  28. Analysis code Summary code Interim code Perform analysis

  29. Using R for Analysis

  30. analyzeData Outputs

  31. MicroEvaluation Summary

  32. MacroEvaluation Summary

  33. How to get it? Andy Nicholls anicholls@mango-solutions.com

  34. Getting MSToolkit • MSToolkit 2.0 on CRAN • Version 3.0 on R-Forge

  35. Acknowledgements • Rich Pugh (Mango) • Mike Smith (Pfizer)

  36. Questions? Andy Nicholls anicholls@mango-solutions.com

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