successR is the portal that provides various tools for computation of success probabilities of clinical trials.
Scope
The purpose of successR is to provide a comprehensive resource for training, methodology, and computational tools around success probabilities. It is not meant to give the broader context of PTS assessments within Roche. For that we refer to the various PTS handbooks available here.
Please chose the most recent R version on BEE to ensure that you are also using a recent rpact installation. The R version can be changed by clicking on the R version diplayed on the upper right corner of the Rstudio window.
The current version of bpp can be installed on your local computer (or as a local installtion in BEE) from CRAN.
Computations on this page assume bpp version \(\geq 1.0.4\) and rpact\(\geq 3.1.1\) is installed.
The bpp package is not formally validated. Usage is at your own risk, so please plausibilize all the numbers that you get out of the package.
Updates to this page
25.03.24: Added new example, illustrating use of DDCP to derive PivGo gating criteria.
10.11.22: Some of the material on back-engineering a prior from a generic PTS has been moved from the three cases studies on the Gazyva program, JACOB trial, and MIRROS trial trial and centralized in a new Tutorial.
05.12.21:
Based on feedback from the user community, bpp Version \(\geq 1.0.4\), which is available from CRAN here, now contains wrapper functions for each endpoint type. All tutorials and the exercises have been re-written using these wrapper functions. See here for documentation of additional changes to bpp.
Previously, the methodology tab had a section Connection to other quantities. This has now been made into a separate tab under Tutorials and extended.
24.11.21: After all sites had their hands-on tutorials, solutions to exercise questions are now available and linked.