FDA: R OK for drug trials

In a poster (PDF) presented at the UseR 2012 conference, FDA biostatistician Jae Brodsky reiterated the FDA policy regarding software used to prepare submissions for drug approvals with clinical trials: Sponsors may use R in their submissions.

The FDA does not endorse or require any particular software to be used for clinical trial submissions, and there are no regulations that restrict the use of open source software (including R) at the FDA. Nonetheless, any software (R included) used to prepare data analysis from clinical trials must comply with the various FDA regulations and guidances. The R Foundation helpfully provides a guidance document for the use of R in regulated clinical trial environments, which provides details of the specific FDA regulations and how R complies with them.

Despite some mistaken conceptions in the pharmaceutical industry, SAS is not required to be used for clinical trials. This origin of this fallacy is probably related to the fact that data must be submitted in the XPT "transport format" (which was originally created by SAS). This data format is now an open standard: XPT files can be read into R with the standard read.xport function, and exported from R with the write.xport function in the SASxport package. (And if you have legacy data in other SAS formats, there's a handy SAS macro to export XPT files.)

R is widely used at the FDA. (Full disclosure: the FDA is a Revolution Analytics customer.) The poster describes how FDA offices "use R on a daily basis", and that FDA scientists have written R packages for use by other scientists (within and outside the FDA) involved in the submissions process. FDA-contributed packages include popPK, MAVTgsa and QT, which was written specifically for the FDA's QT Interdisciplinary Review Team.

Jae Brodsky also provides some personal views on the use of R at the FDA. She notes:

• All results from data should be reproducible independent of software used.
• In submissions, FDA reviewers would like to know: which R functions were accessed; how they were accessed; and that the results are accurate, reliable and consistent.
• The FDA has used R for its own reports. (Interesting side-note: as a government agency, its reports must be Section 508 compliant, one part of which demands that reports be accessible to readers with limited color vision. Jae mentioned to me that she uses R's Rcolorbrewer package to generate 508-compliant pallettes for charts in FDA reports, as the poster excerpt below demonstrates.)

In Jae's experience, "R use at the FDA is completely acceptable and has not caused any problems." So as more and more companies adopt R for statistical analysis, we can expect to see more FDA clinical trial submissions using R for statistical analysis, reporting, and data visualization.