[R] R, clinical trials and the FDA

[Kingsford Jones]

I hope that Marc doesn't mind, but I felt that part of his recent post
was important enough to deserve it's own subject line rather then
being lost in a 60-msg-long thread...



On Sun, Jan 11, 2009 at 10:08 AM, Marc Schwartz
<marc_schwartz at comcast.net> wrote:

...

I strongly believe that the comments regarding R and the FDA are overly
negative and pessimistic.

The hurdles to the use of R for clinical trials are shrinking. There has
been substantive activity over the past several years, both internally
at the FDA and within the R community to increase R's acceptance in this
domain.

At the Joint Statistical Meetings in 2006, Sue Bell from the FDA spoke
during a session with a presentation entitled Times 'R' A Changing: FDA
Perspectives on Use of "Open Source". A copy of this presentation is
available here:

 http://www.fda.gov/cder/Offices/Biostatistics/Bell.pdf

In 2007, during an FDA committee meeting reviewing the safety profile of
Avandia (Rosiglitazone), the internal FDA meta-analysis performed by Joy
Mele, the FDA statistician, was done using R. A copy of this
presentation is available here:
 http://www.fda.gov/ohrms/dockets/ac/07/slides/2007-4308s1-05-fda-mele.ppt

Given the high profile nature of drug safety issues today, that R was
used for this analysis by the FDA itself speaks volumes.

Also in 2007, at the annual R user meeting at Iowa State University, I
had the pleasure and privilege of Chairing a session on the use of R for
clinical trials. The speakers included Frank Harrell (well known to R
users here), Tony Rossini and David James (Novartis Pharmaceuticals) and
Mat Soukup (FDA statistician). Copies of our presentations are available
here, a little more than half way down the page:

 http://user2007.org/program/

At that meeting, we also introduced a document that has been updated
since then and approved formally by the R Foundation for Statistical
Computing. The document provides guidance for the use of R in the
regulated clinical trials domain, addresses R's compliance with the
relevant regulations (eg. 21 CFR 11) as well as describing the
development, testing and quality processes in place for R, also known as
the Software Development Life Cycle.

That document is available here:

 http://www.r-project.org/doc/R-FDA.pdf

I have heard directly from colleagues in industry that this document has
provided significant value in their internal discussions regarding
implementing the use of R within their respective environments and
assuaging many fears regarding R's use.

Additionally, presentations regarding the use of open source software
and R specifically for clinical trials have been made at DIA and other
industry meetings. This fall, there is a session on the use of R
scheduled for the FDA's Industry Statistics Workshop in Washington, D.C.

For those unfamiliar, I would also point out the membership and
financial donors to the R Foundation for Statistical Computing and take
note of the plethora of large pharma companies and clinical research
institutions:

 http://www.r-project.org/foundation/memberlist.html

The use of R within this domain is increasing and will only continue to
progress as R's value becomes increasingly clear to even risk averse
industry decision makers.


Regards,

Marc Schwartz