[R] FDA and ICH Compliance of R
Frank E Harrell Jr
feh3k at spamcop.net
Thu Nov 27 15:04:38 CET 2003
On Thu, 27 Nov 2003 07:48:02 +0100
"Antonia Drugica" <antoniamarija at net.hr> wrote:
> I'm quite new to this medical stuff. But my associates told me that we
> are not free in choice of Statistical Software because the FDA has high
> standards concerning this topic. But if they would prefer a specific
> package (like SAS) that could mean, that this package vendourer could
> lay back and hold it's hand open for licence money.
Your associates are completely wrong. It is only sponsors that choose not
to be free in their choice, due in my humble opinion mainly to the fact
that SAS has been in use since 1966 and that "no one has ever been
criticized by the FDA for using SAS." FDA even receives submissions based
on Excel and we all know about the accuracy of Excel's statistical
calculations. High standards need to be held by statisticians doing the
analyses. Related to such standards open source systems such as R have
many advantages, and the reproducible reporting capabilities of R using
its Sweave package have major impacts on accuracy of reporting.
I along with colleagues at another institution are working on an open
source R package for clinical trial analysis and reporting that should be
mature in about a year. I am currently using the package in two
pharmaceutical industry-sponsored randomized clinical trials to report to
data monitoring committees. I'm also working on a document addressing
validation of statistical calculations. Let me know if you'd like a copy
of the current version of that document.
> Is there any part of the ICH document referring to software packages? I
> really would use R for some tasks but therefor I need arguments...
Don't know of anything in ICH.
In view of the fact that large pharma companies have to pay more than $10M
per year in SAS licenses and have to hire armies of non-intellectually
challenged SAS programmers to do the work of significantly fewer
programmers that use modern statistical computing tools like R and S-Plus,
it is surprising that SAS is still the most commonly used tool in the
clinical side of drug development. I quit using SAS in 1991 because my
productivity jumped at least 20% within one month of using S-Plus.
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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