[R] "R is not a validated software package.."

[Sicotte, Hugues Ph.D.]

I may have overstated  things a bit.

See section VIII
http://www.fda.gov/CDER/GUIDANCE/2396dft.htm

If you are analyzing data your statistical package does not necessarely
have to be validated. You may have to show that the statistical methods
are adequate/appropriate or that the results are reproduced with
different softwares if you are using non-standard packages. By all
tests, S-plus appears acceptable, do not know about R.

However, If your statistical method is an intricate part of a test, then
you do have to validate the system.
This is becoming increasingly relevant for theragnostics.

.. Which is why I said
"Should they need to use those results in a report [where] that will
matter to the FDA.."
(I added the where .. It makes more sense)



-----Original Message-----
From: Frank E Harrell Jr [mailto:f.harrell at vanderbilt.edu] 
Sent: Friday, June 08, 2007 11:08 AM
To: Sicotte, Hugues Ph.D.
Cc: Wensui Liu; Giovanni Parrinello; r-help at stat.math.ethz.ch
Subject: Re: [R] "R is not a validated software package.."

Sicotte, Hugues Ph.D. wrote:
> People, don't get angry at the pharma statistician, he is just trying
to
> abide by an FDA requirement that is designed to insure that test
perform
> reliably the same. There is no point in getting into which product is
> better. As far as the FDA rules are concerned a validated system beats
a
> "better" system any day of the week.

There is no such requirement.

> 
> Here is your polite answer.
> You can develop and try your software in R.
> Should they need to use those results in a report that will matter to
> the FDA, then you can work together with him to set up a validated
> environment for S-plus. You then have to commit to port your code to
> S-plus.

That doesn't follow.  What matters is good statistical analysis practice

no matter which environment you use.  Note that more errors are made in 
the data preparation / derived variables stage than are made by 
statistical software.

Frank

> 
> As I assume that you do not work in a regulated environment, you
> probably wouldn't have access to a validated SAS environment anyways.
It
> is not usually enough to install a piece of software, you have to
> validate every step of the installation. Since AFAIK the FDA uses
> S-plus, it would be to your pharma person's advantage to speed-up
> submissions if they also had a validated S-plus environment.
> 
>
http://www.msmiami.com/custom/downloads/S-PLUSValidationdatasheet_Final.
> pdf
> 
> 
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Wensui Liu
> Sent: Friday, June 08, 2007 9:24 AM
> To: Giovanni Parrinello
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] "R is not a validated software package.."
> 
> I like to know the answer as well.
> To be honest, I really have hard time to understand the mentality of
> clinical trial guys and rather believe it is something related to job
> security.
> 
> On 6/8/07, Giovanni Parrinello <parrinel at med.unibs.it> wrote:
>> Dear All,
>> discussing with a statistician of a pharmaceutical company I received
>> this answer about the statistical package that I have planned to use:
>>
>> As R is not a validated software package, we would like to ask if it
>> would rather be possible for you to use SAS, SPSS or another approved
>> statistical software system.
>>
>> Could someone suggest me a 'polite' answer?
>> TIA
>> Giovanni
>>
>> --
>> dr. Giovanni Parrinello
>> External Lecturer
>> Medical Statistics Unit
>> Department of Biomedical Sciences
>> Viale Europa, 11 - 25123 Brescia Italy
>> Tel: +390303717528
>> Fax: +390303717488
>> email: parrinel at med.unibs.it
>>
>>
>>         [[alternative HTML version deleted]]
>>
>> ______________________________________________
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>> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
> 
> 


-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt
University