Frank et. al: I believe this is a bit too facile. 21 CFR Part 11 does necessitate a software validation **process** -- but this process does not require any particular software. Rather, it requires that those using whatever software demonstrate to the FDA's satisfaction that the software does what it's supposed to do appropriately. This includes a lot more than assuring, say, the numerical accuracy of computations; I think it also requires demonstration that the data are "secure," that it is properly transferred from one source to another, etc. I assume that the statistical validation of R would be relatively simple, as R already has an extensive test suite, and it would simply be a matter of providing that test suite info. A bit more might be required, but I don't think it's such a big deal.
I think Wensui Liu's characterization of clinical statisticians as having a mentality "related to job security" is a canard. Although I work in nonclinical, my observation is that clinical statistics is complex and difficult, not only because of many challenging statistical issues, but also because of the labyrinthian complexities of the regulated and extremely costly environment in which they work. It is certainly a job that I could not do. That said, probably the greatest obstacle to change from SAS is neither obstinacy nor ignorance, but rather inertia: pharmaceutical companies have over the decades made a huge investment in SAS infrastructure to support the collection, organization, analysis, and submission of data for clinical trials. To convert this to anything else would be a herculean task involving huge expense, risk, and resources. R, S-Plus (and much else -- e.g. numerous "unvalidated" data mining software packages) are routinely used by clinical statisticians to better understand their data and for "exploratory" analyses that are used to supplement official analyses (e.g. for trying to justify collection of tissue samples or a pivotal study in a patient subpopulation). But it is difficult for me to see how one could make a business case to change clinical trial analysis software infrastructure from SAS to S-Plus, SPSS, or anything else. **DISCLAINMER** My opinions only. They do not in any way represent the view of my company or its employees. Bert Gunter Genentech Nonclinical Statistics South San Francisco, CA 94404 650-467-7374 -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Frank E Harrell Jr Sent: Friday, June 08, 2007 7:45 AM To: Giovanni Parrinello Cc: [email protected] Subject: Re: [R] "R is not a validated software package.." Giovanni Parrinello 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 > Search the archives and you'll find a LOT of responses. Briefly, in my view there are no requirements, just some pharma companies that think there are. FDA is required to accepted all submissions, and they get some where only Excel was used, or Minitab, and lots more. There is a session on this at the upcoming R International Users Meeting in Iowa in August. The session will include dicussions of federal regulation compliance for R, for those users who feel that such compliance is actually needed. Frank -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
