DISCLAIMER: This represents my personal view and in no way reflects that of my company.
Warning: This is a long harangue that contains no useful information on R. May be wise to delete without reading. ---------- Sorry folks, I still don't understand your comments. As Cody's original post pointed out, there are a host of factors other than ease of programmability or even quality of results that weigh against any change. To reiterate, all companies have a huge infrastructure of **validated SAS code** that would have to be replaced. This, in itself, would take years and cost tens of millions of dollars at least. Also to reiterate, it's not only statistical/reporting functionality but even more the integration into the existing clinical database systems that would have to be rewritten **and validated**. All this would have to be done while continuing full steam on existing submissions. It is therefore not surprising to me that no pharma company in its right mind even contemplates undertaking such an effort. To put these things into perspective. Let's say Pfizer has 200 SAS programmers (it's probably more, as they are a large Pharma, but I dunno). If each programmer costs, conservatively, $200K U.S. per year fully loaded, that's $40 million U.S. for SAS Programmers. And this is probably a severe underestimate. So the $14M quoted below is chicken feed -- it doesn't even make the radar. To add further perspective, a single (large) pivotal clinical trial can easily cost $250M . A delay in approval due to fooling around trying to shift to a whole new software system could easily cause hundreds of million to billions if it means a competitor gets to the marketplace first. So, to repeat, SAS costs are chicken feed. Yes, I suppose that the present system institutionalizes mediocrity. How could it be otherwise in any such large scale enterprise? Continuity, reliability, and robustness are all orders of magnitude more important for both the FDA and Pharma to get safe and efficacious drugs to the public. Constantly hopping onto the latest and greatest "craze" (yes, I exaggerate here!) would be dangerous, unacceptable, and would probably delay drug approvals. I consider this another example of the Kuhnsian paradigm (Thomas Kuhn: "The Structure of Scientific Revolutions")in action. This is **not** to say that there is not a useful role for R (or STATA or ...) to play in clinical trial submissions or, more generally, in drug research and development. There certainly is. For the record, I use R exclusively in my (nonclinical statistics) work. Nor is to say that all change must be avoided. That would be downright dangerous. But let's please keep these issues in perspective. One's enthusiasm for R's manifold virtues should not replace common sense and logic. That, too, would be unfortunate. Since I've freely blustered, I am now a fair target. So I welcome forceful rebuttals and criticisms and, as I've said what I wanted to, I will not respond. You have the last word. Bert Gunter Genentech Nonclinical Biostatistics -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Frank E Harrell Jr Sent: Thursday, February 18, 2010 6:01 AM To: bill.venab...@csiro.au Cc: r-help@r-project.org; p.dalga...@biostat.ku.dk Subject: Re: [R] Use of R in clinical trials I really like both of your responses. To add to Peter's thoughts, I've found that more than half of SAS programmers can learn modern programming languages given a push. And if pharmaceutical companies ever knew the true cost of SAS in terms of their having to hire more programmers to deal with an archaic language they would be astonished. Rumor had it that Pfizer's yearly SAS licensing costs were $14M/year several years ago. Programmer costs were probably in the same range. Frank bill.venab...@csiro.au wrote: > I can't believe I'm saying this, but I think Peter is being a bit harsh on SAS. > > I prefer Greg Snow's analogy (in the fortune collection): If SPSS (or SAS) and R were vehicles, SPSS would be the bus, going on fixed routes and efficiently carrying lots of people to standard places, whereas R is the off-road 4WD SUV, complete with all sorts of kit including walking boots, kayak on the top, &c. R will take you anywhere you want to go, but it might take you longer to master it than the simple recipes for data analysis typical of the 'bus' programs. > > > Bill Venables > CSIRO/CMIS Cleveland Laboratories > > > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Peter Dalgaard > Sent: Thursday, 18 February 2010 5:55 PM > To: Frank E Harrell Jr > Cc: r-help@r-project.org; Cody Hamilton > Subject: Re: [R] Use of R in clinical trials > > Frank E Harrell Jr wrote: >> Cody, >> >> How amazing that SAS is still used to produce reports that reviewers >> hate and that requires tedious low-level programming. R + LaTeX has it >> all over that approach IMHO. We have used that combination very >> successfully for several data and safety monitoring reporting tasks for >> clinical trials for the pharmaceutical industry. >> >> Frank > > There is a point to it, though. One of my friends and colleagues in the > business put it in one word: Mediocrity. > > SAS does a mediocre job at analysing and reporting and data handling > using a mediocre control language. But: It can be handled by mediocre > programmers writing and modifying mediocre programs, and those people > are more available and replaceable, maybe even cheaper. R/LaTeX may run > circles around SAS in terms of capapilities, flexibility, and elegance, > but it can also send a programmer who doesn't have the required skill > set running around in circles. > > -pd > >> Cody Hamilton wrote: >>> Dear all, >>> >>> There have been a variety of discussions on the R list regarding the >>> use of R in clinical trials. The following post from the STATA list >>> provides an interesting opinion regarding why SAS remains so popular >>> in this arena: >>> http://www.stata.com/statalist/archive/2008-01/msg00098.html >>> >>> Regards, >>> >>> -Cody Hamilton > > -- Frank E Harrell Jr Professor and Chairman School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ R-help@r-project.org 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. ______________________________________________ R-help@r-project.org 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.
