[R] Use of R in clinical trials

[myrmail at earthlink.net]

I am old enough to have lived through this particular transition.
Prior to the advent of SAS, trials were analyzed by in-house written
programs (usually in Fortran maybe with the help of IMSL). These
programs were huge card decks. Having the card reader eat a card
half way through reading the deck was a not unusual occurrence.

I was responsible for deploying the first version of SAS. This meant
compiling PL/I code stored on a magnetic tape and storing it on limited
and expensive disk drives. It was several years before the transition
from using in-house programs to SAS was completed. Yes there was a
great deal of angst and I spent a lot of time convincing people that
in the end there would be a cost advantage and overcoming institutional
inertia.

By the way, this was all done on computers that you will probably find
only in a museum, if at all. These systems filled whole rooms and required
a staff just to keep them running.

Murray M Cooper, PhD
Richland Statistics
9800 North 24th St
Richland, MI  49083



-----Original Message-----
>From: "Christopher W. Ryan" <cryan at binghamton.edu>
>Sent: Feb 18, 2010 1:08 PM
>To: r-help at r-project.org
>Cc: p.dalgaard at biostat.ku.dk
>Subject: Re: [R] Use of R in clinical trials
>
>Pure Food and Drug Act: 1906
>FDA: 1930s
>founding of SAS: early 1970s
>
>(from the history websites of SAS and FDA)
>
>What did pharmaceutical companies use for data analysis before there was 
>SAS? And was there much angst over the change to SAS from whatever was 
>in use before?
>
>Or was there not such emphasis on and need for thorough data analysis 
>back then?
>
>--Chris
>Christopher W. Ryan, MD
>SUNY Upstate Medical University Clinical Campus at Binghamton
>425 Robinson Street, Binghamton, NY  13904
>cryanatbinghamtondotedu
>
>"If you want to build a ship, don't drum up the men to gather wood, 
>divide the work and give orders. Instead, teach them to yearn for the 
>vast and endless sea."  [Antoine de St. Exupery]
>
>Bert Gunter wrote:
>> 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
>
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