Legitimizing R in Regulated Systems

Hello Everyone!

I work in the pharmaceutical industry, and I am working towards expanding the use of R in drug research and discovery. Nearly all of the programmers I meet in this industry are SAS programmers, and not to hate on SAS, it has its place, but a lot of the opportunities to improve how we investigate drug safety and efficacy is out of reach for most SAS programs.
Where I currently work, I administer a very small RStudio and shiny server, and with these, I have created applications to improve workflow and data fitness. I worry about all the other programmers that got their server requests denied out of fear, ignorance, or apathy towards R. My goal of this post is to get some feedback on the challenges facing R in general and specifically to a regulated, established industry like pharmaceuticals.
I've many presentations on how to administer R in a way the produces accurate, reproducible research, but this is more of a question of convincing those who know nothing about R.

  • What challenges have other people faced in getting a dedicated R environment?
  • At organizations that have mature R development teams, what did your growth look like?
  • What kind of features of R, Rstudio, shiny server, R Package manager, etc., would help me justify them during a cost/benefit analysis?
  • What roadblocks do you see for the industry as a whole?

Thank you for reading and I look forward to any discussion!


These two challenges are probably common for any organization, no matter how tightly regulated:

  1. Convincing an organization's lawyers to approve the different open source licenses. Sadly, this could also include explaining that "open source" is not the "freeware" of yesteryear which could come with malicious aspects.

  2. Legacy code. Converting working programs can be huge effort with no immediate benefit. But if the org has some programs in SAS and others in R, then it has to maintain environments for both languages. Big cost no matter what.

Statisticians aren't seen as developers in my org, so we're allowed to use any tool as long as legal and some tech guys say it's not dangerous. This is great for experimentation, but not so great for collaboration.

I've been convincing others to use R by showing results SAS can't do: reports made with bookdown, nice GUIs for internal tools made with Shiny. I first tried proselytizing the developer benefits: more flexible than SAS, functions are better than macro abuse, sharing code is a breeze. Nobody was buying it, and for good reason:

They hadn't experienced it
\Rightarrow They didn't believe me
\Rightarrow They didn't try learning it
\Rightarrow They never would experience it

Thanks for the feedback. I'm in a similar situation where there are a good number of R programmers, but we are just now trying to create a organization wide development environment for R programming and application deployment. I think collaboration might be the next step and its just a matter of reaching that critical mass of users.
Any advise on improving collaboration? It can be a struggle to spreed the use of R throughout the organization when all of the R programmers are using their own environment. Most of R administration is the responsibility of individual users.


A lot of people use R in pharma and we all experience similar problems to different levels so there lots of people who might be able to chime in on worked for them. Personally, I would suggest attending the RinPharma conference in Boston this year. It was fantastic last year with lots of shared experiences.




It depends on what level of collaboration you're going for. Like I said, statisticians aren't developers where I work, so I haven't been able to convince them to use a standard environment. And, really, that's fine. It would have been a waste of time to create a shared environment before there was even a project with more than one analyst. I've found it easier to manage and recruit people with an "organic growth" style.

First, the few R users in my section started an R User Group for the whole org. We sent out emails to every section that had somebody doing statistics. This has definitely ignited informal collaboration. I've also created a package with internally useful resources (datasets, report formatting, logos) and advertise it often.

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Thank you for your reply!
This is exactly why we started the R/Pharma conference. Please check out our conference website http://rinpharma.com for our program and participate.

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