R: The Future is Now

R is fast becoming the tool of choice for professions that need to analyze and visualize massive amounts of data. First embraced by biologists and biomedical scientists as the preferred language and environment for statistical computing and graphics, R has spread into all corners of the Life Sciences Industry and is now being used by some big players.

There is good reason for companies dealing with Big Data to implement R. It is designed for today’s needs with an eye to the future, providing adaptability and a vast variety of statistical and graphical techniques. As the R website states, ‘The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.’

R is designed for today’s needs with an eye to the future, providing adaptability and a vast variety of statistical and graphical techniques.

While users usually refer to R as a statistics system, the company likes to call it “an environment within which statistical techniques are implemented.” They supply eight packages with which R can be easily extended to accommodate users’ wide range of needs. It appears that R is destined to be the new standard and it is wise for companies to move forward with what seems to be inevitable and think about training strategies for their staff.

Jason Milnes, Manager, Life Sciences at RStudio PBC, says, “Some of our clients have been working to proactively upskill their SAS programmers to include basic R programming skills, by developing a supplemental internal R training curriculum.” The series of training courses include an introduction to R Studio, an explanation of applications for how R can be best used in daily work, and SWIRL, an interactive learning environment for R and statistics. The R overview course is broken up into 16 half-hour sessions, which include a Lab portion with demonstrations and a Q&A.

At Navitas Data Sciences, we are pleased that we have implemented, with one of our long-term clients, an R training program for our programmers. As well, our leadership team is busy writing papers and providing a perspective from our data reporting function as reported in a most recent blog: R Programming in a Clinical Trial Data Analysis.

In a discussion last year with R Studio’s Director of Life Sciences & Healthcare, Phil Bowsher, he provided a great update on how his company is helping the Life Sciences Industry with R Programming. Having a background with SAS, Bowsher understands how and why Life Sciences is interested in using this open-source programming language, especially now that everyone is focused on Big Data. (Bowser co-chaired the second annual R/Pharma conference last August 21, 22, and 23, 2019 at Harvard University in Cambridge, Massachusetts – a clear indication that the industry is embracing the use of R.)

Over 20% of Navitas Data Sciences’ (NDS) programmers have at least some years of R Programming experience, and several NDS clients are Committee Members for the R/Programming Yearly Conference supporting the use and application of R Programming in Life Sciences. Yes, it would appear that the last decade’s predictions about R becoming the statistical language of the future is fast becoming a reality and by all accounts, the future is now.

We are providing some helpful links for those who would like to learn more about R:

You can find Phil Bowsher’s R Studio talks and workshops here: https://github.com/philbowsher?tab=repositories

Link to a white paper from PhUSE US Connect 2019 - How do I select an R package for my clinical workflow?
https://www.phusewiki.org/docs/2019%20US%20Connect%20Final%20Papers/TT/how-do-i-pick-an-r-package-for-my-clinical-workflow-bowsher-lopp-20454.pdf

Phil Bowsher recommends getting involved with the R in Pharma event, a participant-driven gathering to learn how others are managing their environments: http://rinpharma.com/https://github.com/rinpharma/2018_presentations

You can see NDA's that use R here:
https://www.accessdata.fda.gov/drugsatfda_docs/nda/2016/208573Orig1s000ClinPharmR.pdfhttps://www.accessdata.fda.gov/drugsatfda_docs/nda/2017/209296Orig1s000ClinPharmR.pdf

And the FDA presentation on R is here: http://washstat.org/presentations/20181024/Schuette.pdf

Information on specific R packages for design, monitoring, and analysis of data from clinical trials: https://cran.r-project.org/web/views/ClinicalTrials.html

A Guidance Document for the Use of R in Regulated Clinical Trial Environments: https://www.r-project.org/doc/R-FDA.pdf

Information regarding Docker is here:
https://blog.rstudio.com/2018/11/05/rstudio-rsp-1.2-features/https://support.rstudio.com/hc/en-us/articles/360019253393-Using-Docker-images-with-RStudio-Server-Pro-Launcher-and-Kuberneteshttps://docs.rstudio.com/rsp/integration/launcher-kubernetes/

RStudio is a free and open-source integrated development environment for R, a programming language for statistical computing and graphics. RStudio was founded by JJ Allaire, creator of the programming language ColdFusion.