Using R in the pharmaceutical industry

March 27,2019

(This article was first published on R – Paolo Eusebi,and kindly contributed to 188bet appR-bloggers)

Although SAS is the main player in the pharmaceutical industry,R is gaining popularity.In this post I will just mention some initiatives,documents and podcast episodes dealing with using R in pharmaceutical research and development programs.

Recently,it was a pleasure to listenthe episode of the Effective Statisticianpodcast 金宝搏网址about the rise of R and the role played in it by theApplication and Implementation of Methodologies in Statistics (AIMS)group within theasociation of
Statisticians in the Pharmaceutical Industry (PSI)

I think that it is worth to mention once again that FDA has clearly affirmed in theStatistical Software Clarifying Statement(6 May 2015) that it is not required the "use of any specific software for statistical analyses,and statistical".However,the software used for statistical analyses "should be fully documented in the submission,including version and build identification".

The main objectives of the AIMS group 金宝搏网址about R in pharma are educating statisticians and statistical programmers and validating and documenting R.The R validation project documentation is stored on a dedicatedGitHub repository.

The second annual R/Pharma conference will take place this year in August at Harvard University.The call for papers give an idea of the opportunities and challenges of the use of R in pharma: reproducible research,regulatory compliance and validation,safety monitoring,clinical trials,drug discovery,research & development,PK/PD/pharmacometrics,genomics,diagnostics,immunogenicity.

A useful resource,dense of suggestions and ideas,is adocument issued by Adrian Olszewski.

Cytel provided in ablog posta list of clear pros of R compared to SAS: ability to create effective visualisations;flexibility to combine with other tools;quick release of cutting edge methods;naturality of being a suport for collaboration and therefore innovation,as open source tool.

In conclusion,the rise of R in pharma is a fact and a lot of initiatives are in place.However,this rise is slow and mostly limited to visualization and machine learning applications,due to the position gained by SAS as validated standard in the industry.

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