The future of pharma is open source
An industry-wide shift across every organization
For new talent
Data scientists graduating today expect languages like R and Python to be the backbone of tools used in clinical trials.
Leaders responsible for driving innovation across project portfolios and bringing therapeutics to patients faster are training their workforces on open-source tools.
Regulators like the FDA are embracing the possibility of freeing the evidence of analysis of beneficial drugs from being locked behind proprietary tools.
“We cannot influence whether or not a study reads out positively in the end. But if it does, that basically means it's time for that submission, which uses R and Open Source as its backbone, to get submitted to the Health Authority. And actually, there's one Phase Three trial we have in Oncology which is already on the R platform.”
Senior Data Scientist at Roche
Open source is driving clinical trials forward
Open source makes innovation the standard at every go/no-go checkpoint, shortening the feedback loop on decisions in clinical trials by months. Use Shiny applications to analyze clinical trial data in interactive ways. Feed dashboards that display the status of trials in real-time. Leverage packages designed specifically for pharma to streamline clinical workflows. Open source gets you from thousands of compounds to one leading molecule faster than ever.
Every clinical trial produces hundreds of outputs. Pharmaceutical companies are partnering to build and use packages that help programmers automate this process. Open source can get you to SDTM/ADaM datasets quicker. And once you have SDTM/ADaM datasets, use open source for better validation and quality control.
Open source can and should be used in regulatory submissions. Leading pharmaceutical companies are collaborating with regulatory agencies like the FDA more than ever before, providing guidance and obtaining feedback on how to use open source should be used for submissions. Only open source provides the FDA with complete transparency and reproducibility for clinical trial results, two things that uphold the integrity of great science.
"There are multiple drivers behind our shift to open-source languages and tools. Data Scientists graduating today expect R and Python to be the backbone of our tools, and our internal experienced data scientists realize and are excited by the new tools and innovations available from this shift."
Senior Director of Insights Engineering, Roche
"I think the possibility now with open source and particularly something like R, where you've got a tool like Shiny, is you can start to deliver that submission in a different way. I think we'll be sharing the data directly with the regulators in the future, we'll be worried less about how we format that and get it to look really nice on a piece of paper."
Senior Director, Head of Statistical Data Sciences at GSK
Big pharma, innovating with open source
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"Experiential learnings is key to generating the motivation needed to develop our Data Scientists, and RStudio Academy has been a great ally in this journey."
Director of Data Science Learning and Development, AstraZeneca
Posit products allow us to deploy R more easily, get started quicker, have confidence that the tools and packages we’re using are accessible and reproducible in the long term, and that we can develop and deploy modern data science products within our company, allowing us to concentrate on better science, faster decision making and getting our medicines to patients more quickly.
Senior Director of Statistics, Pfizer