Your team struggles to repeat experiments and generate consistent research insights, despite being necessary for regulatory compliance.
Establish a reproducible data science environment
Make sure your research and clinical trials produce consistent results for project validation. Allow your data science to be flexible and repeatable as requirements change.
Orchestrating the collaboration that is necessary between hundreds of data scientists when bringing a new drug to market is challenging when different tools and workflows are involved.
Support for multilingual data science teams
R or Python, it doesn't matter. Let your data scientists, researchers, and statisticians use the language that they prefer at every stage of the drug development cycle.
Serious scientific insights sometimes go to waste because of how difficult it is to share them with key stakeholders.
Share results frequently, effectively, and easily
Securely deploy dashboards, interactive applications, and automated reports at the push of a button, throughout the entire drug discovery, research, and development process.
"We are also using the enterprise version of RStudio. In case there is an FDA audit and we need to reproduce analysis, we can easily containerize simulations, deploy them internally, forget about them, and come back to them when necessary.”
- Satish Murthy, IT Manager Janssen R&D
"Adapting to the rapidly changing requirements of science requires collaborative software development across the enterprise, industry and field.”
- Michael Lawrence, Scientist, Genentech Research and Early Development
"Effective use of visualizations enables clear and impactful communication, elevates our influence without stakeholders, and facilitates informed decision making.”
- Mark Baille, Director of Statistical Methodology, Novartis
In this webinar, see how GSK enables R within a global department of over 600 Statisticians, Programmers and Data Scientists.
You'll learn about our tidyverse-centric training program, a future-ready Working Area for R Programming (WARP) environment, and a leading-edge R for Clinical Reporting (R4CR) initiative.
Topics we help our pharma customers with:
Validation, Reproducible workflows, FDA Compliance, using R & Python together.