Pharma and biotech
R and SAS together, apart or integrated, in a GxP qualified SCE with IQ, OQ and PQ.
Enterprise Open Source for Regulated Environments
Professional, enterprise statistical computing environments. GxP ready from the experts.
We help pharma companies, CROs and government departments move from SAS to open source and adopt AI with confidence, with validated packages, controlled environments and teams trained to run them.
Partners We Trust
Who We Work With
Every regulated team needs the same things from open source: code they can trust, a controlled place to run it and evidence an auditor will accept. What changes is the language.
Contract research organisations
Validated packages and reproducible environments for every sponsor's needs.
Government and public sector
Secure, auditable environments with no vendor lock-in, via G-Cloud and DOS7.
Trusted By
What We Deliver
We deliver implementation and full life-cycle management of your GxP environment, ready for successful regulatory submission and for AI, and built to suit your company.
GxP qualified SCE
A statistical computing environment on Posit, qualified for GxP use, with AI governed and controlled.
Certified Posit implementation
Designed and qualified for your user and output specification.
R package risk assessments
Qualified risk assessments for the R packages your team uses.
Adoption and training
Training in R, machine learning and AI, so your teams achieve their desired outputs.
GxP assurance
Dashboards, models and workflows assessed and documented for GxP use.
Life-cycle management
Maintained with a GxP qualified life-cycle management plan.
Our Products
Coadun
AI-ready statistical computing for pharma.
- SAS, R, Python and Posit, validated together
- Auditable AI-assisted workflows
- In collaboration with Achieve Intelligence
Litmus
Risk assess the R packages your team relies on.
- Code, documentation and maintenance scored
- Reports for your validation SOPs
- CRAN, Bioconductor and internal packages
Diffify
See what changes before you upgrade your SCE.
- Dependency and version changes
- Updates reviewed before they reach your validated environment
- Ask your AI assistant, via the Diffify MCP server
Could Your Team Answer These Today?
If some of these are still open questions, we can help you work through them.
Talk to us- Where should open source be introduced first? Which workflows are good candidates, and which should stay on SAS or other tools?
- What needs to be validated? Which packages, functions and environments fall within your quality requirements?
- How will package risk be assessed? Do you have a defined approach for deciding what is suitable for use?
- What evidence will your quality or audit team need? Qualification, testing, documentation and audit requirements, before deployment.
- How will adoption be supported? Who will train users, maintain the environment and support teams as usage grows?
Why Jumping Rivers?
Our expert teams have skills that span from the start to the finish of statistical programming, AI and reporting.
- 4+ years of validating R packages in large pharma.
- Posit Premier Partner. As one of the longest-standing Posit partners, we offer the ultimate in design, maintenance and support for successful enterprise GxP systems.
- Leading in secure infrastructure to validated open-source innovations. We understand the analysis your programmers run and the infrastructure behind it.
- Certified. ISO 9001, ISO 27001 and Cyber Essentials Plus. Accredited Living Wage Employer.
Take a Look for Yourself
Public Health Scotland: Support for scientific SPSS functions transitioning to R
Read online: Public Health Scotland case study Download: Public Health Scotland case study
Francis Crick Institute: Training 500+ Researchers in R and Python
Read online: The Francis Crick Institute case study Download: The Francis Crick Institute case studyGet Your Team Ready
Our trainers are practising data scientists. From your first steps in R to building with AI, every course can run privately, on-site or online, with examples from your own domain.
View course catalogue- Why Use R?An overview for teams weighing up open source alongside SAS.
- Introduction to RImport, wrangle and plot data with the tidyverse.
- Posit WorkbenchGet the most from your team's shared development environment.
- Package Management with PPMControl which package versions your organisation uses.
- LLM-Driven Applications with R and PythonBuild applications on large language models, including retrieval-augmented generation.
From Our Blog
Read more on our blog
Why R, and where the budget goes
Planning a move from SAS to R? Find out why R stands up to regulators, where the cost and risk of a migration come from, and the four things to settle before you convert a line of code.
R Package Quality: Validation and beyond!
Not all R packages are clearly “good” or “risky”, most fall somewhere in between. This post introduces a scoring framework to help users assess package quality, based on documentation, code, maintenance, and popularity. We also share key principles to ensure the scores are useful, fair, and adaptable to different contexts.
Validating Shiny Apps in Regulated Environments
In regulated industries, Shiny apps must be reliable, reproducible, and well-documented. Validation builds trust, supports compliance, and prevents costly delays. Learn how to avoid common pitfalls and set up a lightweight, effective validation approach that scales with your needs. Validation isn’t a blocker, it’s a long-term advantage for you and your team.
Let's Talk About Your Move to Open Source
Whether you are exploring your first R use case, migrating a body of SAS code or planning a validated environment, we'll help you decide the right first step.