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Cloud-native Statistical Computing Environment in use by clinical researcher on tablet and laptop.

Cloud-native Statistical Computing Environment at Boehringer Ingelheim

Scalable and compliant environment for statistical computing in pharmaceutical studies
Project Overview
Industry:
Pharmaceutical and healthcare industry
Customer:
Global pharmaceutical company
Highlights
  • Replacement of a 25-year-old, business-critical SAS system with a modern cloud-native platform
  • Integrated development environment with SAS Studio and R Studio
  • Automated validation supporting continuous compliance and release cycles
Technology stack
  • Angular
  • AWS
  • CI/CD pipeline
  • Git
  • OpenDevStack
  • Posit Workbench
  • R
  • rmarkdown
  • SAS Studio
  • SAS Viya
  • testthat
  • VCA
We implemented a scalable cloud platform for clinical data analysis – enabling secure and validated processes for every release.
Portrait of Dr. Christoph Frank, Project Manager at HMS
Dr. Christoph Frank
Project Manager at HMS
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In pharmaceutical research, statistical analysis of clinical trial data is essential – particularly given the high regulatory requirements regarding data security and result consistency.
There was a clear need for a solution that offered role-based access combined with context-aware, accurate answers.

Boehringer Ingelheim had been using a central, SAS-based system with a proprietary interface for over 25 years. This system was business-critical but technologically outdated, lacking the scalability and flexibility to meet future demands.

The HMS solution: Cloud-native SCE for clinical trials

HMS implemented a fully integrated, cloud-native Statistical Computing Environment (SCE) that replicated key functions of the legacy system while introducing modern usability enhancements. The solution is built for scalability, user-friendliness, and regulatory compliance.

Architecture and integration

The cloud-native architecture leverages an AWS backend, integrating the SCE web app with SAS Viya and SAS Studio as IDE as well as Posit Workbench with RStudio as IDE:
SAS Viya for executing parameterized processes and batch analyses
SAS Studio and Posit Workbench (RStudio) as interactive IDEs
Optional integration with further tools such as Python-based environments
The cloud-native architecture is tailored to the client’s requirements and supports secure, validated workflows.

Validation and automation

To meet regulatory demands, HMS implemented a highly automated validation strategy that ensures:
Reproducibility of analytical processes
Automated testing using R/testthat and rmarkdown
CI/CD integration for compliant deployment and documentation
Controlled release cycles through VCA-compliant pipelines

Development approach

Facilitating the OpenDevStack Framework, HMS enabled a compliant application lifecycle for building, deploying, testing, documenting, releasing and running applications. Agile project phases ensured iterative delivery aligned with user expectations and validation standards.
The solution now enables secure, scalable, and regulation-ready data workflows across the clinical analytics lifecycle.

Learn more

This project was presented at PHUSE EU Connect 2024. Visit our event page to download the full presentation and paper of the talk "Development of a Customised Statistical Computing Environment for Clinical Trial Data Analysis".
Access presentation and paper

Business value through regulatory-grade automation

The implemented SCE delivers measurable benefits for clinical data processing:
Cloud-native setup with high data security and role-based access control
Seamless integration of multiple IDEs tailored to users’ daily work
Automated validation reduces manual effort and error risks
Scalable infrastructure supporting future growth and tool expansion
Fully documented, compliant application lifecycle from development to release
This modern platform supports long-term digital transformation in clinical trial analytics.

Our strengths, your advantage –
End-to-end SCE for pharma

HMS delivered a fully integrated Statistical Computing Environment tailored to the specific needs of clinical research teams.
End-to-end architecture
From development to deployment – tailored for regulated environments in clinical research.
Deep IDE integration
SAS Studio and R Studio embedded for seamless use by statistical programmers.
Validation & compliance by design
Automated pipelines, RBAC and VCA conformity ensure audit readiness and regulatory fit.
Transform your statistical computing with HMS – let’s talk.
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Cloud-native Statistical Computing Environment in use by clinical researcher on tablet and laptop.

Cloud-native Statistical Computing Environment at Boehringer Ingelheim

Life Science / Pharma

HMS replaced a 25-year-old central SAS-based system with a modern, cloud-native Statistical Computing Environment (SCE) for analyzing clinical studies for Germany's largest pharmaceutical company.

Benefits:

  • Integration of the SCE web app with SAS Studio under SAS Viya for seamless workflows
  • System design with AWS services for optimal data security and access
  • Automated validation strategy to simplify regular release deployments
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