Data Science Platform
One Environment
Endless Possibilities
Faster reporting with a modern, compliant Statistical Computing Environment (SCE) tailored for small and mid-size Pharma and Biotech. Support analysis with SAS, R, Python, and future tools - modular, cloud-ready, and with GxP validation when required.
Lack of, or Outdated SCEs Slow Down Your Trials and Create Compliance Risks.
Every day without a modern SCE makes higher cost, compliance risk,
and slower drug development.
Your Full partner across research and development
Appsilon is helping pharma and biotech teams accelerate discovery, cut costs, and ensure compliance. We bring 12+ years of open-source leadership to deliver faster, auditable, and scalable analytics environments. With Appsilon you gain:
Empowers users to deliver more and faster
Multi-language, multi-tool ecosystem with build-in support for AI
Standardized workspaces across the organization
GxP compliant foundation
Higher research output volume with reduced time to insights
Increased automation to reduce repetitive tasks
Replace costly off-the-shelf systems achieving up to 7-digits costs savings
Access to competitive intelligence through our in depth industry footprint
Appsilon vs Traditional Vendors
with GenAI accelerators to speed up app creation
Statistical Programmers:
Generate TLFs faster, validated R submissions.
Data Science Teams:
Use Modern Tools. Explore with multiple languages, submit in R.
Clinical Operations:
Streamline clinical trial tasks from preprocessing to reporting for faster, error-free results.
IT & Governance:
Secure, scalable, reproducible infra; no hidden “shadow systems.”; Fast change management with IaC
Unlocking $930K Annual Savings with a Future-Proof Data Analytics Platform
Read how Appsilon helped a top 50 pharmaceutical company design a custom system for analytics in R and Python, saving the client $930,000 annually.
The Anatomy of Modern Statistical Computing Environments in Pharma
Learn how pharma companies are building validated, flexible platforms to support both regulatory submissions and modern analytics.
From Blueprint to Validated Production
in Weeks
Discovery & Design
Assess current workflows, compliance needs, future goals
Deployment
Modular, cloud-native environment with Posit, Domino, or hybrid stacks
OPTIONAL
Validation & Documentation
GxP-compliant validation packs and SOPs
Support & Scale
Long-term managed services, user training, iterative upgrades
Compliance Without Complexity
Appsilon provides audit-ready environments aligned with FDA 21 CFR Part 11 /
EU Annex 11 and GxP and our R package validation is delivered in partnership with the R Validation Hub.
The R Validation Hub, co-created with pharma, regulators, and academia, provides the guidance and tools that enable pharmaceutical organizations to validate and use R packages in full compliance with regulatory standards.
With Appsilon you get:
- Validation powered by the industry-standard RValHub
- Risk-based approach that reduces validation time and cost
- Reproducible, audit-ready packages for regulatory submissions
- Access to partner network (e.g. Era Sciences - Compliance Partner)
Andrea Nicolaysen Carlsson
Technology Manager Electrodes at Elkem ASA
Director
at Top10 Pharma Company
Director
at Top5 Pharma Company
Our Expertise, Your Advantage
Our team masters leading technologies, ensuring every project is built with reliability, scalability, and performance in mind.
Let’s Build Your Data Science Environment
FAQs About SCE
Answers to the most common questions about data platforms, cloud solutions, and infrastructure best practices.
Why Is Data Governance Critical for Enterprise Success?
Data governance ensures data quality, security, and regulatory compliance, enabling organizations to make accurate decisions and maintain trust in their data assets.
What Is Infrastructure as Code (IaC)?
Infrastructure as Code is the process of managing and provisioning IT infrastructure using code instead of manual configuration. It allows for automation, version control, and scalability, ensuring consistent and repeatable infrastructure setups.
How Can I Optimize Costs in Data Science Projects?
Cost optimization involves right-sizing your infrastructure, using cloud cost-management tools, automating workflows, and leveraging serverless or spot instances to reduce idle resource usage and improve efficiency.
What Is a Scientific Computing Environment (SCE) and Why Is It Important?
A Scientific Computing Environment (SCE) is a specialized infrastructure for managing complex data analysis and modeling, particularly in data-intensive industries like life sciences and pharma.
How Can CI/CD Pipelines Enhance Data Project Efficiency?
CI/CD pipelines automate code integration and deployment, reducing manual errors, improving delivery speed, and ensuring consistent updates for data-driven applications.
What Is Data Orchestration, and How Does It Benefit Enterprises?
Data orchestration automates the movement and transformation of data across systems, improving accessibility, consistency, and readiness for analytics.