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SCE That Scales With Your Needs
Run More Trials Without Adding Risk
More trials, same controls. We design, build and validate your statistical computing environment in your cloud: validated R and Python packages reach statisticians in days, historical SAS still runs, and the GxP work is carried for you.
#Why Now
Outgrown Your SAS Environment? Build the Next One Right.
A Submission Date Is Set
A filing or a pivotal readout within 24 months, and the environment that has to carry it was last updated years ago, with a long IT queue in front of every change. This is the trigger behind every full-environment engagement we have signed.
The In-House Platform Reached End of Life
Five global sponsors presented the replacement or refactoring of a home-grown SCE at PHUSE between 2022 and 2026. Their words: outdated technology, retiring engineers, a shortage of skilled people, and extensive revalidation for every enhancement. At mid-size the same story reads: we have outgrown our SAS environment, and there is no quick fix.
The third reason is sourcing. Biometrics runs on a CRO's or a vendor's environment and licences, nobody can independently verify when a QC report was actually run, and every insourcing or outsourcing decision is constrained by whose environment the study lives in. If one of these three is yours, the timing is now.
Book a Scoping Call
#What You Get Back
Your Trials Are Growing. Your Environment Should Keep Up.
SPEED
More Studies, Same Team
New packages are assessed against a written risk procedure and released on a cadence your studies can plan around, instead of behind a six-to-nine-month queue. Statisticians stop waiting and stop working around the environment, which is what lets a growing programme add trials without adding a queue.
COMPLIANCE
Validation Built In, Not Bolted On
Evidence is produced as the environment runs, not assembled before every audit. A new package or a rebuilt container does not wait for a validation cycle, and your QA gets records they can verify and rerun.
OWNERSHIP
You Own It
Built in your AWS or Azure, on your identity and storage, with the code, the data and the infrastructure yours. It stays yours if we leave.
IT CAPACITY
IT Is Not Left Holding It
We integrate with what you run rather than replace it, and we can operate the environment for you: package assessment, validation refreshes, upgrades and L2/L3 support. Your platform team keeps its roadmap.
CONTINUITY
Historical SAS Still Runs
R, Python and SAS side by side, on SAS or on Altair SLC, so an auditor's request to rerun a historical analysis is answered from the same environment as today's work.
HEADROOM
AI Inside the Validated Boundary, Later
The environment is designed so that AI-assisted programming workflows can run inside the validated boundary when you are ready, with traceability and Part 11 intact, without re-platforming. Our thinking on that is in the AI-ready SCE ebook below.
#Why Appsilon
Built by People Who Have Done This Before
Appsilon works with 8 of the top 10 pharma companies, has built open-source tools for life sciences since 2013, contributes to pharmaverse and is a Posit Certified Partner. The people on your calls are the engineers who design, build and validate these environments, not a sales team with a template.
Audit-Ready
A pre-commercial biotech went from fully CRO-dependent to an owned GxP environment supporting its BLA programme, built in six months in a greenfield context and presented at PHUSE US Connect 2026.
#How We Work With You
Start With the Piece That Hurts
1. Discover
Three days on site with our senior SCE architects and the compliance point of view in the room. A fixed-price workshop. If you have already mapped your workflows and defined the components, we start from your map and turn it into an integration architecture and an evaluation scorecard.
You leave with:
The target design of your environment
The storage decision, settled
A validation strategy your QA helped write
A costed, fundable first increment
2. Build and Qualify
Deployed in your cloud with infrastructure as code, integrated with the data sources, identity, Posit, SAS or Altair tooling you already run.
Includes:
R, Python and SAS from day one
Validation documentation your QA needs to release it
Integrate, not replace: your AWS or Azure, your identity, your storage
Phased rollout with early-adopter studies
3. Run and Keep It Current
We operate the environment for you, with the SOPs, work instructions, controlled templates and training that let your people run it. Or hand it to your platform team with the runbooks and stay on call.
Includes:
Package assessment on a published cadence
Validation refreshes when components change
Monitoring, upgrades and L2/L3 support
Cost and consumption you can see
#How Sponsors Test an SCE
Judge Us the Way Sponsors Judge an SCE
In 2026 a top-ten pharma company published the ten categories it tested in a four-week proof of concept before replacing its in-house SCE: 70 requirements, 33 of them critical, scored by 30 programmers and statisticians. Here is how we answer them. Mid-size biotechs now run the same process: written requirements, a formal RFP, a pilot with a short list of two. Bring your own list and we will score against it.
Control and Evidence
Security and access control, including inspection support: your identity provider, role-based access, exportable audit trails
Lineage, versioning and reproducibility: Git, locked package environments, container digests and run logs
Backup, restore and archive: infrastructure as code and versioned storage, rebuildable on demand
Data and Integration
Data ingestion across sources and formats: landing zones for CRO deliveries, SDTM and ADaM pipelines, parquet next to XPT
Integration upstream and downstream: CRO and vendor data exchange, your clinical data repository (Databricks included), EDC exports, metadata and standards tooling, Pinnacle 21, TLF review tools, publishing flow and version control
Dashboarding: review apps and metrics served from inside the validated boundary
Scale and Languages
Language-agnostic: R, Python and SAS side by side, Altair SLC where SAS code must keep running, and Clinical Pharmacology tooling such as NONMEM, PsN, Monolix, Phoenix and SimCyp inside the same qualified boundary
Job scheduling and dynamic compute for database locks and interim analyses
User experience, performance and scalability: judged by the programmer's day. A choice of IDE, R and SAS in one workbench, project templates, job submission without a ticket, environments that reproduce without effort, sized for database lock rather than average load
#How We Helped Our Partners
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.
#Valued by clients worldwide
Engineers Who Have Built and Qualified These Environments
Senior SCE Architect
Designs the target state with your team and challenges the assumptions under it, including ours.
Platform Engineers
Kubernetes, infrastructure as code, identity, storage and networking, in your cloud.
Validation and Compliance Specialists
Package risk assessment, environment qualification and documented evidence for your QA and CSV owners.
Statistical Programmers
SDTM, ADaM and TLF work in R and Python, so the environment is shaped by people who use one like it every day.
Ebook for Clinical Data & Platform Leaders
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.
#Contact Form
Consult with Our Experts for Custom Solutions
Get in touch
with Appsilon Experts
with Appsilon Experts
We will contact you within 24 hours!
Our Clients About Appsilon
How It Feels to Work with Us
We rely on Appsilon's expertise to support the build and maintenance of critical clinical reporting software based in R and Shiny.
Data Engineering Lead
Top 10 Pharma Company
Appsilon team is exceptional. The engineers challenge and speak their minds, which helps do justice to the product
Associate Director
Top 50 Pharma Company
We wouldn’t be here where we are now without Appsilon. I want this partnership to keep going and growing.
Human Resources People Partner
Top 10 Pharma Company
#Before You Book a Call
Questions We Get Asked
We could build this ourselves. Why involve you?
Most platform teams can build the infrastructure. What they tell us they cannot carry is the validation and the revalidation every time a component changes, and the platform-engineering bench to keep it that way. So the usual answer is neither build nor buy: you choose the components, we design, build and validate the integration in your cloud, and you own the result.
Do we have to replace Posit, SAS or our cloud?
No. We integrate with the AWS or Azure account, identity provider, storage, Posit and SAS or Altair licences you already have, and with the systems around the environment: CRO data exchange, your clinical data repository, Pinnacle 21, TLF review tools and your version control. Rip-and-replace is how these programmes stall.
Does our historical SAS still run?
Yes. SAS code continues to execute in the environment, on SAS or on Altair SLC, so an auditor's request to rerun a historical analysis is answered from the same place. If a SAS performance fix cannot wait for the SCE, we design it so it lands inside the target environment instead of becoming a second migration.
How do new R and Python packages get in?
Through a written, risk-based assessment: purpose, maintenance practice, community usage and test coverage, with the evidence filed. Packages are released on a published cadence, and study teams can request an out-of-cycle assessment against a submission timeline.
What does it cost?
The discovery workshop is a fixed price. The build is scoped from the workshop's roadmap and costed increment by increment, with architecture and programme management as their own lines rather than buried in a day rate. Operations are an annual agreement sized to your environment. You get a ballpark for all three on the first call, so procurement is not the last surprise.
Is this only for large pharma?
No. The full-environment engagements we have signed were with pre-commercial biotechs approaching a first submission, with biometrics teams of five to fifteen people and thin IT. That is where managed delivery matters most. Mid-size biotechs scaling their trial count run a formal selection, with written requirements and a pilot, and we take part in those on the buyer's own scorecard.
Our Clinical Pharmacology team runs NONMEM, Monolix and Phoenix. Does that belong in the same environment?
It can. Pharmacometrics tooling is regulated software with the same qualification needs as the programming environment, and the same case for one audit trail. We scope it as its own increment, with the previously validated tools migrated first.
What does a programmer's day look like?
Open a project template, pull the study data from the repository, work in RStudio, VS Code or SAS in the same workbench, submit a long job without a ticket, and commit to version control with the environment pinned. The evidence for the audit is produced by working, not by a second pass.
Knowledge Base
Insights, Inspiration & Distilled Knowledge
Video
Where Technology Meets Science
Where Science Meets Technology by Appsilon is a series of interviews and discussions focused on how technology can accelerate data science processes, particularly within life sciences and biopharmaceutical companies.
Explore our Blogposts
Check our Blog
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Drive Impact with Appsilon
From custom dashboards and applications to AI-powered solutions and compliant computing environments, our engineers and infrastructure architects accelerate clinical development within fully validated, regulatory-compliant frameworks.