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Statistical programming is evolving. Your SCE should too.

With Domino you get SAS, R, and Python in one governed workspace. GxP-compliant from day one.
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Read the GSK case study

What statistical programmers need from an SCE

Domino gives statistical programmers a single validated environment with 21 CFR Part 11 audit trails, full reproducibility, and GxP compliance built in, not configured on top. Built to work the way your organization works.

Reusable workspace

SAS, R, and Python — One governed workspace
Your statistical programmers work in the tools they know. Domino runs all of them in a single validated environment with consistent access controls, audit trails, and compliance across every language and job.

Reproducibility that holds up to inspection
Every execution snapshots the data version, code, compute environment, and outputs together. Any analysis, from last week or three years ago, can be reproduced exactly, with a complete audit trail ready for FDA review. No manual reconstruction before a submission.

Governed work environemt

GxP compliance built in, not bolted on
21 CFR Part 11 electronic signatures, immutable audit records, role-based access controls, and session-level traceability are built into the platform from the ground up. Exploratory and GxP work run side-by-side with separate controls automatically applied.

Exploratory and regulatory work in one environment
When your exploratory analysis lives on a separate platform from your regulated work, you're managing two systems, two validation cycles, and two sets of access controls. Domino runs both in a single environment, so your team works in one place and your organization maintains one validated system.

What Domino looks like for your team

For statistical programmers and biostatisticians

  • Automated QC workflows replace manual tracking; status, assignments, and audit evidence captured in Domino
  • Raw to SDTM to ADaM to TFL workflows with full lineage and audit trail at every step
  • Blinded and unblinded access controls managed at the project level, not manually toggled
  • Git-native version control with audit trails built in, no separate documentation required

For IT and infrastructure teams

The SCE running at the world's leading pharma companies

GSK unified two legacy SCEs into one

Pharmaceuticals and Vaccines now run in Domino for both GxP and non-GxP work with end-to-end traceability and reproducibility for regulatory submissions.

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Novartis is consolidating onto one platform

Ready to see what a modern SCE looks like?

See how GSK, Novartis, and UCB structured their SCE migrations and what the platform looks like for a team moving off a legacy environment.

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Who is Domino?

Domino Data Lab empowers the largest AI-driven enterprises to build and operate AI at scale. Domino’s Enterprise AI Platform provides an integrated experience encompassing model development, MLOps, collaboration, and governance. With Domino, global enterprises can develop better medicines, grow more productive crops, develop more competitive products, and more. Founded in 2013, Domino is backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors.

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  • Deploy in your VPC, on-prem, or Domino-hosted
  • Domino provides IQ/OQ documentation and infrastructure validation. You handle PQ. The split is defined from day one
  • Licensing is not compute-based, so you control and optimize your own cloud spend
  • Integrates with your existing clinical data infrastructure: CDRs, data lakes, and validation tooling

One environment for regulated submissions and exploratory work, managing 600+ trial outputs per study with standardized workflows and automated orchestration.

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UCB

UCB selected Domino to modernize its SCE

Standardizing statistical programming workflows and automating compliance across global regulatory requirements.

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The only SCE customer coalition in the industry

Leaders from top pharma meet to share implementation patterns, solve shared problems, and shape Domino's product roadmap together. No other SCE offers this.

What a legacy SCE costs your team

Statistical computing environments built around SAS in a controlled environment served the industry well, but the work has changed. R is no longer optional, open source is standard, and regulators are scrutinizing every analytical decision.

The hidden cost

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QC tracking is manual. Each step assigned individually, status tracked outside the platform.

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Your data and workflows are locked to the vendor's system and proprietary framework.

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Your exploratory and regulated work live on separate platforms with no connection between research and submission.

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The platform determines how your team works. Edge cases and exceptions mean workarounds, not solutions.

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Roadmap driven by vendor priorities. Customers have no visibility into what's coming or when.

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No roadmap for FDA AI/ML guidance as regulatory requirements for analytical models evolve.

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Package validation and environment reproducibility is manually managed.

How Domino is different

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Automated QC workflows built in. Status, assignments, and audit evidence automatically captured.

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Open architecture. Domino brings AI capabilities to your existing toolchain rather than replacing it. Your data, your tools, your process.

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One environment for exploratory and GxP work, so teams work in one place and your organization maintains one validated system.

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Domino adapts to how your organization works. No inherited constraints when your requirements don't fit the mold.

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Coalition meetings with statistical programming leaders from GSK, Novartis, UCB, and others. Customers shape the roadmap together.

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The same platform that runs your SDTM programs is built to govern production models. No re-platforming when regulatory requirements catch up.

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Containerized compute environments so every execution runs in a versioned, reproducible container. Package validation is systematic, not ad-hoc.

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