New: 2026 edition with chapters on validation and AI

The AI-Ready SCE: A Pharma Guide to Building Modern Environments

Learn how pharma companies are building modular SCEs that support validated submissions and AI workloads on the same architecture.

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astellas
Genmab
merck
johnson and johnson
World Health Organisation
Kenvue
Phuse
Pharmaverse
astellas
Genmab
merck
johnson and johnson
World Health Organisation
Kenvue
Phuse
Pharmaverse
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What’s Inside

Everything That Changed Since Last Year, and How to Keep Up

Learn how to modernize your SCE to handle validated submissions and AI workloads and discover what's working at leading pharma companies.

What Makes a Modern SCE

The five layers of a modern SCE: infrastructure, data, platform, process, compliance; and why a system that supports submissions on Monday and exploratory ML on Tuesday is now a competitive baseline, not a stretch goal.

Risk-Based Validation (New Chapter)

Why validation is a system property, not a periodic event. A practical framework for validating R and Python packages, container images, and platform changes continuously, so a CRAN release becomes a routine operation, not a quarterly project.

AI Inside the Compliance Boundary (New Chapter)

The three categories of AI workload in pharma today: GenAI assistants, validated ML pipelines, and AI agents in regulated processes combined with the engineering foundation that determines whether you can deploy them cheaply or not at all.

Implementation Strategy & Leader Case Studies

Build vs. buy vs. partner — what actually works at different organization sizes. Plus real examples: Novo Nordisk's open-source migration, a top 50 pharma saving $930K annually, and a clinical-stage biotech going from zero to operational regulated work in six months.

Who Should Download This

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Statistical Programming Leaders

VPs and Directors of Statistical Programming, Biostatistics, and Clinical Data Science evaluating what a modern SCE needs to support for submission work and the exploratory and AI work happening alongside it.

Pharma IT & Platform Engineering Leads

Platform, infrastructure, and IT leaders scoping their next SCE investment and looking for a framework that handles validation, change management, and AI workloads on the same architecture.

Regulatory & Quality Experts

QA and regulatory leads who need to understand how continuous validation, risk-based package management, and AI inside the compliance boundary actually work in audit-ready environments.

Expert Insights

Stay Informed with GxP Compliance Tips and Trends

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What Cloud-Native Means for Your Statistical Computing Environment (and Why it Matters)
What Cloud-Native Means for Your Statistical Computing Environment (and Why it Matters)
Containers, IaC, CI/CD, Kubernetes — what these mean for a pharma SCE, why they matter for compliance, and the questions to ask your technical partner.
Rafael Pereira
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When to Modernize Your SCE: Build Now or Wait for Cloud Migration
When to Modernize Your SCE: Build Now or Wait for Cloud Migration
On-prem or cloud for your pharma SCE? Build cloud-native now - even on-premise - so a future migration is incremental, not a full rewrite.
Rafael Pereira
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R vs Python vs SAS in a Modern SCE
R vs Python vs SAS in a Modern SCE
Where R, Python, and SAS each fit in a modern pharma SCE, and why the AI era turns this from a language choice into an architecture decision.
Rafael Pereira
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Services

Check our Services

Rigplay Case Study

Statistical Computing Environments (SCE)

GxP-ready platforms for modern analytics
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Shiny Dashboards

Advanced Data Visualizations

Transform complex data into actionable insights
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RNS-Ligand Binding

R package validation

Axon.R – a GxP-aligned, audit-ready R package validation
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RNS-Ligand Binding

Migration to Open Source

Our automation and migration work delivers impact at every level.
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Ebook for Directors in Clinical Trials

Get Your Copy Today

Explore how open-source technology – particularly R and Shiny is transforming clinical trials and the broader pharmaceutical industry.

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