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We optimize analytics data workflows, help adopt data standards, automate regulatory deliverables, and migrate you to validated open-source solutions or help you adopt a multilanguage setup while automating the most time-intensive parts of your process.
From operational speed to strategic positioning, our automation and migration work delivers impact at every level of your organization.
We eliminate repetitive manual work. Submission dossier creation for ICH eCTD modules, including Clinical Summary and Study Reports built on SDTM/ADaM datasets, becomes streamlined.
Open-source solutions deliver significant cost reduction while eliminating vendor lock-in. Standardizing now lays the foundation for AI-driven analytics tomorrow.
Modern open-source tooling attracts the next generation of data scientists. Your existing team stays engaged because the expertise is transferable and career-building.
A global pharmaceutical company reduced a 40GB submission dataset export from an overnight run to about 20 minutes, making delivery timelines more predictable for submission teams.

From R/Python ecosystem work to AI-driven TLF generation, we cover the entire analytics modernization lifecycle.
Package development, testing, documentation, open-releasing and validation across your analytics ecosystem.
Best engineering practices applied to existing fragmented workflows and analytics infrastructure.
Working with CDISC datasets, generating metadata, and implementing analysis results standards.
Leverage AI for automated Tables, Listings, and Figures generation from standardized data.
End-to-end support for submission dossier creation aligned with ICH eCTD requirements.
We bring ecosystem access, regulatory experience, and elite talent that compounds your capabilities.
We sit on the pharmaverse council, develop core packages, and contribute to the ecosystem. You gain access to our deep connections and collaborative innovation.
Partnered with Eli Lilly and R Consortium on pilot FDA submissions. We know what regulators expect and how to deliver it with open-source tooling.
We've helped 8 of the top 10 pharma companies modernize their analytics workflows. We understand the regulatory constraints, organizational dynamics, and technical debt you're working with.
Appsilon engineers serve as core contributors to the {teal} framework, sponsored by Roche. Our team shapes the tools your teams rely on.
From operational speed to strategic positioning, our automation and migration work delivers impact at every level of your organization.
Audit your SAS codebase, map regulatory workflows, identify automation opportunities, and define the pilot scope — typically one study's TLF pipeline.
Set up validated R/Python environment, implement CDISC data standards, establish Git workflows, and validate priority packages with Axon.R.
Automate TLF generation, migrate the pilot workflows to open source, run QC in parallel with SAS, and deliver the first R-based outputs.
Expand to additional studies and teams. New studies launch on R/Python, SAS licenses phase out naturally. AI-driven analytics become possible.







Data Engineering Lead
Top 10 Pharma Company
Associate Director
Top 50 Pharma Company
Human Resources People Partner
Top 10 Pharma Company
Learn how pharma companies are building validated, flexible platforms to support both regulatory submissions and modern analytics.

Find clear answers to common questions about GxP compliance, helping you navigate regulations with confidence.
A focused pilot — migrating a single study's TLF pipeline — typically takes 8-12 weeks. Full-scale enterprise migrations are phased over 6-18 months, running parallel to existing SAS workflows to ensure zero disruption.
Yes. The FDA accepts submissions using R. Major pharma companies have completed real-world R-based NDAs to the FDA, EMA, and NMPA using Pharmaverse packages. Proper validation is key — which is what Axon.R provides.
We never recommend a hard cutover. Migrations run in parallel — SAS stays fully operational while we build and validate the open-source equivalent. Teams transition gradually, often starting new studies on R/Python.
We're core contributors to the tools the industry uses. Our engineers build key pharmaverse packages, contribute to {teal}, and sit on the pharmaverse council. You work with the people who shape the ecosystem.
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.