The client’s clinical data team spent significant time preparing FDA submission packages. Two scientists had to create analysis datasets and regulatory files (like define.xml and ARM) by hand across several tools. The work was slow and error-prone, often leading to validation failures. These failures caused delays, compliance risks, and inconsistent results across studies. The company wanted to improve standardization, reduce manual work, and deliver regulatory packages faster and more reliably at scale.
Our team worked on a custom R-based ADaM submission toolkit, speeding up metadata preparation across clinical studies.
Key innovations included automated generation of define.xml (v2.0 & v2.1), ADaM datasets, and ARM from structured Excel/YAML inputs. We built in validation with Pinnacle21 CLI, ensured outputs met FDA rules, and aligned the toolkit with the client’s internal systems.
Our modular toolkit enabled easy scaling and adoption across multiple teams.
This initiative set the foundation for scalable metadata automation aligned with CDISC and FDA standards and global regulatory expectations.
- Reduced metadata delivery time from 3 days to under 30 minutes
- Accelerated onboarding by 10× across 100+ users
- Boosted validation accuracy, minimizing rework cycles
- Enabled near real-time submission readiness in live studies
- Improved export speeds by up to 80% for large datasets (40GB+)
From advanced analytics to platform development and pharma consulting, we craft solutions tailored to your needs.