Automated and Controlled Clinical Data Analysis
Client: Global Pharmaceutical Company
Overview
We partnered with a top-tier global pharmaceutical client to design, build, and deploy a cloud-based platform to accelerate clinical data analysis. The initiative addressed two core objectives: reducing conversion time from unprocessed clinical data to submission-ready assets while preserving and strengthening data integrity, and minimizing reliance on on-premises infrastructure by aligning with the organization’s cloud migration strategy.
Solution
The platform comprises multiple web applications and microservices deployed on Microsoft Azure Kubernetes Service. Key technical components include:
- Polyglot Analysis Support: Execution of analyses in R, Python, SAS, and containerizable tools
- Kubernetes-Native Engine: Integrated with Domino Data Science platform for controlled analysis execution
- Configurable Processing Graphs: Adaptable workflows matching evolving business and regulatory requirements
- Complete Audit Trail: Full processing documentation demonstrating data integrity and control per GxP and ALCOA+ guidelines
Project Scope
This was a multi-year, multi-vendor program replacing legacy software that we had maintained and enhanced for almost 20 years. Delivered using the SAFe agile framework across multiple product increments, we architected, delivered, and integrated multiple bespoke and packaged software titles over the course of the four-year engagement.