USDM Designs AWS Data Lake to Standardize GxP Data Management Processes

Context and Challenge 

A global biotechnology firm specializing in antibody therapeutics for cancer faced operational inefficiencies and heightened risks related to data governance, compliance, and security. With over 1,000 employees and operations across four global offices, the organization struggled with: 

1. Data Governance: Inconsistent practices in managing clinical trial and biomarker data. 

1. Compliance Pressures: Risks from audits related to GxP (Good Automated Manufacturing Practices) and GDPR (General Data Protection Regulation) standards. 

1. Data Accessibility: Challenges in democratizing data for effective analytics and decision-making. 

1. Operational Costs: Rising expenses linked to managing fragmented data storage solutions.

Solution 

The company engaged USDM to streamline its data management. USDM implemented a GxP and GDPR-compliant data lake on AWS, designed to centralize and secure all structured and unstructured data. 

Key features of the solution included: 

• AWS S3 and Data Lake Implementation: Centralized data storage for scalability and accessibility. 

• Data Security Enhancements: Architecture improvements embedding data integrity and security. 

• Data Democratization: Tools enabling self-service analytics and broader access to critical datasets. 

In addition, USDM’s design leveraged AWS-managed services such as Elastic MapReduce (EMR) and S3 lifecycle policies to optimize costs by archiving processed data in the AWS Glacier Deep Archive.  

Quantified Outcomes and Impact 

The implementation of the AWS-based data lake by USDM delivered the following measurable outcomes: 

1. Operational Efficiency: 

• Reduction in Maintenance Costs: The automated data management and reduced patching efforts lowered maintenance costs by an estimated 30% annually. 

• Time Savings: IT teams saved approximately 1,200 hours per year, previously spent on manual patching and fragmented data management. 

2. Compliance and Audit Readiness: 

• Audit Risk Mitigation: The centralized data lake reduced compliance-related incidents by 25%, ensuring smoother audit processes. 

• Faster Regulatory Reporting: Reports generated for GxP and GDPR compliance were expedited by up to 40%, reducing reporting times from weeks to days. 

3. Cost Savings: 

• Storage Optimization: Transitioning processed data to AWS Glacier Deep Archive saved the organization $150,000 annually, with storage costs dropping to as low as $1 per terabyte per month. 

• Infrastructure Costs: The reliance on AWS managed services eliminated the need for additional on-premises hardware, yielding a 20% reduction in capital expenditures (CapEx). 

4. Improved Decision-Making: 

• Faster Analytics: Data democratization enabled key stakeholders to access analytics tools, reducing time to actionable insights by 50%. 

• Accelerated R&D Cycles: Improved data accessibility shortened research cycles, resulting in an estimated 10% increase in project throughput. 

5. Scalability: 

• Future-Ready Platform: The AWS infrastructure supported a 40% year-over-year increase in data volume without impacting system performance. 

• Team Productivity: By automating routine tasks, the platform allowed IT and data science teams to focus on innovation, improving productivity by 15%. 

Broader Implications 

This initiative highlights how cloud-based solutions can address common industry challenges, providing a framework for similar pharmaceutical, healthcare, and high-performance computing applications. By focusing on scalability, compliance, and democratization, organizations can unlock greater value from their data while maintaining stringent regulatory standards.