Architecting a GxP-Compliant Data Lakehouse for Pharma: Leveraging Azure Databricks for Regulated Analytics

Abstract

This article presents a comprehensive framework for implementing GxP-compliant data lakehouse architectures using Azure Databricks within pharmaceutical environments. The article addresses the fundamental tension between regulatory requirements and analytical innovation, proposing an architectural approach that satisfies stringent compliance standards while enabling advanced analytics capabilities. The article establishes design patterns for maintaining data integrity, traceability, and auditability across the pharmaceutical data lifecycle. The article demonstrates integration approaches for critical systems, including SAP S/4HANA, Laboratory Information Management Systems, and Manufacturing Execution Systems, with particular attention to data lineage implementation and validation strategies. The article reveals practical insights from implementation within a mid-size pharmaceutical organization, highlighting both challenges and successful outcomes. Discussion of best practices encompasses regulatory compliance patterns, performance optimization considerations, cost management strategies, and governance recommendations. While acknowledging current limitations in validation efficiency and specialized expertise requirements, the article establishes a foundation for GxP-compliant cloud data platforms that can transform pharmaceutical operations while maintaining the highest standards of data integrity and regulatory compliance.