From fragmented data to actionable insights for a pharma company

A global pharmaceutical company was at a critical crossroads. While the company was embarking on a new therapeutic focus in oncology, its data, expertise, and knowledge were siloed. Spread across numerous sites and previous acquisitions, there was little ability to consolidate previous research efforts to build a new data foundation. This fragmentation created significant roadblocks:

• Inaccurate forecasting: The inability to get a complete and accurate forecast for the supply chain across its vast portfolio of clinical trials

• Inefficient workflows: Business workflows for supply planning and forecasting were cumbersome and not user-friendly, slowing down critical processes

• Integration gaps: Ingesting data from all trials into a central system and integrating it with other systems in the clinical landscape was a major hurdle

• Unidentified bottlenecks: The company struggled to identify and resolve the pain points, issues, and bottlenecks that were impeding progress

   

Without a unified data strategy, the company could not fully leverage its own research to build the new foundation required to excel in its renewed focus on oncology. The company needed to transform its disjointed data landscape into a cohesive, powerful asset.

We partnered with the company to systematically dismantle its data silos and build a connected, intelligent data ecosystem. Our approach was not just about technology; we wanted to create a new operating model centered on data product delivery.

First, we conducted a thorough discovery and definition phase, applying our business blueprinting methodology to map the entire data consumption life cycle. This meant we could conduct a current state analysis of business process inefficiencies.

With a clear understanding of the challenges, we developed a multifaceted solution.

• Established a robust data office and governance model: We implemented tailored policies and processes to help govern data. This included creating a URI policy for persistent identifiers to help promote data consistency and developing a modular oncology "building block" process to structure data logically

• Helped transform key data assets with Databricks: Using the Databricks platform's unified analytics capabilities, we streamlined data ingestion, processing, and analysis to transform the company's data ecosystem. A critical biomarker database was converted into a FAIR data knowledge graph, complete with a biomarker decision and analytics application. Additionally, a molecular data warehouse was uplifted from a proprietary structure into a multimodal FAIR data product, enhanced with powerful semantic search

• Delivered advanced analytics tools: For the disease strategy team focused on oncology, we delivered a competitive intelligence and asset FAIR knowledge graph application. This tool helps the team understand the competitive landscape and identify asset opportunities. We also created a virtual cohort FAIR knowledge graph from multimodal clinical, real-world, and public oncology patient datasets to enable advanced analytics

   

This strategic application of modern data architecture and FAIR principles provided the company with the tools to turn scattered information into strategic intelligence.