VW - Datasphere a pharma case study

Virtualizing Workloads in the Pharmaceutical Industry: Unlocking the Power of Data with SAP Datasphere

The pharmaceutical industry thrives on data. From research and development to clinical trials and manufacturing, data drives every stage of the drug lifecycle. However, this data often resides in disparate systems, creating silos that hinder access, analysis, and real-time decision-making. This is where the concept of virtualizing workloads comes into play.

Virtualizing workloads allows pharmaceutical companies to access, process, and analyze data from various sources in real-time without the need for physical data movement or replication. It creates a virtual layer that interacts with data residing in its source systems, eliminating latency, minimizing storage costs, and enabling faster insights.

SAP Datasphere, an evolution of SAP Data Warehouse Cloud, emerges as a crucial enabler of workload virtualization in this context. It provides a unified platform for data integration, management, and access across SAP and non-SAP systems, including legacy systems, cloud platforms, and data lakes. Its semantic data layer ensures consistent data representation regardless of the physical location, making it easier for business users to understand and analyze data.

How SAP Datasphere Enables Workload Virtualization in Pharma

1. Federated Query Processing: SAP Datasphere leverages federated queries to access data directly from source systems like SAP S/4HANA, SAP BW, clinical trial databases, and manufacturing execution systems (MES). This eliminates the need for time-consuming ETL processes, ensuring near real-time data access for faster analysis and decision-making.
2. Data Orchestration: It orchestrates data from various systems, enabling seamless integration between SAP and non-SAP data sources like Salesforce, Veeva Vault, and research databases. This provides a holistic view of the entire drug development and manufacturing process.
3. Business Data Fabric: The Business Data Fabric layer provides a semantic understanding of the data, enabling business users to work with meaningful information rather than raw datasets. This simplifies data discovery and analysis, empowering users to make informed decisions.
4. Security and Governance: SAP Datasphere integrates with SAP BTP's security features, providing robust data access controls and ensuring compliance with industry regulations like GxP and GDPR.

Example Use Cases in the Pharmaceutical Industry

Use Case 1: Accelerating Drug Discovery

A pharmaceutical company wants to accelerate drug discovery by analyzing research data from various sources, including internal lab systems, external research databases, and clinical trial data.

Challenge: Data resides in siloed systems with different formats and structures, making it difficult to analyze and derive meaningful insights.

Solution:

• SAP Datasphere connects to all data sources, including internal systems, external databases, and cloud platforms.
• It harmonizes data and provides a unified view for analysis, enabling researchers to identify potential drug candidates faster.
• Machine learning models can be applied to the integrated data to predict drug efficacy and safety.

Use Case 2: Optimizing Clinical Trials

A pharmaceutical company needs to improve the efficiency of clinical trials by monitoring patient data and identifying potential risks in real-time.

Challenge: Patient data is spread across multiple systems, including electronic health records (EHR), clinical trial management systems (CTMS), and lab systems.

Solution:

• SAP Datasphere integrates data from all sources, providing a real-time view of patient data.
• Automated alerts can be set up to notify researchers of potential risks or adverse events.
• Real-time dashboards provide insights into trial progress, enabling proactive decision-making.

Use Case 3: Ensuring Supply Chain Integrity

A pharmaceutical company needs to ensure the integrity of its supply chain by tracking drug shipments and monitoring storage conditions in real-time.

Challenge: Data is scattered across different systems, including ERP systems, warehouse management systems (WMS), and transportation management systems (TMS).

Solution:

• SAP Datasphere integrates data from all systems, providing end-to-end visibility into the supply chain.
• Real-time monitoring of storage conditions ensures drug quality and prevents spoilage.
• Predictive analytics can be used to anticipate potential disruptions and optimize logistics.

By virtualizing workloads with SAP Datasphere, pharmaceutical companies can unlock the true potential of their data. This leads to faster drug discovery, more efficient clinical trials, improved supply chain integrity, and ultimately, better patient outcomes.