The role of Master Metadata Management (MDM)

MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official, shared master data assets. The idea of Master Data focuses on providing unobstructed access to a consistent representation of shared information.

How does it work?

Master Data Management (MDM) comprises of a set of processes and tools that consistently define and manage the master data and master reference data of an enterprise, which are fundamental to the company’s business operations. MDM has the objective of providing processes & tools for collecting, aggregating, matching, consolidating, assuring quality, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information.

There are different models for master data management – the 2 main extremes are

• Centralized model – where all data are managed within a central data store and pushed to the different applications within an organization.
• Decentralized model (registry) where the master data are managed within each application but then reconciled through a registry system to federate.

CHANGING LANDSCAPE: Enforcing data standards from protocol onwards

There are two approaches to enforcing data standards from protocol, they are the retroactive and proactive approaches.

Retro-active approach from paper protocol

• Different interpretations of same protocol
• Limited standards
• Time to build integrated SDTM data sets

Pro-active approach with structural metadata

• One single interpretation of protocol
• Increased efficiency, consistency & quality through standards
• Reduced time for integration and secondary data use

Efficient Data Integration and compliance with regulatory standards does not start after pooling (retroactive approach); it starts with the protocol (proactive approach)

A proactive approach is based on two components:

• Definition of Master Data (Drug Products, Studies, Sites, Investigators,..) and associated descriptive metadata
• Definition of study structural metadata – aka study specific data standards – as a subset of the enterprise-wide variables and value sets    contained in a Metadata Repository (MDR)

To be manageable, variables in an MDR need to be grouped in semantically meaningful “clinical research concepts” (CRC)

To Conclude – Sponsors need to change the way they consider compliance with data standards and data integration: From a retroactive way (building define.xml at submission) to a proactive approach (study data standards defined at study setup)

For that to happen, sponsors need new tools to manage metadata. Such tools should enable

• Concept-based MDR
• Grouping variables into semantically meaningful concepts (following industry-wide patterns)
• Linking data sources (e.g, CDASH based collection) to data submission (SDTM) variables
• Linking with controlled terminology
• Capabilities to handle standards versioning

MaxisIT

At MaxisIT, we clearly understand strategic priorities within clinical R&D, and we can resonate that well with our similar experiences of implementing solutions for improving Clinical Development Portfolio via an integrated platform-based approach; which delivers timely access to study specific as well as standardized and aggregated clinical trial operations as well as patient data, allows efficient trial oversight via remote monitoring, statistically assessed controls, data quality management, clinical reviews, and statistical computing. Moreover, it provides capabilities for planned vs. actual trending, optimization, as well as for fraud detection and risk-based monitoring. MaxisIT’s Integrated Technology Platform is a purpose-built solution, which helps Pharmaceutical & Life sciences industry by “Empowering Business Stakeholders with Integrated Computing, and Self-service Dashboards in the strategically externalized enterprise environment with major focus on the core clinical operations data as well as clinical information assets; which allows improved control over externalized, CROs and partners driven, clinical ecosystem; and enable in-time decision support, continuous monitoring over regulatory compliance, and greater operational efficiency at a measurable rate”.