Sporify and Veeva Webinar: Getting Ready for IDMP: The Importance of Reference Data Management

This webinar, co-hosted by Sporify and Veeva, provides an in-depth exploration of the challenges and solutions associated with preparing for the Identification of Medicinal Products (IDMP) mandate, focusing specifically on the critical role of reference data management (RDM) and data governance. The discussion establishes that the industry is moving toward a structured data agenda driven by health authorities (HAs) like the EMA and FDA, necessitating a shift from disparate, document-oriented systems to unified, data-centric platforms built on strong governance principles.

The core of the presentation centers on the need for a robust Regulatory Information Management (RIM) data foundation, which must be built upon consistent, high-quality referential data. This data includes controlled vocabularies and standards (e.g., EMA's SPOR databases: Substances, Products, Organizations, and Referentials—SMS, PMS, OMS, RMS) that ensure submissions are accurate and compliant. Paul Attridge from Veeva emphasized that poor data quality at the outset leads to downstream failures, similar to historical "failure to file" issues with content submissions. Sporify, introduced by co-founder Gary Worsley, positions itself as a data broker sitting between internal systems (like Veeva Vault RIM) and health authority databases. Sporify synchronizes HA data, compares it against internal records, and facilitates a centralized governance workflow, offering initial mapping efficiency gains of up to 80% by filtering data relevant only to the organization's product portfolio.

The webinar includes detailed case studies from Bristol Myers Squibb (BMS) and GSK, illustrating their respective IDMP and RDM journeys. BMS detailed a two-year process for establishing data governance, which involved clearly defining four distinct roles: Data Owner, Data Steward, IDMP Data Steward, and System Data Steward. Their strategy focused on harmonizing internal controlled vocabularies to accommodate regional differences while ensuring seamless mapping to required SPOR terms using the Sporify-Veeva integration. GSK shared their phased implementation approach, starting with Organization (OMS) and Referential (RMS) data, followed by Substance (SMS) data. GSK highlighted the business impact, noting that RDM implementation significantly improved data quality, particularly for organizational addresses, and created a new awareness among users regarding the importance of data alignment across documents and submissions. Both companies stressed the importance of intentional and sustainable data governance structures, ongoing training, and clear change management to maintain momentum and compliance long-term.

A key technical and procedural insight shared by both pharmaceutical companies is that Sporify acts as a complement to their RIM system (Veeva Vault). Internal controlled vocabularies are maintained in Veeva, synchronized to Sporify for mapping and governance by IDMP Data Stewards, and then the approved SPOR data flows back into Veeva. This centralized approach ensures a single source of truth for reference data across the enterprise, enhancing interoperability and reliability for use in RIM, safety, and MDM systems. The speakers also addressed the complexities of managing data changes outside internal control, such as updates to SPOR terms, which require dedicated governance workflows to review, approve, and synchronize before the data is used downstream in production systems.

Detailed Key Takeaways

• IDMP Requires a Data Foundation: Successful IDMP compliance hinges on building a robust regulatory data foundation (RIM data foundation) that moves organizations away from fractured, document-oriented systems toward unified, structured data management.
• Data Governance is Foundational: Establishing strong data governance principles and processes is critical for improving data quality from day one, which allows downstream QC processes to become more risk-oriented and prevents submission failures.
• Defined Governance Roles are Essential: BMS implemented four distinct data governance roles: Data Owner (accountable for access and conformance), Data Steward (responsible for standards and quality), IDMP Data Steward (handles mapping internal terms to SPOR terms), and System Data Steward (evaluates system enhancements).
• Centralized RDM for Harmonization: Centralizing the management of reference data (e.g., using Sporify) ensures data is harmonized across multiple enterprise systems (RIM, Safety, MDM), preventing version discrepancies and improving accessibility and reliability.
• Phased Implementation Strategy: GSK adopted a phased approach for RDM implementation, starting with OMS (Organization) and RMS (Referential) data, followed by SMS (Substance) data, allowing them to manage complexity and focus resources sequentially.
• Managing External Change Control: Organizations must adapt their change control practices to manage data that changes outside their control (e.g., SPOR updates). Sporify acts as a broker to alert organizations only to changes relevant to their product portfolio, enabling focused governance review.
• Mapping Efficiency Gains: Using specialized tools like Sporify can provide initial mapping efficiency gains of up to 80% by automating the comparison between internal data and health authority data and filtering out irrelevant noise.
• The 4i Principle for Mapping: BMS utilizes the "4i principle" (implying a rigorous review process) to ensure correct and appropriate mapping of internal terms to SPOR terms before the governed data is published back to the RIM system.
• Sustainability Requires Ongoing Effort: Data governance implementation is not a one-time project; it requires approximately two years to establish fully (as per BMS) and demands ongoing training, refresher courses, and clear communication to maintain momentum and onboard new team members due to turnover.
• Controlled Vocabulary Management: Organizations must develop harmonized internal controlled vocabulary lists that incorporate existing terms and new values, while also establishing processes for users to request new terms internally and recommend new terms to the EMA.
• Manual vs. Automatic Updates: GSK decided against automatic updates from Sporify to Veeva for OMS data, opting for manual review and potentially creating a new organization record in Vault if an address change occurs, to prevent disruption to registered details and regulatory submissions.
• Global Governance Expansion: The data governance structure should be built with the intention of expanding to other regions (e.g., Swissmedic, FDA SPL) as those requirements mature, necessitating training and preparation for regional data stewards.
• Data Enrichment and Cleansing Necessity: Moving from disparate systems to a unified platform requires lengthy processes of data enrichment and cleansing, especially where historical systems did not enforce mandatory data fields.

Tools/Resources Mentioned

• Veeva Vault RIM (Regulatory Vault): The primary internal system used by GSK and BMS for managing regulatory information and content.
• Sporify: A data broker platform that integrates with Veeva Vault RIM to synchronize, compare, govern, and manage health authority reference data (SPOR, GSRS).
• EMA SPOR Databases: Substance Management Service (SMS), Organization Management Service (OMS), Referential Management Service (RMS), and Product Management Service (PMS).
• FDA GSRS: Global Substance Registration System (used for substance data).

Key Concepts

• IDMP (Identification of Medicinal Products): The ISO standard requirements mandated by the EMA and other HAs for the unique identification and structured data submission of medicinal products.
• Referential Data Management (RDM): The processes and systems used to manage controlled vocabularies and standardized data elements (like dose forms, units of measure, routes of administration) required for regulatory submissions.
• Regulatory Data Foundation: A unified, centralized framework within an organization built on high-quality, governed data that serves as the single source of truth for all regulatory processes and submissions.
• Structured Data: The shift from submitting regulatory information primarily as unstructured text documents to submitting machine-readable, standardized data elements.
• Data Steward: A defined role responsible for authoring and maintaining data standards, ensuring data quality, and managing the mapping and governance of controlled vocabularies.