Federated Governance in Life Sciences

Life Sciences companies are increasingly adopting data mesh architecture in response to growing business demands and evolving regulatory pressures. Heightened data protection laws such as GDPR and HIPAA, the emergence of digital twins, and technological advances are all accelerating the shift towards decentralised data ownership.

A fundamental pillar of the data mesh approach is federated governance. Put simply, federated governance is a coordinated yet decentralised method of managing data. It relies on several essential components:

• Data lineage
• Data standards
• Metadata requirements
• Compatibility
• Governance meetings
• Security policies
• A designated governance team

While broad literature exists on data mesh governance, this blog focuses on its application within biopharmaceutical companies.

Why Biopharma is Different

Although many core principles of data mesh governance remain relevant across industries, biopharma introduces unique challenges due to strict regulatory requirements, dynamic research environments, and long drug development cycles.

1. Regulatory-Driven Metadata Requirements

In biopharma, metadata requirements are often shaped by stringent regulatory frameworks. For example, the IDMP (Identification of Medicinal Products) standard prescribes highly specific metadata structures that companies must adopt. Compliance is not merely a goal—it is a foundational necessity.

Furthermore, ALCOA+ principles (Attributable, Legible, Contemporaneous, Original, Accurate, plus additional integrity attributes) must be deeply embedded within all layers of the data governance framework to uphold data integrity.

2. Flexibility in Evolving Research Data

The essence of biopharma—discovering and developing new compounds—means the data environment must be highly adaptable. New entities and attributes emerge frequently, requiring a governance structure that supports flexible and extensible naming and classification standards. This agility is vital for maintaining data quality and discoverability across scientific and operational domains.

3. Complex and Extended Data Lineage

Drug development typically spans many years. Over time, a single compound may undergo multiple name changes, become associated with various therapeutic indications, or be marketed under different brand names. Ensuring accurate and traceable data lineage throughout this lifecycle is both complex and essential.

The governance approach must allow for the proactive tracking of these changes and the ability to map relationships across data sources in a resilient and consistent manner.

Recommendations for Implementation

These distinctive characteristics make federated governance in life sciences significantly more complex than in other industries. At MIGx, we recommend the following best practices:

• Thoroughly document your governance strategy, clearly outlining roles, responsibilities, and accountability structures.
• Tailor documentation to the needs of specific stakeholder groups—including regulatory teams, research scientists, data engineers, and IT—ensuring accessibility and clarity for each audience.
• Engage cross-functional teams early to co-develop standards, ensuring both regulatory compliance and operational efficiency.
• Foster a culture of collaboration across data domains, reinforcing the shared responsibility for data quality and stewardship.

Federated governance, when properly implemented, empowers biopharma organisations to meet regulatory demands, support innovation, and unlock the full potential of decentralised, high-integrity data ecosystems.