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Veeva Vault Configuration: Lessons from a GMP Compliance Project

A global pharmaceutical company used Veeva Vault QMS to manage deviations, CAPAs, and change controls.

Over time, teams added product structures, device hierarchies, stability data, and manufacturing details. Consequently, Vault started to replace functions that belonged to ERP, LIMS, and MES systems.

Although Veeva Vault supports objects, fields, workflows, lifecycles, security rules, and page layouts, it operates within fixed platform limits. Customers cannot access the database directly or deploy server-side code inside Vault.

Therefore, the growing configuration increased validation effort, affected performance, and made the system harder to explain during GMP inspections. The company needed to simplify the design and restore clear system boundaries.

Our team reviewed the existing Vault configuration, identified unnecessary complexity, and assessed which data and processes should remain within the QMS. We then proposed a simplified object model, returned non-essential data to the relevant source systems, and defined clearer principles for future configuration and change control.

Challenges Faced

A detailed GAP analysis in Quality Management Systems is essential for identifying process deficiencies effectively.
  • Vault Expanded Beyond Its Intended Role: Teams stored ERP, LIMS, and MES data inside Vault QMS, extending the system beyond quality processes.
  • Overengineered Object Models: Complex objects, fields, and relationships made the system difficult to manage and validate.
  • Configuration Limits: The growing design approached Vault limits and slowed record-saving performance.
  • Large Regression Testing Scope: Small configuration changes affected several connected processes and required extensive retesting.
  • Complex CSV Documentation: The validation team struggled to document the actual configuration clearly and traceably.
  • Inspection Transparency:Inspectors found it difficult to follow quality-process logic during GMP audits.
  • Upgrade and Change-Control Risk: Complex configurations created hidden dependencies that could affect future Vault releases.
  • Risk of Shadow Customization:External scripts and middleware introduced critical logic outside Vault, reducing transparency and increasing validation scope.

Zamann Pharma Support’s Approach

  • Review of the Vault’s Intended Role: The review identified which quality processes should remain inside Vault QMS.
  • Assessment of Configuration Boundaries: The team separated supported Vault configuration from unsupported software customization.
  • Simplification of Object Structures: The remediation reduced unnecessary objects, fields, relationships, and process complexity.
  • Return of Data to Source Systems: ERP, LIMS, and MES data moved back to their appropriate source systems.
  • Definition of Vault Design Principles: The approach prioritized standard objects, essential fields, and simple workflow structures.
  • Configuration Catalogue Development: The team documented critical objects, fields, lifecycles, workflows, and GxP configurations.
  • Controlled Use of Sandboxes and Snapshots:
    Sandboxes supported testing, while Snapshots captured controlled configuration states.
  • Risk-Based Change Management: Each configuration change received testing and documentation based on its GxP impact.
  • Simplification of High-Risk Logic: Critical decisions remained visible in clear Vault workflows instead of hidden integrations.
  • Cross-Functional Governance: IT, QA, process owners, and validation teams jointly reviewed major design decisions.

Results Achieved

  • Simplified Vault Configuration: The company reduced unnecessary complexity across objects and workflows.
  • Restored System Boundaries: Operational data returned to the appropriate ERP, LIMS, and MES systems.
  • Re-Focused QMS Scope: Vault returned to its core role in managing regulated quality processes.
  • Clearer Configuration Governance: The company established clearer rules for future configurations and integrations.
  • More Controlled Validation Approach: Catalogues, sandboxes, Snapshots, risk assessments, and change control strengthened CSV activities.
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FAQ

1. Why does an overengineered Vault QMS increase CSV workload?

An overengineered Vault QMS creates dependencies across objects, fields, lifecycles, workflows, permissions, reports, and integrations. Therefore, even a minor configuration change may require updates to risk assessments, specifications, traceability matrices, and test scripts, along with broader regression testing across affected GxP process paths.

 

2. When does external Vault logic become shadow customization?

External logic becomes shadow customization when middleware or scripts perform critical routing, calculations, approvals, status changes, or compliance checks outside Vault. Because this logic can affect regulated records and decisions, companies must include it within the validated system boundary and control it through documented specifications, testing, access control, and change management.

 

 

3. How should life sciences companies validate Vault configuration changes?

Companies should validate Vault changes through a risk-based change-control process. Teams should assess affected objects, workflows, permissions, integrations, and GxP records; implement and test changes in a sandbox; compare configurations through Snapshots; update validation documents; complete targeted regression testing; and obtain QA approval before production migration.