LSPERF07-BP03 Develop an agile change management process

Develop a specialized change management process that enables rapid iteration for scientific computing while maintaining GxP adherence through a combination of procedural and technical safeguards. Implement digital solutions for documentation-as-code that creates machine-readable artifacts alongside software development, establish predefined patterns for common computational workflows, and deploy automated monitoring tools that provide real-time verification without manual intervention. Create cross-functional teams combining computational scientists, IT specialists and experts who collaboratively define fit-for-purpose validation approaches that protect data integrity and regulatory requirements while enabling the performance optimization and innovation velocity required by modern life sciences research.

Desired outcome: Establish efficient change management that enables fast scientific progress while maintaining adherence through automated documentation, predefined patterns, and cross-functional collaboration.

Level of risk exposed if this best practice is not established: High

Implementation guidance

Design change processes specifically optimized for computational science workflows. Specialized frameworks balance requirements with the need for scientific agility and rapid iteration.

Integrate documentation directly into development workflows using automated approaches. Documentation-as-code creates machine-readable artifacts that evolve alongside computational systems.

Create standardized approaches for common scientific computing challenges. Pre-defined patterns accelerate implementation while improving the consistency of regulatory and GxP approaches across research platforms.

Implement automated monitoring that continuously validates the state of systems. Real-time verification replaces periodic manual audits with constant assurance of compliant operations.

Establish collaborative teams that combine scientific, technical, and compliance-aligned expertise. Integrated teams develop balanced approaches that satisfy stakeholders while optimizing for research outcomes.

Implementation steps