Validation

What validation means

Validation is the establishment of documented evidence providing a high degree of assurance that a specific process, computerized system, or analytical method will consistently produce a result meeting its predetermined specifications and quality attributes.

In regulated quality, validation covers three overlapping domains: process validation (manufacturing), method validation (analytical), and computer system validation (CSV) or its modern risk-based variant Computer Software Assurance (CSA).

Why validation defines regulatory confidence

Inspectors rely on validation records to answer a core question: does this process or system actually produce what you claim? Weak or missing validation is among the most serious compliance failures — FDA Warning Letters frequently cite inadequate validation of computerized systems and manufacturing processes.

The 2022 FDA draft guidance on Computer Software Assurance (CSA) signaled a shift away from script-heavy CSV toward risk-based, fit-for-purpose evidence. Organizations now navigate a transition where legacy CSV programs coexist with modern CSA practice.

Where validation is mandated

Validation is referenced across virtually every GxP regulation and quality standard:

• FDA 21 CFR Part 11 — Validation of closed / open systems handling electronic records
• FDA 21 CFR Part 211 §211.68 and §211.100 — Process and computer system validation
• EU GMP Annex 11 — Computerised systems validation (the EU counterpart to Part 11)
• EU GMP Annex 15 — Qualification and validation framework
• FDA Guidance: Computer Software Assurance (CSA) — Risk-based, modern alternative to pure CSV
• GAMP 5 (Second Edition) — Category-based risk-based approach to CSV/CSA
• ISO 13485 §7.5.6 & §7.5.7 — Process and software validation for medical devices

The validation lifecycle

A typical validation lifecycle for a computerized system:

• Validation Master Plan (VMP) — scope, approach, roles, deliverables, risk posture
• URS (User Requirements Specification) — what the system must do
• Risk Assessment — GAMP 5 category, impact classification, test strategy
• Functional / Design Specifications — how the system meets requirements
• IQ (Installation Qualification) — correctly installed per specifications
• OQ (Operational Qualification) — functions as designed across expected ranges
• PQ (Performance Qualification) — performs reliably in intended operating environment
• Traceability Matrix — URS → spec → test mapping
• Ongoing maintenance — change control, periodic review, re-validation triggers

What strong validation programs share

Effective validation operations have:

• Clear GxP impact classification driving validation depth
• GAMP 5 category aligned to test rigor (Category 3-5)
• Risk-based CSA for low-risk SaaS, fuller CSV for high-risk custom systems
• Controlled deviation handling during execution
• Traceability matrix maintained through change control
• Periodic review tied to regulatory updates
• Supplier audit evidence for vendor-provided systems

How Complere supports validation

Complere ships with a validation package aligned to CSV/CSA that organizations can adopt as their starting evidence set, then extend for site-specific needs.

• Pre-built VMP, URS, risk assessment, IQ/OQ/PQ templates
• GAMP 5 Category 4 (configurable SaaS) baseline classification
• Traceability matrix auto-generated from requirements → tests
• Validation evidence kept within Complere's own document control + audit trail
• Change control triggers re-validation workflow for impacted requirements
• Periodic review cadence aligned to regulatory frameworks
• Annex 11 and Part 11 mapping documentation included

Related validation terms

Validation sits at the intersection of many quality concepts:

• CAPA — CAPAs may trigger re-validation
• Audit Trail — part of every validated system
• Deviation — validation deviations require justification
• OOS — analytical method validation underlies OOS interpretation
• Root Cause Analysis — used when validation fails