Pharmaceutical quality assurance teams operate under some of the most demanding regulatory requirements in any industry. Current Good Manufacturing Practice (cGMP) regulations under 21 CFR Parts 210 and 211, combined with ICH Q7 and Q10 guidelines, require documented procedures, controlled records, deviation management, corrective and preventive action programs, and audit trails that withstand FDA inspection scrutiny.
for Pharmaceutical
GMP Compliance
Many pharmaceutical companies — particularly small and mid-size manufacturers, CDMOs, and emerging biotechs — still manage these requirements across disconnected spreadsheets, shared drives, and paper-based systems. QAtrial v3.0.0 offers a purpose-built alternative: an open-source quality workspace that maps directly to pharmaceutical GMP requirements, deploys on the company’s own infrastructure, and costs nothing to license.
The FDA GMP Pharmaceutical Quality Pack
QAtrial’s setup wizard includes a pre-configured FDA GMP Pharmaceutical Quality compliance starter pack. Selecting this pack auto-fills the wizard with:
- Country: United States
- Vertical: Pharmaceuticals (FDA 21 CFR 210/211, ICH Q7/Q10, EU GMP Annex 11)
- Project Type: Quality System
- Modules (10): Audit Trail, Electronic Signatures, Data Integrity, Change Control, CAPA, Deviation Management, Training, Supplier Management, Document Control, Validation/CSV
This is not a generic quality template. The generated requirements and tests reference specific cGMP clauses, FDA guidance documents, and ICH guidelines. A QA manager at a pharmaceutical company can go from a blank system to a structured GMP quality project in under five minutes.
Ensuring the Integrity of Electronic Health Records
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CAPA Lifecycle Management
QAtrial implements a six-state CAPA lifecycle that mirrors pharmaceutical practice:
- Open — CAPA initiated from a deviation, failed test, complaint, or audit finding.
- Investigation — Root cause analysis in progress. QAtrial’s AI co-pilot can suggest root causes based on the failure description and the project’s regulatory context.
- In Progress — Corrective and preventive actions defined and being implemented.
- Verification — Actions completed, effectiveness verification underway.
- Resolved — Verification successful, CAPA closed pending final review.
- Closed — CAPA formally closed with documented evidence.
The backend enforces valid state transitions. A CAPA cannot jump from “Open” to “Closed” without passing through the intermediate states. Every transition is logged to the append-only audit trail with the user’s identity, timestamp, and reason for the change. The CAPA aging dashboard (/api/dashboard/:projectId/capa-aging) categorizes open CAPAs into aging buckets (0-7 days, 7-30 days, 30-90 days, 90+ days), providing the visibility that quality managers need to prevent overdue CAPAs — a common FDA 483 observation.
Clinical Quality Assurance Manager: Journal, Notes, Ideas, Actions, Priorities, Checklists, Log | Tool for Daily Goal Setting Tracker | Time … | Project Office Book Gifts for Meetings
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Data Integrity: ALCOA+ by Design
FDA’s 2018 guidance on data integrity and compliance with cGMP emphasizes ALCOA+ principles: Attributable, Legible, Contemporaneous, Original, Accurate, plus Complete, Consistent, Enduring, and Available. QAtrial’s architecture addresses each principle:
- Attributable: Every action is tied to an authenticated user via JWT. Electronic signatures capture the signer’s printed name, role, meaning of signature, and timestamp.
- Legible: All records are stored in structured PostgreSQL tables with defined schemas. Exports use UTF-8 encoding with BOM for correct rendering.
- Contemporaneous: Audit trail entries are timestamped at the moment of the action, not retroactively entered.
- Original: The PostgreSQL database is the original record. The audit trail is append-only — entries cannot be modified or deleted.
- Accurate: Input validation on all API endpoints prevents malformed data. Prisma ORM enforces referential integrity.
- Complete: The missing-evidence dashboard identifies records without attached evidence. The traceability matrix highlights untested requirements.
- Consistent: Auto-generated sequential IDs (REQ-001, TST-001) ensure consistent naming. Status transitions are enforced by the backend.
- Enduring: PostgreSQL with configurable backup. Docker deployment with named volumes for data persistence.
- Available: All data is exportable as CSV. Audit Mode provides instant read-only access. The system supports 12 languages for global operations.
The Data Integrity module is one of the 10 modules included in the FDA GMP pack, generating specific requirements and tests that verify ALCOA+ compliance within QAtrial itself.
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Electronic Signatures for Batch Release
Pharmaceutical batch release requires documented approval by authorized personnel. QAtrial’s electronic signature system is designed for 21 CFR Part 11 compliance:
- Signatures require password re-authentication at the time of signing. A user cannot sign based solely on an existing session.
- Each signature captures: printed name, role/title, meaning of signature (e.g., “Approved for Release,” “Reviewed,” “Authored”), reason, and timestamp.
- Signatures are linked to specific records via the approval workflow, creating an unbreakable chain from the record to the signer.
- A 15-minute verification window prevents replay attacks while allowing reasonable workflow continuity.
- The Compliance Statement documents alignment with Part 11 sections 11.50 (signature manifestation), 11.70 (signature/record linking), 11.100 (general requirements), and 11.200 (signature components).
The five-role RBAC system enforces separation of duties. A QA Engineer (qa_engineer role) can create and edit batch records but cannot approve them. A QA Manager (qa_manager role) can approve. A Reviewer (reviewer role) can approve but cannot edit, ensuring independent review.
THE DEFINITIVE REFERENCE TO GOOD MANUFACTURING PRACTICE: Pharmaceutical, Biologics, and Combination Product Compliance
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AI-Powered Gap Analysis
QAtrial’s AI co-pilot includes a gap analysis function that compares the current project state against regulatory standards. For a pharmaceutical project configured with the FDA GMP pack, the gap analysis evaluates coverage of 21 CFR 210/211 requirements, ICH Q7/Q10 clauses, and EU GMP Annex 11 sections.
The analysis categorizes each clause as:
- Covered: Requirements and tests exist that address this clause.
- Partially Covered: Some elements are addressed, but gaps remain.
- Missing: No requirements or tests address this clause.
The gap analysis is not a static document. It can be re-run after requirements are added or modified, providing a continuous view of regulatory coverage. The AI identifies specific gaps and suggests requirements that would close them, giving QA managers actionable remediation guidance rather than a generic checklist.
The Requirement Quality Check function adds another layer: it analyzes individual requirements for vagueness, untestability, ambiguity, incompleteness, duplicate risk, and missing acceptance criteria. In pharmaceutical quality systems where every requirement must be testable and verifiable, this automated quality gate prevents weak requirements from entering the system.
Migrating from Spreadsheet-Based QMS
Many pharmaceutical companies have years of quality data in Excel spreadsheets. QAtrial’s import system provides a practical migration path:
- Export existing requirements or test cases from Excel as CSV.
- Upload the CSV file to QAtrial’s three-step import wizard.
- The system auto-detects the delimiter (comma, semicolon, or tab) and suggests column mappings based on header names.
- Review the first three mapped rows to verify accuracy.
- Choose duplicate handling strategy: skip, overwrite, or create new.
- Import. Each imported record receives an auto-generated sequential ID and is logged to the audit trail.
After import, every record immediately participates in QAtrial’s traceability matrix, is subject to the audit trail, and can be linked to test cases, evidence, and approvals. The transition from a flat spreadsheet to a structured, traceable quality system happens in a single operation.
Export back to CSV is always available, ensuring that QAtrial does not create vendor lock-in — even though there is no vendor.
Server-Side AI: API Keys Stay on Your Infrastructure
Pharmaceutical companies have legitimate concerns about sending quality data to external AI services. QAtrial addresses this with a server-side AI proxy architecture. The backend endpoint (POST /api/ai/complete) proxies all LLM calls. API keys are stored as server environment variables and never exposed to the browser.
For companies that cannot send any data outside their network, QAtrial supports Ollama — a local LLM runtime. With Ollama configured as the AI provider, all AI functionality (test generation, risk classification, gap analysis, CAPA suggestions, quality checks) runs entirely within the company’s infrastructure. No quality data leaves the network.
This architecture makes QAtrial viable in environments where cloud-based AI is prohibited by corporate policy or regulatory interpretation.
Getting Started
git clone https://github.com/MeyerThorsten/QAtrial.git
cd QAtrial
cp .env.example .env
docker-compose upSelect the “FDA GMP Pharmaceutical Quality” compliance pack in the setup wizard. The system generates GMP-specific requirements, tests, and module configurations. From there, the quality team can customize, add company-specific requirements, import existing data, and begin building a traceable, auditable quality system.
QAtrial v3.0.0 is available under the AGPL-3.0 license at https://github.com/MeyerThorsten/QAtrial.
