Audit & GxP Compliance Assessment of Artificial Intelligence (AI/ML) Systems
Protect patient data, pass inspections by leading global regulators (FDA, EMA), and safely move your AI solutions from pilot stage to full-scale production.
Why Traditional IT System Audits Fail for AI
Deploying AI and generative networks (LLMs) in clinical trials and manufacturing fundamentally changes the rules. Regulators (FDA, EMA) and emerging global standards (ICH E6 R3, GAMP 5 App. D11, EU AI Act) demand entirely new approaches to quality control.
Deploying AI and generative networks (LLMs) in clinical trials and manufacturing fundamentally changes the rules. Regulators (FDA, EMA) and emerging global standards (ICH E6 R3, GAMP 5 App. D11, EU AI Act) demand entirely new approaches to quality control.
- Shadow AIEmployees use public services (ChatGPT, DeepL) for handling medical data, violating confidentiality (PII/PHI) and leaking data to open models.
- Hallucinations & Data Integrity LossAI can generate plausible but fabricated facts. Without verification, this leads to distorted reports (CSR) or incorrect coding (MedDRA).
- The Black Box EffectTraditional validation (CSV) checks code but cannot verify the hidden logic of a neural network. A transition to Computer Software Assurance (CSA) with rigorous validation datasets is required.
- Model DriftAI accuracy degrades over time as real-world input data changes. Without continuous monitoring, the system becomes a compliance risk.
Who Is This Service For?
- Pharmaceutical & Biotech CompaniesFor assessing risks before deploying AI assistants in pharmacovigilance processes, protocol design, or eTMF triage.
- Contract Research Organizations (CROs)To demonstrate to Sponsors that your AI-powered data management solutions comply with ALCOA+ principles and the rigorous requirements of ICH E6(R3).
- IT Vendors & DevelopersEach member of our team has at least 5 years of legal experience. They use their knowledge to make our clients’ lives better.
Our team evaluates the system from every angle — assessing not just IT infrastructure, but also data processing algorithms.
What Does an AI System Audit Include?
- Data Governance & Vendor ControlReview of contracts (SLA/DPA) for mandatory clauses, including Zero Training Clause and Data Residency controls.
- Model Validation & Risk AssessmentSystem categorization per GAMP 5. Validation of test dataset quality (Ground Truth) and accuracy metrics using FMEA methodology (ICH Q9).
- Human-in-the-Loop PrincipleAudit Trail analysis for electronic signatures and evidence of genuine review of AI-generated outputs by qualified specialists.
- Drift Monitoring & Change ControlEvaluation of lifecycle procedures: re-validation frequency, prompt version logging, and deviation thresholds for retraining or model freezing.
Regulatory Framework
Standards We Audit Against
• ISPE GAMP® 5 (2nd Edition, 2022) — Appendix D11 (AI and Machine Learning)
• ICH E6(R3) Guideline — Data Governance and proportionate validation
• FDA & EMA Guiding Principles — 10 Principles of Good Machine Learning Practice
• EU AI Act — Requirements for High-Risk AI Systems
• 21 CFR Part 11 / EU GMP Annex 11 — Electronic records integrity standards
• ICH E6(R3) Guideline — Data Governance and proportionate validation
• FDA & EMA Guiding Principles — 10 Principles of Good Machine Learning Practice
• EU AI Act — Requirements for High-Risk AI Systems
• 21 CFR Part 11 / EU GMP Annex 11 — Electronic records integrity standards
Audit Deliverables
- Detailed Audit ReportClassification of all findings (Critical, Major, Minor) using an international GxP risk scale.
- AI Impact Assessment (AIIA)Ready-made risk profile with defined Context of Use.
- CAPA RoadmapStep-by-step instructions: SOP updates, Audit Trail configuration for prompts, vendor SLA revisions.
- Inspection ConfidenceConfidently answer FDA or EMA inspectors: How do you prove the AI isn't hallucinating? Where's the evidence the vendor isn't training on your data?
Frequently Asked Questions
Do we need to validate AI if it's a ready-made Enterprise cloud from a well-known provider?
Yes. Under ICH E6(R3) and Annex 11, responsibility for validating system usage always lies with the Sponsor/Company. We help conduct Vendor Assessment and set up UAT for your specific clinical or manufacturing processes.
What if we only use AI for writing texts, not for medical decisions?
Even assistive AI (Low/Medium Risk) requires baseline controls: data isolation (Walled Garden), algorithm version control, and fact-verification procedures (Human-in-the-Loop).
Do we need to validate AI if it's a ready-made Enterprise cloud from a well-known provider?
Yes. Under ICH E6(R3) and Annex 11, responsibility for validating system usage always lies with the Sponsor/Company. We help conduct Vendor Assessment and set up UAT for your specific clinical or manufacturing processes.
What if we only use AI for writing texts, not for medical decisions?
Even assistive AI (Low/Medium Risk) requires baseline controls: data isolation (Walled Garden), algorithm version control, and fact-verification procedures (Human-in-the-Loop).
Ready to Audit Your AI Systems?