AI now supports trial design, pharmacovigilance, medical writing and manufacturing quality. Asenion turns data integrity, validation and emerging AI rules into operational controls your CISO, QA and computer system validation teams can verify, monitor and evidence.
Schedule a Call30 minutes with our AI compliance team.
Few of these were written only for AI. All of them apply to it.
FDA requirements for trustworthy electronic records and electronic signatures in GxP systems.
For AI: AI that creates or modifies GxP records needs validation, audit trails, access controls and ALCOA+ data integrity.
FDA draft guidance (January 2025) proposing a risk-based credibility assessment framework for AI used to support decisions on drug and biologic safety, effectiveness or quality.
For AI: Define the question of interest and context of use, assess model risk, and document credibility evidence and lifecycle maintenance.
The industry's computerized system validation guide, including an appendix on AI and machine learning.
For AI: A risk-based approach to validating AI-enabled GxP systems and the data used to train and test them.
Proposed EU GMP rules for AI in medicines manufacturing, still in draft.
For AI: Static, deterministic models in critical GMP uses with defined acceptance criteria and independent test data; generative and dynamic AI limited to non-critical uses with human oversight.
AI in medical devices and IVDs is high-risk, with product-embedded obligations applying from August 2028 under the AI Omnibus.
For AI: Build AI Act risk management, data governance and human oversight into your QMS and MDR/IVDR processes.
The AI use cases we see most often, and the requirements that follow them.
Recruitment, site selection and endpoint analysis models need a documented context of use and credibility evidence if they support a submission.
Visual inspection, batch release support and process control models must be validated and monitored like any other GxP system.
GenAI that drafts case narratives, study reports or submission content needs qualified human review, hallucination testing and traceability to source data.
Scientists using GenAI with proprietary compounds or patient data need data classification, approved tools and controls against leakage.
One set of controls, applied from model development through production, with evidence your QA, auditors and inspectors can rely on.
Start from Policy Packs for 21 CFR Part 11, FDA AI guidance, GAMP 5, EU GMP Annex 22 and the EU AI Act, combined with your own QMS and SOPs.
Test models against acceptance criteria and GenAI tools for hallucination, data leakage and prompt injection, with every result mapped back to a control.
Apply context-aware controls to AI agents in production and capture tamper-resistant evidence of what happened, which controls applied and whether they worked.
In 30 minutes we'll map your AI use cases to the rules above, show the controls that apply, and point out gaps in your validation and governance approach.
Schedule a CallNo preparation needed.
