Compliance & validation
The evening before an audit shouldn't cost you sleep. Neogeniqs runs inside a validated, audit-ready platform aligned to the standards clinical teams, sponsors, and inspectors expect — 21 CFR Part 11, ICH E6(R3), the full CDISC stack, HIPAA/GDPR, SOC 2 and ISO 27001, ISO 42001 AI governance, and GAMP 5 validation — so you walk in already ready instead of scrambling to get there.
Why it matters
An AI platform that touches source data, consent, datasets, and the Trial Master File has to be trustworthy by construction — so that when the auditor arrives, you already know the answer to every question they'll ask. That means grounded generation, human sign-off on every regulated output, an unbroken audit trail, and a validated system underneath it all.
Below, each standard the platform is built against — what it is, and how Neogeniqs meets it — so nothing about your compliance posture is left to be discovered on inspection day. Compliance is a shared responsibility: we provide validated controls and evidence; your procedures and qualification complete the picture.
Regulatory foundation
The worry that keeps QA up: can we actually prove our electronic records and signatures are trustworthy and equivalent to paper? These regulations — 21 CFR Part 11 and ICH E6(R3) GCP — are how you answer that with evidence instead of hope.
What it is. The FDA rule that makes electronic records and electronic signatures trustworthy and legally equivalent to paper — requiring validation, audit trails, access controls, and signature manifestations.
How we meet it. Every record Neogeniqs creates carries a secure, time-stamped, computer-generated audit trail. Electronic signatures capture the signer, meaning, and timestamp; records are protected by role-based access and validated system controls end to end.
What it is. The current Good Clinical Practice guideline, which modernizes expectations for risk-based quality management, computerized systems, and data governance across the trial lifecycle.
How we meet it. Human-in-the-loop review, risk-based monitoring agents, and a governed data layer align to E6(R3)'s emphasis on quality-by-design, proportionate oversight, and reliable, attributable data.
Data standards
Few things sting like a submission delayed because the datasets didn't conform. From first eCRF to final define, the platform is built around the CDISC standards inspectors and regulators expect — so conformance is baked in from the start, not a scramble at the end.
What it is. Clinical Data Acquisition Standards Harmonization defines how data is collected on CRFs so it maps cleanly downstream.
How we meet it. The CRF Designer and Smart eCRF agents generate CDASH-conformant forms and fields, so what you collect is standardized from the first eCRF.
What it is. The Study Data Tabulation Model organizes collected data into the standardized structure required for FDA submission.
How we meet it. SDTM Annotation and the SDTM/ADaM agents produce annotated CRFs and conformant tabulation datasets automatically from your collected data.
What it is. The Analysis Data Model defines traceable, analysis-ready datasets derived from SDTM for statistical reporting.
How we meet it. The dataset agents build ADaM with full SDTM-to-ADaM traceability, ready to feed Tables, Listings & Figures.
What it is. The machine-readable data-definition document that describes datasets, variables, and derivations for a submission.
How we meet it. The Define.xml generator produces a conformant define with value-level metadata and derivation documentation alongside your datasets.
What it is. The de facto CDISC validation tool regulators use to check SDTM, ADaM, and Define.xml conformance.
How we meet it. CDISC Validation runs Pinnacle 21 checks in the loop and drives issues to resolution, so deliverables validate clean before they leave the platform.
Privacy
In a global trial, a single mishandled identifier can turn into a reportable breach. Rigorous, jurisdiction-aware handling of personal and health information is how you stop lying awake wondering where PHI went and who could see it.
What it is. The US framework governing protected health information (PHI) — its use, disclosure, and safeguards.
How we meet it. PHI is encrypted, access is role-based and logged, and de-identification is applied wherever downstream processing does not require identifiers. Business Associate Agreements are available.
What it is. The EU regulation governing lawful processing of personal data, data-subject rights, and cross-border transfer.
How we meet it. Lawful-basis controls, data-subject-rights support, data-minimization, and EU data-residency options support GDPR-compliant processing for global studies.
Security certifications
'Is our data actually secure — and can we show a sponsor or auditor the proof?' Independently audited controls over the confidentiality, integrity, and availability of your data mean that answer is documented and attestable, not just asserted.
What it is. An attestation of controls over security, availability, processing integrity, confidentiality, and privacy.
How we meet it. The platform operates and evidences controls audited against the Trust Services Criteria, with continuous monitoring and least-privilege access.
What it is. The international standard for an Information Security Management System governing risk, controls, and continual improvement.
How we meet it. A certified ISMS governs the whole platform — risk assessment, access management, encryption, incident response, and supplier controls.
AI governance
The newest fear on every reviewer's mind: AI touched a regulated document — so who's accountable, and can we trust it? Governing the AI itself as a first-class concern is how that anxiety becomes an auditable, defensible answer.
What it is. The international standard for managing AI responsibly — covering risk, transparency, oversight, and lifecycle governance of AI systems.
How we meet it. Neogeniqs aligns to ISO 42001 with grounded (RAG) generation, human-in-the-loop approval of regulated outputs, model and prompt version control, and auditable AI decision records.
Validation
An unvalidated system is an audit finding waiting to happen. The platform is validated as a computerized system, and it helps you keep your instance validated over time — so the deployment itself never becomes the thing that trips you up.
What it is. Computerized System Validation, following the GAMP 5 risk-based approach, documents that a system is fit for its intended use through Installation, Operational, and Performance Qualification (IQ/OQ/PQ) against user and functional requirements (URS/FRS).
How we meet it. Neogeniqs ships with a validation package — URS/FRS traceability, IQ/OQ/PQ protocols, and test evidence — and supports your qualification so the deployed system is inspection-ready.
What it is. The data-integrity principles regulators expect: Attributable, Legible, Contemporaneous, Original, Accurate — plus Complete, Consistent, Enduring, and Available.
How we meet it. Audit trails, versioning, secure storage, and access controls make every record attributable and enduring, so data integrity holds from capture through 25-year archival.
Our validation approach
Following a risk-based GAMP 5 lifecycle, the platform is qualified against your requirements and delivered with evidence you can hand to an inspector — so the moment they ask, the answer is already in the binder, not a task on your to-do list.
Requirements are captured as a User Requirements Specification and Functional Requirements Specification, traced to risk and to every downstream test.
Verify the system and its integrations are installed and configured correctly in your validated environment.
Test that each function — from CRF generation to e-signature to dataset output — operates as specified across expected conditions.
Confirm the system performs reliably against real study workflows and user requirements, with documented evidence for inspection.
Across the whole lifecycle, records stay Attributable, Legible, Contemporaneous, Original, and Accurate — plus Complete, Consistent, Enduring, and Available — carried by audit trails, versioning, and secure, access-controlled storage from capture through 25-year archival.
We'll walk your quality and regulatory teams through the audit trail, validation package, and AI governance model in detail — the strengths and the honest limits — so you can judge it for yourself. No pressure.
