Lab to label. Every AI call governed.
Pharmaceutical and life sciences organizations face AI governance challenges spanning clinical trial data integrity, drug discovery IP protection, pharmacovigilance reporting, and regulatory compliance across FDA, EMA, and ICH frameworks. Arbitex puts governance in front of every AI call — protecting clinical data, research IP, and patient safety information under FDA 21 CFR Part 11, HIPAA, GxP, and GDPR. The data plane deploys inside your network.
Capabilities
AI governance built for pharma R&D, clinical operations, and regulatory affairs.
FDA 21 CFR Part 11 Compliance
Electronic records and electronic signatures in pharmaceutical AI workflows must meet FDA 21 CFR Part 11 requirements for audit trails, access controls, and data integrity. Arbitex enforces identity-verified sessions for every AI interaction involving regulated records. The tamper-proof audit log provides tamper-evident evidence of who submitted what data to which model, when, and what action was taken. Every enforcement decision is traceable to a specific user credential and policy rule.
Clinical Trial Data DLP
Clinical trial datasets contain patient identifiers, adverse event reports, randomization codes, and interim efficacy data — all subject to strict handling requirements during blinded studies. Arbitex's DLP pipeline detects clinical data patterns: subject IDs, site codes, randomization assignments, SAE narratives, and biomarker results. Researchers using AI for protocol analysis, literature review, or statistical modeling are inspected in-path. Violations are blocked before reaching any model.
Drug Discovery IP Protection
Pharmaceutical R&D generates high-value intellectual property: compound structures, formulation data, preclinical results, patent-pending discoveries, and proprietary assay methodologies. AI tools used for molecular modeling, literature synthesis, or target identification create a path for this IP to reach external models. Arbitex detects research-sensitive content patterns: compound identifiers, assay data, formulation parameters, and proprietary dataset references. Policy enforcement governs which research data categories reach which models.
Pharmacovigilance AI Governance
Post-market safety surveillance generates adverse event reports, signal detection analyses, and benefit-risk assessments that must be handled under strict regulatory timelines and data integrity requirements. AI tools used for case processing, signal detection, or periodic safety report drafting operate on patient safety data with regulatory submission obligations. Arbitex enforces department-level routing policies and data category restrictions for pharmacovigilance teams. Every AI interaction with safety data is logged for regulatory inspection.
GxP Validation Readiness
AI systems used in GxP-regulated processes — GLP for laboratory studies, GMP for manufacturing, GCP for clinical trials — require validation evidence demonstrating the system operates as intended. Arbitex provides the audit infrastructure for computerized system validation: immutable interaction logs, policy enforcement evidence, access control records, and data integrity verification through tamper-proof audit trails. Validation documentation maps directly to GAMP 5 risk-based categories for AI tool qualification.
Air-Gap for Classified R&D
Pharmaceutical companies handling controlled substance research, biosecurity-sensitive data, or pre-submission regulatory filings require isolated AI environments where no data leaves the organizational boundary. Arbitex Hybrid Outpost deploys inside the pharma company's secure network — DLP, policy enforcement, and audit run with no external connectivity. Policy bundles are delivered through approved secure transfer procedures. The gateway operates fail-closed: if the policy bundle cannot be validated, all AI traffic is blocked until the condition is resolved.
How it works
Deploy inside your pharma network or research environment
The Arbitex data plane installs in your corporate VPC or research network using Docker Compose or Kubernetes. R&D, clinical operations, regulatory affairs, and pharmacovigilance AI traffic routes through the gateway before reaching any model endpoint. For air-gap research environments, the Outpost package installs on locally provisioned infrastructure with no external network dependency. Clinical trial data detection, drug discovery IP protection, and audit logging run entirely inside your organizational boundary. No prompt content, response content, or patient data transits Arbitex infrastructure.
Clinical data and pharmaceutical IP detection runs in-path before any model processes it
Clinical trial data, patient identifiers, compound structures, pharmacovigilance reports, and regulatory submission content are detected before reaching any AI model. Policy enforcement applies organization-specific rules per department and user role. R&D workflows, clinical operations, manufacturing quality, and regulatory affairs tasks are each governed by appropriate policies. Enforcement actions — block, redact, or route-to-review — execute before any data reaches the model. Every decision is logged with a compliance framework identifier for regulatory reporting.
Audit evidence ready for FDA inspection and GxP validation
The tamper-proof audit log accumulates a complete evidence trail for every AI interaction involving clinical data or pharmaceutical IP. Signed exports provide documentation for FDA 21 CFR Part 11 compliance, GxP validation reviews, and regulatory inspection readiness. SIEM integrations deliver enforcement metrics for continuous monitoring of clinical data handling and research IP protection across departments. Pharmacovigilance audit trails are available for signal detection review and periodic safety report documentation.
Six frameworks. One policy layer.
Each compliance obligation maps to a specific Arbitex capability. All bundles are active simultaneously — no separate configuration per framework, therapeutic area, or trial phase.
Audit trail requirements for electronic records in AI workflows. Identity-verified sessions with tamper-evident logging. Access controls mapped to Part 11 requirements for closed and open systems. Signed export for FDA inspection.
Protected health information detection in clinical AI workflows. PHI patterns — patient names, MRNs, diagnoses, treatment data — detected and governed before reaching AI models. BAA-aligned data handling and audit trail.
GLP, GMP, and GCP validation evidence for AI systems used in regulated processes. GAMP 5 risk-based qualification support. Immutable interaction logs for computerized system validation documentation.
Clinical trial data integrity requirements under ICH E6(R3) Good Clinical Practice. Decentralized trial data governance, risk-based quality management evidence, and audit trail support for AI-assisted clinical analysis workflows.
EU GMP Annex 11 requirements for computerised systems in pharmaceutical operations. Validated audit trails, electronic signature support, and data integrity controls for AI tools used in EU-regulated processes.
EU clinical trial participant data under GDPR Article 9 special category protections. Cross-border data transfer controls for multi-site EU trials. Data subject rights enforcement for trial participant PII in AI workflows.
Related Resources
Ready to put governance in front of your pharmaceutical AI?
Talk to an Arbitex engineer about FDA 21 CFR Part 11 compliance, clinical trial data protection, drug discovery IP governance, pharmacovigilance audit trails, and air-gap deployment for sensitive R&D environments.