AI for Pharma & Life Sciences: GxP Validated, Audit-Ready AI
From clinical evidence to HCP compliance, we build AI that meets pharma's regulatory requirements from day one.
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Challenges
GxP validation slows AI adoption
IQ/OQ/PQ, 21 CFR Part 11, full audit trails. Most AI vendors have never been through pharma validation. The gap between what they promise and what passes QA is enormous.
HCP engagement compliance is manual and slow
Every communication needs review. Teams spend more time on compliance than engagement. The review bottleneck limits how fast your field teams can operate.
Clinical evidence volumes overwhelm manual processes
Thousands of new publications monthly. Teams can't read everything but are responsible for knowing everything. Manual literature review doesn't scale.
Pharmacovigilance can't keep up
AE reports from trials, spontaneous reports, literature, social media growing exponentially. Signal detection at the speed and scale required is beyond manual capability.
Solutions
How we help
Pharma & Life Sciences AI
HCP engagement, clinical evidence automation, pharmacovigilance, and regulatory intelligence. All GxP validated.
Learn moreEnterprise RAG Systems
Regulatory document search across ICH, FDA, EMA guidelines, and internal submission histories with full citations.
Learn moreCompliance & Risk Agents
GxP monitoring, 21 CFR Part 11 verification, and automated regulatory change management.
Learn moreUse Cases
Real-world applications
HCP Engagement Compliance
AI reviews all healthcare professional communications against FDA regulations and industry codes before distribution.
80% faster compliance review
Clinical Evidence Automation
Continuous literature monitoring and evidence synthesis across PubMed, Embase, and internal clinical data.
10x faster evidence review
Pharmacovigilance & Safety Signals
AI monitors adverse event reports across clinical trials, spontaneous reports, and real-world evidence.
60% faster signal detection
Regulatory Document Intelligence
Semantic search across FDA submissions, EMA guidelines, ICH standards, and internal regulatory archives.
Medical Information Management
AI-powered medical inquiry response grounded in approved product information and clinical data.
GxP Audit Preparation
Automated evidence collection and CAPA documentation for GxP audits with full traceability.
50% less audit prep time
Our Method
Production AI in 90 days
Assess
Weeks 1-2
Map workflows, data sources, and compliance requirements. Identify highest-impact use case.
Build
Weeks 3-8
Architecture, development, and integration with your systems. Security hardening from day one.
Pilot
Weeks 9-10
Deploy with pilot group. Measure against success metrics. Refine based on real usage.
Harden
Weeks 11-12
Production hardening, monitoring, documentation, and handoff with training and support.
Assessment fee credited toward implementation
Compliance & Security
Technology Partners
FAQ
Frequently asked questions
How do you handle GxP validation for AI systems?
We follow full IQ/OQ/PQ validation protocols with complete documentation for every AI system. Our implementations are built with 21 CFR Part 11 compliance from the architecture level, including electronic signatures, audit trails, and role-based access controls.
Can the AI integrate with our existing pharma systems?
Yes. We integrate with Veeva Vault, IQVIA, Medidata, SAP for Life Sciences, and other pharma-specific platforms. The AI reads from your systems of record without modifying validated data.
How does the AI handle adverse event detection across data sources?
Our pharmacovigilance AI monitors clinical trial databases, spontaneous reporting systems, published literature, and real-world evidence simultaneously. It uses NLP to identify potential safety signals across structured and unstructured sources, then routes findings to safety teams for medical review.
Is the system compliant with both FDA and EMA requirements?
Yes. We build AI systems that meet both FDA and EMA regulatory requirements simultaneously, including 21 CFR Part 11, EU MDR, GDPR data residency, and ICH guidelines. Multi-region pharma companies can run a single compliant system.
What is the typical timeline for deploying pharma AI?
Pharma deployments typically follow a 90-120 day timeline due to validation requirements: 2-3 week assessment, 6-8 week build including IQ/OQ/PQ, 2-3 week pilot with clinical users, then production hardening with ongoing validation documentation.
Ready to ship AI that actually works?
Start with a 15-minute call. No pitch decks. We'll discuss your use case and whether our 90-day method is the right fit.
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