When Daily Work Drowns Your Team
Your quality manager spends three days writing CAPAs. Your regulatory team takes two weeks assembling submission sections from scattered documents. Literature surveillance backlogs pile up faster than analysts can clear them. Meeting notes sit unwritten. Training materials stay outdated because nobody has time to revise them.
The work matters. Patient safety depends on it. But the manual grind is unsustainable.
AI can help—if you control it properly.
I’m Carl Bufe—The AI-Native GxP Practitioner. I don’t sell AI platforms or promise magic. I build working AI systems into your daily operations—with the data controls, validation evidence, and audit trails that keep you inspection-ready while cutting manual work 20-40%.
What AI Integration Actually Delivers
AI integration takes approved use cases and embeds them where your team actually works. This means:
Document Writing
Draft SOPs from templates, generate CAPA investigation reports from deviation data, write protocol sections using your standard language, and create regulatory responses pulling from approved product information. Human experts review, edit, and approve—but start from 80% complete instead of blank pages.
Business Process Automation
Route documents for approval based on content type, send automated notifications when deadlines approach, trigger CAPA workflows when performance thresholds are breached, and populate fields in quality systems with structured data from external sources. Reduce manual clicking and chasing.
Data Aggregation
Pull safety data from multiple pharmacovigilance databases for periodic reports, combine clinical monitoring data across sites for oversight meetings, and extract metrics from your QMS for management reviews. Stop copying and pasting between systems.
Scientific Research Support
Screen literature databases against your product profiles, summarise clinical study results by indication, extract safety signals from regulatory authority databases, and compile competitive intelligence from public sources. Get the signal faster without getting lost in abstracts.
Communication Efficiency
Draft responses to regulatory authority questions using approved technical documentation, summarise long email threads for handovers, and generate meeting summaries with action items tracked. Keep teams aligned without administrative overhead.
Every output includes citations that reference the source documents. Every recommendation requires human approval. Every decision creates an audit trail.
Few Components We Build With You
- Workflow Design Under GAMP 5 Principles – We map current processes, then redesign them with AI assistance at the right points. Each workflow includes risk assessment, validation requirements, change control, and clear approval authorities.
- Data Integrity and Provenance Controls – Data lineage tracking from source through AI processing to final output. Version control for data, models, and prompts. Access controls limit who can modify configurations. Retention schedules meet regulatory requirements.
- RAG Architecture for Evidence Retrieval – Retrieval-Augmented Generation systems pull answers from your approved documents rather than inventing information. Connect to SharePoint, Veeva Vault, or internal databases. Maintain versioning and permissions. Return answers with citations. Log every query.
- Human-in-the-Loop Approval and Oversight – Where medical judgment, regulatory decisions, or quality determinations matter, humans review and approve. Structured review screens show AI recommendations with source evidence. Override mechanisms let experts reject suggestions. Escalation paths handle low-confidence outputs.
- Integration With Your Existing Systems – We connect AI to Microsoft 365, Quality Management Systems, pharmacovigilance databases, Clinical Trial Management Systems, and validated databases. Your teams work in familiar environments. AI runs behind the scenes with proper controls.
- AI Model Lifecycle Management – Performance monitoring, tracking accuracy, and user satisfaction. Model retraining schedules when performance drops. Validation evidence documenting that updates maintain fitness-for-purpose. Decommissioning protocols when systems become obsolete.
Examples From Daily Work (Cases)
- Pharmacovigilance Case Processing (GxP Vigilance Partner). AI drafts case narratives from structured fields. The safety physician reviews the medical assessment, adjusts the causality, and approves. Cycle drops from 8 days to 3-5 days.
- Literature Surveillance (GxP Vigilance Partner and Internal Team). AI screens 1,900 abstracts weekly against your safety profile (90min review vs 8 hours).
- CAPA Investigation Reports (GxP Vigilance Client – Microsoft with comprehensive organisational data). AI generates an investigation structure from deviation data, retrieves relevant SOPs, and suggests root causes based on similar past deviations (2-4 hours).
- Meeting Minutes and Transcription (Client). AI transcribes meeting audio in real-time, identifies key phrases and action items, generates structured minutes, and extracts owner/due date information. Clinical trial site meetings and safety committee meetings.
- Drug Labelling and Patient Information Leaflets (GxP Vigilance Project Work).
- Training Material Generation (Client). AI generates training materials for field Medical Science Liaisons (MSLs), creates slide decks for scientific presentations, customises patient education materials, and produces onboarding content.
