AI Document Intelligence for Pharma & Life Sciences

The Challenge: Pharmaceutical IP and Patient Data Cannot Leave Your Network

Pharmaceutical and life sciences organizations manage some of the most valuable and sensitive documents in existence — clinical trial protocols, adverse event reports, drug formulation dossiers, regulatory submissions, and decades of proprietary research. Yet AI adoption in pharma has been slow, because the risks of data exposure are existential.

The core problem: Cloud-based AI tools require uploading documents to third-party servers. For pharma and life sciences, this creates risks that go beyond compliance:

• Intellectual property leakage — drug formulations, compound structures, and development timelines sent to external APIs
• Clinical trial data exposure — participant data and proprietary protocols accessible to cloud providers
• Regulatory violation — EMA, Swissmedic, and BfArM requirements for data confidentiality breached by default
• Competitive intelligence risk — years of R&D investment exposed to cloud infrastructure shared with competitors

How KADARAG Solves This

KADARAG runs entirely on your infrastructure. No trial protocol, compound dossier, or patient record ever leaves your network — not even as a query fragment. Your IP stays yours.

Clinical Trial Documentation

Research and regulatory affairs teams manage enormous volumes of trial data across dozens of active studies:

• "Which adverse events in Phase II of trial 2024-CHF-019 overlap with the exclusion criteria?"
• "Summarize all protocol amendments for the current compound across trials since 2022."
• "What were the primary endpoint results for studies using this dosage range?"

All queries are processed locally. The AI reads your trial documents on your servers and returns answers without any data leaving your infrastructure boundary.

Regulatory Submission Intelligence

Regulatory affairs teams face constant pressure to respond to authority queries and prepare dossiers — often searching across hundreds of related documents:

• Cross-reference new EMA guidelines against existing submission content
• Retrieve prior regulatory correspondence relevant to a current authority inquiry
• Identify gaps between current data packages and updated requirements
• Search across CTD modules, scientific advice letters, and CHMP opinions simultaneously

Pharmacovigilance & Safety

Safety teams monitoring adverse event signals need to correlate data across large document repositories:

• Search spontaneous case reports against protocol-defined adverse event categories
• Retrieve all documents referencing a specific drug interaction or safety signal
• Cross-reference post-market surveillance data with pre-approval trial findings
• Generate periodic safety update report (PSUR) summaries from source documents

Research & IP Management

R&D teams can query their internal scientific knowledge base without external exposure:

• Search patent filings, research notes, and lab reports simultaneously
• Find prior internal research relevant to a new compound candidate
• Retrieve formulation precedents from historical development files
• Identify which research teams have worked on related molecular pathways

Key Benefits for Pharma & Life Sciences

Zero IP Exposure

Every component — embeddings, vector database, language model, and retrieval engine — runs inside your infrastructure boundary. Compound structures, trial data, and regulatory strategy never leave your network.

EMA, GCP & GDPR Alignment

By eliminating third-party data transfers entirely, KADARAG supports compliance with EMA data governance expectations, Good Clinical Practice (GCP) requirements for data integrity, and GDPR obligations for clinical trial participant data. There is no external data processor involved in the AI pipeline.

EU AI Act High-Risk Compliance

AI systems used in clinical contexts are classified as high-risk under the EU AI Act (full enforcement August 2026). KADARAG's on-premise architecture supports auditability, transparency, and human oversight requirements — all logged locally without cloud dependency.

Air-Gap Capable

Research facilities, cleanroom environments, and organizations with strict network segmentation can deploy KADARAG without any internet connection. The fully offline model is designed for exactly these environments.

Full Audit Trail

Every query, every document retrieval, and every generated answer is logged locally with user identity and timestamp. Supports GCP audit trail requirements and provides complete traceability for regulatory inspections.

Role-Based Access Control

Granular permissions ensure that clinical staff access trial data, regulatory affairs teams work with submission documents, and research teams query IP-sensitive files — each within their authorized scope and with no cross-contamination.

Deployment Options

Most large pharmaceutical organizations and clinical research organizations choose the fully offline deployment to eliminate any risk of compound or patient data exposure. For early-stage biotech companies working primarily with non-confidential scientific literature, the hybrid model offers frontier-model quality at lower infrastructure cost.

Getting Started

1. Assessment — We evaluate your document repositories, data sensitivity profile, and regulatory obligations
2. Pilot deployment — A dedicated KADARAG instance with a defined document set, running on your servers within your security perimeter
3. Go live — Full deployment with training for regulatory affairs, clinical operations, and research teams