Every adverse event report tells a story—not just about safety, but about real people. Pharmacovigilance (PV) teams carry the responsibility of protecting patient safety by detecting, analyzing, and reporting those events. But with over 30 million records in the FDA’s FAERS database—and over a million new ones added annually—the volume of data has surpassed what manual systems can handle.

And we’re still missing too much. The WHO estimates that fewer than 10% of adverse drug reactions are reported. The scale of the challenge demands a smarter, faster, and more scalable approach.

Why Legacy Safety Workflows Fall Short

Even the most experienced PV professionals are up against:

Diverse data sources

PDFs, EHRs, social media, and more, each in different formats

Manual coding bottlenecks

Mapping narratives to MedDRA remains slow and error-prone

Delayed signal detection

Quarterly reviews delay potential interventions

Constant regulatory updates

FDA, EMA, and PMDA changes make static systems obsolete

The result? Safety scientists spend more time managing documents than managing drug safety risk.

Introducing Q‑Safe: Generative AI for End-to-End Pharmacovigilance Automation

Q‑Safe is Quantiphi’s AI-powered platform for pharmacovigilance automation. Built on LLMs and retrieval-augmented generation (RAG), Q‑Safe accelerates the ICSR lifecycle—from intake to narrative generation, signal detection, and regulatory submission.

How Q‑Safe Transforms the Adverse Event Workflow:

Intake → Narrative → Signal Detection → Submission

Multichannel Intake & Auto-Coding: Capture adverse events from PDFs, emails, social media, PubMed, and EHRs. Q‑Safe automatically deduplicates and classifies cases (Valid, Invalid, Potentially Valid), and maps terms to MedDRA.
Narrative Drafting with LLMs: Generative AI drafts regulator-ready case narratives that safety scientists can finalize in minutes—cutting narrative creation time by up to 80%.
Real-Time Signal Surveillance: Built-in machine learning algorithms run disproportionality and clustering analyses continuously, so safety signals surface immediately—not months later.
Causality and Seriousness Assist: Q‑Safe applies scoring across WHO-UMC, CTCAE, and Naranjo scales to support fast, consistent triage.
Regulatory Compliance by Design: Every action is logged with a full audit trail. Q‑Safe supports HIPAA, GDPR, and GxP requirements from day one.
Case Management Dashboards: Filter by molecule, source, or date. Review flagged duplicates. Track team activity. All from one secure, user-friendly interface.
Seamless Exports & Integrations: Export outputs to ArisG, Veeva, E2B, Excel, and other systems—without disrupting your existing workflow.

What Sets Q‑Safe Apart

Unlike tools focused solely on literature surveillance, Q‑Safe was built to manage the full intake ecosystem. It combines:

LLMs trained specifically for PV data
Real-time deduplication and validation
Support for structured and unstructured sources
Interoperability with your existing safety systems

Q‑Safe doesn’t replace your CROs or safety teams—it enhances them. By reducing turnaround times and administrative overhead, it empowers your scientists to focus on what matters most: protecting patients.

Why Quantiphi

Quantiphi brings unmatched experience in combining deep domain expertise with cutting-edge AI. As a premier partner of Google Cloud, AWS, NVIDIA, and Microsoft Azure, we deliver secure, compliant, and production-grade AI solutions. With over 2,500+ AI deployments, we’ve helped life sciences organizations unlock the value of their data—safely and responsibly.

Ready to See Q‑Safe in Action?

Pharmacovigilance doesn’t need to be a patchwork of PDFs, spreadsheets, and missed signals. With Q‑Safe, safety teams start their day with clarity—seriousness scores, emerging risks, and pre-drafted narratives all surfaced instantly and intuitively.

It’s automation where it matters most—freeing scientists to focus on insights, not inboxes.

Run a pilot using your real-world safety data
Quantiphi will scope, deploy, and benchmark Q‑Safe in just four weeks—delivering measurable ROI without the guesswork.

Book your pharmacovigilance assessment

Don’t Miss Our Webinar: HealthTech Qonversations
Join us for a deep dive into how AI is transforming pharmacovigilance—and see Q‑Safe in action.

Modernizing Pharmacovigilance: How Q‑Safe Frees Safety Scientists to Focus on Patients

Every adverse event (AE) is more than a datapoint—it’s a patient’s story. But today’s pharmacovigilance (PV) teams are drowning in data, not insights. The U.S. FDA’s FAERS database alone holds over 30 million individual case reports and adds more than a million each year. Yet the World Health Organization estimates that fewer than 10% of adverse drug reactions are reported.

Why is there such a gap? Because the process of managing safety data is still burdened by manual effort and outdated systems. According to a recent industry survey, 80% of PV professionals cite data integration from diverse sources—email, EHRs, call centers, and social media—as their greatest bottleneck. On average, manual entry still takes 45 minutes per case and costs approximately $180 when considering staff time and overhead.

Why Legacy Safety Workflows Are Breaking

Even the most disciplined teams struggle when faced with:

Source Explosion: A single AE case can span PDFs, EHR extracts, emails, and even social media—none sharing a consistent format.
Manual Data Entry: Coding free-text into MedDRA is time-consuming, error-prone, and labor-intensive.
Delayed Signal Detection: Traditional systems rely on quarterly reviews and retrospective analyses—delaying response to emerging risks.
Frequent Regulatory Changes: EMA, FDA, and PMDA regulations evolve quickly, leaving teams scrambling to reconfigure legacy or homegrown tools.

The result? Safety scientists spend far too much time clicking through forms, validating fields, and transcribing information—instead of interpreting risk signals and improving patient outcomes.

Enter Q‑Safe: The Future of Generative-AI Powered Pharmacovigilance

Q‑Safe is Quantiphi’s AI-native pharmacovigilance platform built on advanced large language models (LLMs) and retrieval-augmented generation (RAG). It automates the end-to-end ICSR (Individual Case Safety Report) lifecycle—from Intake → Narrative → Signal Detection → Submission—dramatically reducing turnaround time and unlocking new levels of efficiency.

At its core, Q‑Safe is designed to let scientists focus on science—not systems.

What Sets Q‑Safe Apart

Most solutions on the market focus solely on automating literature monitoring. Q‑Safe is a comprehensive safety automation platform that addresses the entire intake ecosystem—from multichannel data ingestion to real-time signal detection and regulatory-compliant submissions.

Key Differentiators:

End-to-End Workflow Automation: From source import to signal detection and submission
Seamless Integration: Compatible with industry platforms like ArisG and Veeva
Multichannel Intake: Pulls in PDFs, emails, EHRs, social posts, CSVs, and PubMed content
Real-Time Duplicate Detection: Flags redundant cases instantly
Advanced Validation Logic: Ensures data quality and audit-readiness at every step

Q‑Safe is not here to replace your CROs—it works with them to build internal capacity, improve visibility, and reduce ICSR turnaround time by up to 80%.

How Q‑Safe Works: Step-by-Step

Intelligent Case Intake

Log in through a secure, role-based interface and access Q‑Safe’s intuitive dashboard. Navigate to Case Intake, where you can:

Import data from email, PDFs, PubMed, or configured sources
Use smart filters by molecule, source, or date
Auto-fetch content from scientific literature or internal databases
Track progress in real time via the notification bell icon

Q‑Safe uses fine-tuned LLMs to:

Detect and validate adverse events
Filter out irrelevant documents
Classify each case as Valid, Invalid, or Potentially Valid
Flag duplicates automatically

This minimizes noise and accelerates initial triage, so analysts can focus on higher-risk cases.

Streamlined Case Processing

In the Case Processing dashboard, users can:

Track active case volumes through an interactive activity chart
Filter and sort by custom criteria
Access comprehensive case details—including MedDRA-coded terms, patient and product data, and regulatory narrative drafts

Q‑Safe’s automation engine:

Scores causality and seriousness using WHO-UMC, Naranjo, and CTCAE
Auto-fills relevant narrative sections
Ensures traceability with fully explainable models

All data is exportable in E2B, Excel, and other industry formats—making it easy to comply with regulatory submission workflows.

Closed Case Management and Duplicate Handling

Even after submission, Q‑Safe allows you to:

Revisit closed cases
Manage flagged duplicates across all intake sources (literature, EHRs, call centers)
Maintain an immutable audit trail to support compliance and traceability

Real-Time Signal Detection

Q‑Safe uses clustering and disproportionality analysis to surface emerging risk signals as they happen. High-risk patterns immediately trigger alerts via the dashboard—eliminating delays tied to quarterly surveillance cycles.

The result? Faster decisions, fewer missed signals, and safer outcomes for patients.

Platform Features That Empower Your Team

Role-Based Dashboards:

Tailored views for PV analysts, safety scientists, and QA/compliance

Audit-Ready Transparency:

Every user action is logged and timestamped

Global Compliance:

Fully aligned with 21 CFR §314.80, EMA GVP Module VI, ICH E2B(R3), HIPAA, GDPR, SOC 2, and ISO 27001

Cloud-Native Speed:

Built for scalability, supporting millions of cases annually

A Reimagined Day in Pharmacovigilance

Before Q‑Safe:
A senior scientist spends the morning buried in spreadsheets and scanned PDFs—manually inputting data, coding terms, and validating forms.

After Q‑Safe:
The scientist logs in to a dashboard that highlights high-risk cases. Auto-drafted narratives are ready for review. Two new statistical signals are flagged. A quick review and the rest of the day is free for strategic work—conferring with R&D, updating risk management plans, or collaborating with the clinical team.

The role doesn’t disappear—it evolves.

Why Quantiphi

Quantiphi combines deep pharmacovigilance domain expertise with world-class AI and cloud engineering. As a premier partner of Google Cloud, AWS, and NVIDIA, we have delivered over 2,500+ enterprise-grade AI solutions—with full adherence to GxP, HIPAA, and GDPR requirements.

What You Can Expect:

Modular, scalable AI architecture
Responsible AI practices built into the model lifecycle
ROI in weeks—not quarters

We understand both the regulatory landscape and the codebase that powers transformation.

Q‑Safe in Action: Your Next Step

Run a Real-World Pilot
Deploy Q‑Safe on your safety data with our 4-week pilot offering. We’ll scope, deploy, and benchmark performance—so you can evaluate results, not promises.

Want to see the impact firsthand?

Book Your Pharmacovigilance Assessment

Because safety science should move as fast as the risks it monitors.

Watch HealthTech Qonversations

Watch our debut webinar, HealthTech Qonversations, to discover how AI is revolutionizing pharmacovigilance. Hear from industry experts and see Q‑Safe in action as it transforms safety workflows.