Scenario & Background
A mid-sized biotech company developing a novel oncology cell therapy was running multiple Phase II trials across different sites. The company’s internal safety team was overwhelmed by the volume of adverse event (AE) reports and needed support in:
- Identifying emerging safety trends
- Standardizing reports across inconsistent formats
- Preparing for regulatory submission readiness
However, the client did not want a new IT platform or continuous system integration. They needed offline analytics support and actionable insights without disrupting their existing processes.
Objective
Use Assurea’s custom-built AI-enabled analytics framework to:
- Process AE reports provided by the client
- Standardize and code AE data consistently
- Identify safety patterns and emerging trends
- Deliver offline summaries and insights reports to the client’s safety team
Our Approach
- Data Sharing
The client provided monthly AE reports from three Phase II trial sites (~30–60 reports/month) along with early real-world AE inputs (~2–5 reports/month).
- AI-Assisted Analysis (Offline)
Assurea used its custom-built AI tech stack to parse, code, and trend the data offline — ensuring no integration into client systems.
- Periodic Insight Report
Assurea delivered bi-weekly summaries highlighting:
- New or worsening AE patterns
- Potential safety signal clusters
- MedDRA coding consistency gaps
- Safety Team Reviews
The client’s internal safety team used Assurea’s insights to:
- Prioritize safety review meetings
- Prepare responses for regulatory queries
- Strengthen their clinical safety database
The Results
- Time to identify AE trends reduced from ~10–14 days → ~3–4 days. Assurea reduced AE trend identification time from 10–14 days to 3–4 days by using its AI-powered offline analytics. Our custom tech stack standardized data, automated MedDRA coding, and quickly detected patterns, enabling faster insights without integrating into the client’s systems.
- MedDRA coding coverage improved from ~70% manual → 90% standardized
- False positives significantly reduced, improving accuracy of safety signals
- Analyst workload decreased, saving ~5–10 hours per week for deeper analysis
Benefits to the Client
- Faster detection of emerging safety trends
- Improved AE data quality and MedDRA coding consistency
- Reduced manual workload for analysts
- Strengthened clinical safety database ahead of BLA submission
- Zero IT disruption — Assurea handled analysis entirely offline
Summary
By leveraging Assurea’s custom-built AI-assisted analytics framework, the biotech company gained clear visibility into AE trends during their Phase II trials without deploying a new system or expanding internal teams.
This AI-driven, offline analysis model enabled:
- A scalable approach for future Phase III and post-marketing safety surveillance
- Faster trend detection
- Stronger regulatory readiness