An NLP + LLM system that classifies, codes, and routes adverse event reports automatically — reducing manual triage from 48 hours to under 2 minutes while staying fully GxP-compliant.
Opella's OTC portfolio — Doliprane, Allegra, Dulcolax, Enterogermina and 100+ brands — reaches hundreds of millions of consumers across 100 markets. Every adverse event report must be triaged, coded to MedDRA, and submitted to regulators within strict timelines. Manual triage at this scale is unsustainable.
Current state: PV teams receive reports via email, web portals, call centres, and social media monitoring tools. Each report is manually read, seriousness assessed, MedDRA-coded, and routed to the right country safety officer. At scale, this requires large teams, creates processing backlogs, and introduces human error risk that can result in regulatory non-compliance.
Each incoming adverse event report passes through a six-stage NLP pipeline before reaching a human reviewer. The system handles free text, structured E2B(R3) XML, and multi-language inputs.
The system is designed as a modular, independently deployable pipeline — each layer has a single responsibility and communicates via well-defined contracts.
The LLM is not trusted blindly. It operates as a gated reasoning layer — called only when the NLP classifiers are uncertain, and always producing structured, verifiable output that a human can review.
Any AI system in pharmacovigilance must meet the same validation standards as other GxP-regulated software. This system is designed for validation from day one, not retrofitted.
Starting with a focused proof-of-concept on one product line, expanding to full global coverage. Each phase produces measurable, auditable results before the next begins.