Built to close the gap between
patient voices and safety action
Pharmacovigilance — the science of monitoring drug safety after a medication reaches the market — has historically relied on formal reporting systems that capture only a fraction of the adverse events patients actually experience.
The result is a systematic blind spot. Patients have always been talking about their experiences with medication — describing symptoms, comparing reactions, warning each other — in public online communities. This data is rich, timely, and real. But until now, no platform existed to listen to it at scale.
VigilanceRx was built to change that. Our mission is to turn the collective voice of patients into actionable pharmacovigilance intelligence — surfacing safety signals earlier, more broadly, and more cost-effectively than any existing approach.
“I kept hearing the same frustration from clinicians — by the time a safety signal made it through traditional channels, it was already too late. VigilanceRx exists to close that gap.”
Demir Can Uslu is a Biochemistry graduate of Tufts University. The idea for VigilanceRx emerged directly from his experience on clinical research teams, where he witnessed firsthand the limitations of incumbent pharmacovigilance systems — hearing from clinicians that critical adverse event signals were being missed, delayed, or lost in manual reporting processes.
Every signal we surface represents a real patient experience. We treat that data with the seriousness and respect it deserves.
Our NLP pipeline is built on peer-reviewed biomedical models and validated against established pharmacovigilance terminology.
Every alert is fully traceable to its source. We never generate signals that cannot be independently verified.
Automated detection is the starting point, not the endpoint. Human review and analyst judgment are integral to our workflow.