VigilanceRx monitors patient conversations across the open web, automatically extracts adverse drug reaction signals using clinical NLP, and surfaces actionable safety intelligence — on demand, at scale.
Adverse drug reactions cost the global healthcare system over $30 billion annually. Yet the vast majority go unreported through conventional channels — yellow card schemes, clinical trial reporting, and manual surveillance systems built for a pre-internet world.
Meanwhile, patients are talking. On Reddit, on patient forums, on drug review sites — millions of people are describing their real experiences with medication every single day. This data exists. It is rich, timely, and almost entirely untapped.
The tools to listen have finally arrived. The industry just hasn't built them yet.
No manual review. No reporting lag. No missed signals.
Billions of patient experience data points are generated on public platforms every year. The signal has always been there. The infrastructure to capture it hasn't.
Transformer-based clinical NLP models like BioBERT have reached the accuracy threshold required for reliable adverse event extraction from unstructured text.
Regulators globally are expanding post-market surveillance requirements. Pharma companies need faster, broader, more cost-effective ways to meet their obligations.
Watch the platform ingest patient conversations, extract signals, and generate alerts — automatically.
VigilanceRx analyzes only publicly available patient conversations — posts, reviews, and discussions that individuals have chosen to share openly on public platforms. We do not collect, store, or process any personally identifiable information. No private messages. No authenticated data. No protected health information.
See VigilanceRx in action. We typically respond within 24 hours.