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Effective Adverse Event Detection and Coding with Natural Language Processing


Time: 8:00am PDT, 11:00am EDT, 4:00pm BST, 5:00pm CEST

Duration: 0 minutes


In an ideal world, adverse event reports would fit neatly into MedDRA, the standardized medical terminology for all regulatory submissions, so they could be easily reported and assessed for patterns to inform safety decisions. However, adverse events are often reported in natural language, for example by nurses, physicians and patients, each with a unique way of expressing themselves. To add to the complexity, these reporters have more reporting routes available than ever before, creating a deluge of natural language safety events that must be fully captured and understood. 

Today’s NLP technology can effectively “read” adverse event reports in their natural language, detect the adverse event and appropriate context, and code the adverse event to MedDRA.  This can reduce the manual effort needed in safety case processing, and increase coding consistency, whether from safety verbatims, social media, published literature, or other unstructured text.  

Join our webinar to learn how NLP can be used to synthesize information from many sources, provide evidence for business decisions, identify those novel connections that drive better value from your safety processing and how using NLP, CSL Behring doubled the level of autocoding adverse events from 30% to 60%.


Jane Reed - Director, Life Science
Jane Reed
Director, Life Science
Peng Zhang - Senior Application Scientist
Peng Zhang
Senior Application Scientist

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