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Natural language processing innovations for drug safety in Pharma


Safety in drug development and discovery is one of the biggest challenges and opportunities facing life sciences companies today. It costs around $1 billion to develop one successful drug, but only 1 out of 10 drug candidates successfully passes clinical trial testing and regulatory approval because around 30% of new drugs fail to gain approval due to unmanageable toxicity or side effects. 

Innovative AI/ML technologies can bring benefits and improve this. Many of our customers use the power of IQVIA’s Natural Language Processing (NLP) platform to optimize their safety processes, and lower development costs. NLP transforms unstructured text into structured data that can be rapidly analyzed or visualized. This capability can be applied for safety assessment and medical review, enabling effective search of literature, drug labels and regulatory review packages for adverse events and the critical context around these, to help with a deeper understanding and contextualization of any potential safety signal. 

This webinar will present an overview of customer success stories, and a demo the IQVIA Safety Intelligence Hub, to show best practice use of NLP to advance drug safety. 

What will you learn? 

  • How natural language processing (NLP) text mining can extract structured data from unstructured text for safety assessment, contextualization of safety signals, safety case processing, MedDRA mapping. 
  • How big pharma access internal data silos and external data sources for safety decision making. Use cases from top pharma and the FDA will be discussed.  

Who should attend? 

  • Teams involved in safety assessment, medical review, adverse event medical coding, safety systems, medical literature mining for safety intelligence.  
  • Teams with a need to get better value from both internal and external textual safety information and integrating diverse data sets to provide knowledge relevant to drug safety and risk prediction. 
  • Informaticians, information professionals, researchers, with responsibility for: 
  • Risk profiles for targets in early drug discovery 
  • Preclinical and clinical drug safety 
  • Safety assessment across the pipeline 


Jane Reed - Director, Life Science
Jane Reed
Director, Life Science
Kaitlyn Whyte Linguamatics Application Scientist
Kaitlyn Whyte
Linguamatics Application Scientist

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