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Webinar: Innovating drug safety with natural language processing

When:

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

Duration: 60 minutes


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Pharmaceutical organizations have a problem – there is a growing volume of safety data in varied data sources, report types, formats, etc. This is leading to unsustainable increases in the costs of safety operations and safety assessment, and leaders are looking for innovative solutions from new AI, automation and cloud approaches.  A recent Gartner reported stated: “By 2023, 60% of the top 100 life science companies will use AI augmentation in one or more safety vigilance solutions”.[1]

Many of our customers are using the power of IQVIA’s Natural Language Processing (NLP) platform from Linguamatics, 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 of IQVIA’s NLP Insights Hub for safety, 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 case processing, MedDRA mapping, safety intelligence, contextualization of safety signals. 
  • 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 adverse event medical coding, safety systems, medical literature mining for safety intelligence. 
  • With an interest in getting better value from both internal and external textual 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 

References:
[1] Jeff Smith, “Life Science CIOs Reduce Runaway Costs With Innovative Safety Vigilance Technology”. March 2021

Speakers

Jane Reed - Director, Life Science
Jane Reed
Director, Life Science
Sridevi Krishnamurthy - Application Scientist
Sridevi Krishnamurthy
Application Scientist

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