Innovating drug safety with natural language processing

Pharmaceutical organizations have a problem – there is a growing volume of safety events in increasingly varied formats. This is leading to unsustainable increases in the costs of traditional safety operations, and safety leaders are looking to 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 platforms and lower clinical development costs. NLP transforms unstructured text into structured data that can be rapidly analyzed or visualized. This capability can be applied for safety case processing, medical coding (e.g. to MedDRA), publication search for potential AE situations and medical review of AEs, and indeed, at every stage through the safety lifecycle of a drug.

This webinar will present an overview of customer success stories, to show best practice use of this Artificial Intelligence (AI) technology 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.

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