Labeling Intelligence Hub

Compare and extract critical drug label information

Accurate regulatory intelligence is essential for better decision-making for regulatory teams. The IQVIA labeling Intelligence Hub uses award-winning natural language processing (NLP) to find, extract and compare drug label information with simple and rapid capture of relevant data in labeling documents from diverse sources such as FDA drug labels, EMA drug labels, French drug labels and more.

Deliver meaningful value from labels for regulatory teams

There are a multitude of pressures facing regulatory teams. Externally downward pricing pressure on products and evolving regulations globally mean teams must do more with less. Internally, teams can lack the resources to be as effective as they need to be..

Our Labeling Intelligence Hub can reduce your workload, by enabling effective identification of relevant and rich information from across key label sources.

Key benefits of natural language processing for drug label insights

Extracting rich insights from diverse drug label sources has never been easier.

  • Speed: Reduce the manual effort required to search, compare and extract  label intelligence
  • Convenient: Cost effective access to label information from an increasing number of multi-lingual drug label sources (e.g. FDA, EMA, France, Canada, UK)
  • Powerful: Use your own NLP-powered search, use pre-built searches, or the latest generative AI capabilities to quickly gain competitive insights
  • Trusted: Our embedded, award-winning NLP and comprehensive ontologies means you’ll extract the right terms in the right context to augment your label search
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IQVIA Labeling Intelligence Hub

Key features of the Labeling Intelligence Hub

Powered by hybrid natural language processing (NLP), our solution allows you to build your own label searches, deploy pre-built searches, or use the latest generative AI capabilities to ask questions and get relevant results to optimize your label writing and analytics.

Once you’ve found the labels you need, use the side-by-side comparison to assess differences across labels, and generative AI-enabled section creation to start your new label draft.

Regulatory Labeling

Regulatory and labeling teams need good access to global label data, for informed and data-driven lifecycle management, label authoring and labeling due diligence. This enables alignment of global and local regulatory strategies to meets regulatory and business requirements.

Safety

Product labels contain summaries of drug-related adverse events from preclinical and clinical development and post market surveillance. This landscape of safety data is valuable for safety teams to understand context of any signal, enable predictive risk models, compare ADRs for drugs in same class, and more

Medical

Medical affairs teams communicate the real-world benefits and use of product to prescribers, where label information can be combined with real world evidence, published research, and safety information, for a holistic view

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