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As many people know, it can take 10-12 years and $1.5B to $3B to bring a new drug to market, with data from the Centers for Medical Research (CMR) showing that 90% of drugs entering the clinic fail before launch.  Although drugs can fail for many reasons, like safety issues and commercial viability, the inability to show drug efficacy is the leading cause of failure in Phase 2 and Phase 3 trials.  Nearly 40% of drugs that fail to show efficacy were against drug targets that didn’t have a clear linkage to the disease.  Lack of access to well-documented animal models was also a contributing cause.  In addition, 29% of the failure was attributed to poor compound selection.

This GEN webinar will focus on new tools and techniques for target identification and lead detection that harness the power of diverse data sources, advanced analytics, and visualizations.  With these tools, researchers may soon be able to eliminate failure due to erroneous target identification, allowing them to provide better preclinical validation earlier and start with much better lead compounds.

Who Should Attend

  • Drug discovery scientists
  • Researchers interested in target druggability
  • Translational research scientists
  • Pharmacologists
  • Medicinal chemists

You Will Learn How to

  • Establish a clear link between the target and disease
  • Use competitive intelligence to understand the disease and the target landscape
  • Identify animal models that show a clear link between the animal model and the human disease
  • Use previous chemistry knowledge to find lead molecules

Produced with support from:

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Richard Harrison, Ph.D.
Chief Scientific Officer,
Clarivate Analytics

Carlos Faerman, Ph.D.
Senior Scientist,

Matthew Wampole, Ph.D.
Senior Solutions Scientist,
Clarivate Analytics