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Driving Life Sciences Innovation in R&D Through Artificial Intelligence and Robotic Process Automation

概要

This Solution Provider Webinar is brought to you by DIA in cooperation with

ArisGlobal

With the rising costs and complexities involved in bringing life sciences products to market, both drug and medical device manufacturers are re-examining how they conduct their business operations and how automation technologies can help play a role.

The cost to research and develop new drugs is consistently escalating and this, on top of other challenges like outcome-based payment for products, is increasing the need for automation within the industry.

According to the Tufts Center for the Study of Drug Development, it currently costs $2.6 billion to develop a prescription drug that gains market approval. At the industry’s current pace, that figure will explode to $32 billion by 2050.

Attend this webinar to hear leading industry experts and Stefan Prebil, Pharma Industry Practice Leader at Appian, as they dive into how the next generation of technologies such as Artificial Intelligence (AI), Robotic Process Automation (RPA), and Internet of Things (IoT) are offering opportunities to dramatically increase efficiency while cutting costs in R&D projects and processes.


Continuing Education Credits are not available for this event.

特集トピック

  • Life Sciences research and development
  • Artificial Intelligence (AI)
  • Robotic Process Automation (RPA)
  • Business Process Management (BPM)
  • Internet of Things (IoT)
  • Digital Transformation Platforms

参加対象

Professionals who work in the area of:
  • Head / Directors / Managers of R&D
  • Head / Managers of Clinical Trials
  • Head of Pharmacovigilance / Drug Safety
  • CTO / CIO

学習目的

At the conclusion of this webinar, participants should be able to:
  • Describe how AI and RPA can support setup in clinical trials/study start-up
  • Explain how these technologies can help reduce complexity for faster, more accurate outcomes, In collaboration with an enterprise automation platform
  • Discuss how Automated analytics of existing big data in clinical trials can boost results and focus study set-ups/endpoints for new trials
  • Describe how Intelligent Automation in Safety Information Tracking can unlock patient value with:
    • Automated scanning of external safety information
    • AI supported safety information on patient conditions

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