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Generative AI in Healthcare & Life Sciences

Gen AI is transforming the biotech, pharma, and MedTech markets. Discover 4 strategies you can implement, today.

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Race to keep up with drug discovery? Or make it business as usual?

The healthcare and life sciences industry is under rapid transformation. What companies once struggled with is now being done more efficiently and less costly. They are predicting protein structures more accurately and understanding diseases better than ever before.

Gen AI is allowing companies to tap into invaluable data to find accurate insights faster, enhance drug discovery, and streamline internal processes for maximum efficiency.

The outcome? Increased revenue and decreased internal costs.

If you’re in biotechnology, pharmaceuticals, or MedTech, this guide will help you accelerate your gen AI journey with strategies on how to:

  • Personalize experiences from research to insights
  • Generate interoperable insights
  • Drive sustainable and efficient operations
  • Enrich customer interactions

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$15-35 billion Gen AI potential value across the life sciences industry in North America1


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OPTIONAL EYEBROW

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Gen AI on Google Cloud

Deliver gen AI powered experiences quickly, efficiently, and responsibly with Google’s most advanced technology and models.

The business value of gen AI

Find out how gen AI is being used in compelling ways to generate revenue and cut costs across industries.

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ALL DAY TRACKS

Day 1 Agenda

  • 8:30 AM–09:30 AM
    Registrations
  • 9:30 AM–09:40 AM
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    Fast analytics at scale with Google BigQuery
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  • 10:40 AM–11:00 AM
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  • 11:40 AM–12:40 PM
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  • 1:00 PM–01:20 PM
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  • 1:40 PM–02:40 PM
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  • 2:40 PM–03:40 PM
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Day 2 Agenda

  • 8:30 AM–09:30 AM
    Registrations
  • 9:30 AM–09:40 AM
    Opening Keynote: Lorem ipsum dolor sit
    Firstname Lastname, Position, Company XYZ
  • 9:40 AM–10:00 AM
    Pushing the limits of BigQuery with Kabam
    Firstname Lastname, Position, Company XYZ
  • 10:00 AM–10:40 AM
    Fast analytics at scale with Google BigQuery
    Speaker: Name, Title, Organization
  • 10:40 AM–11:00 AM
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  • 11:40 AM–12:40 PM
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Day 3 Agenda

  • 8:30 AM–09:30 AM
    Registrations
  • 9:30 AM–09:40 AM
    Opening Keynote: Lorem ipsum dolor sit
    Firstname Lastname, Position, Company XYZ
  • 9:40 AM–10:00 AM
    Pushing the limits of BigQuery with Kabam
    Firstname Lastname, Position, Company XYZ
  • 10:00 AM–10:40 AM
    Fast analytics at scale with Google BigQuery
    Speaker: Name, Title, Organization
  • 10:40 AM–11:00 AM
    Break
  • 11:00 AM–11:20 AM
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  • 11:40 AM–12:40 PM
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  • 1:20 PM–01:40 PM
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  • 1:40 PM–02:40 PM
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Agenda

  • 8:30 AM–09:30 AM
    Registrations
  • 9:30 AM–09:40 AM
    Opening Keynote: Lorem ipsum dolor sit
    Firstname Lastname, Position, Company XYZ
  • 9:40 AM–10:00 AM
    Pushing the limits of BigQuery with Kabam
    Firstname Lastname, Position, Company XYZ
  • 10:00 AM–10:40 AM
    Fast analytics at scale with Google BigQuery
    Speaker: Name, Title, Organization
  • 10:40 AM–11:00 AM
    Break
  • 11:00 AM–11:20 AM
    Session Title
    Speaker: Name, Title, Organization
  • 11:20 AM–11:40 AM
    Session Title
    Speaker: Name, Title, Organization
  • 11:40 AM–12:40 PM
    Lunch
  • 12:40 PM–01:00 PM
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  • 1:00 PM–01:20 PM
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  • 1:20 PM–01:40 PM
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  • 1:40 PM–02:40 PM
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    Happy hour

Track 1

Track 2

Track 3

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    Registrations
    Registrations
    Registrations
  • 9:30 AM–09:40 AM
    Opening Keynote: Lorem ipsum dolor sit
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    Opening Keynote: Lorem ipsum dolor sit
    Firstname Lastname, Position, Company XYZ
    Opening Keynote: Lorem ipsum dolor sit
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  • 9:40 AM–10:00 AM
    Pushing the limits of BigQuery with Kabam
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    Pushing the limits of BigQuery with Kabam
    Firstname Lastname, Position, Company XYZ
    Pushing the limits of BigQuery with Kabam
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Agenda

Track 1

Track 2

  • 8:30 AM–09:30 AM
    Registrations
    Registrations
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    Opening Keynote: Lorem ipsum dolor sit
    Firstname Lastname, Position, Company XYZ
    Opening Keynote: Lorem ipsum dolor sit
    Firstname Lastname, Position, Company XYZ
  • 9:40 AM–10:00 AM
    Pushing the limits of BigQuery with Kabam
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    Pushing the limits of BigQuery with Kabam
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