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Key Takeaways: Scalable Data Strategies for Scientific AI-enabled Breakthroughs

Get the essentials from an expert discussion on AI featuring AWS and TetraScience.

Artificial intelligence (AI) stands on the brink of revolutionizing the biopharmaceutical industry. It promises to slash time to market, lower costs, mitigate risks, and create novel therapies. However, the main barrier to realizing these benefits is not the development of AI models but rather the quality and accessibility of the scientific data that feeds them.

The recent webinar "Scalable data strategies for scientific AI-enabled breakthroughs" featured insights from industry experts Naveen Kondapalli, Senior Vice President of Product and Engineering at TetraScience, and Himanshu Jain, Healthcare and Life Sciences Strategy Leader at AWS. They delved into the data challenges underlying scientific AI and discussed strategies to overcome them.

In this recap, we summarize four key takeaways from the conversation that will jumpstart your AI journey.

    Esther Howard Linkedin

    Director Solution Consulting, Tetrascience

    Richard leads Nexthink’s Solution Consulting team in North America. Richard has extensive experience leading software presales teams to deliver solutions in complex and challenging market environments, and has held senior solution consulting positions in companies such as Everbridge, BMC Software and Dell.

    Esther Howard Linkedin

    Director Solution Consulting, Tetrascience

    Richard leads Nexthink’s Solution Consulting team in North America. Richard has extensive experience leading software presales teams to deliver solutions in complex and challenging market environments, and has held senior solution consulting positions in companies such as Everbridge, BMC Software and Dell.

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