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Meet Biorelate at upcoming biopharma conferences

Mira Nair

'The potential of GenAI and LLMs to transform drug development.' Register for our upcoming panel webinar with Novartis, Boehringer Ingelheim and Grünenthal on October 17 2023 : Registration (gotowebinar.com)

Even if you can't attend, approved registrants will be automatically sent a link to the recording after the event.

Meet Biorelate at the following conferences in 2023:

BioTechX USA, September 6-7th, 2023, Santa Clara, CA. Speaking on Weds Sept 6th at 12.35pm, Bionformatics Track. Meet us at Booth #426

InnovatePharmaHealthcare 2023, September 11-12th, London, UK. Speaking on Monday Sept 11th at 12.10pm. Meet us at Booth #8

BioTechX Europe, October 4-6th, 2023, Basel.  Speaking on Weds October 4th at 3.30pm, Bionformatics Track. Meet us at Booth #1010

Festival of Biologics, October 10-12th, 2023, Basel.

Pistoia Alliance's Collaborate. Innovate. Educate. Conference, November 14-15th, 2023, Boston, MA.

AI Driven Drug Discovery, December 5-6th, 2023 Boston, MA. Speaking on Tues, December 5th.

Festival of Genomics and Biodata, January 24-25th, 2024, London, speaking Weds Jan 24 at 12pm, Booth # TBD.

Our talk at these conferences will cover:

Cause-and-Effect to Empower Drug Discovery In A Generative AI World

  • Mining published biomedical research plays a crucial role in providing valuable knowledge for generating new hypotheses and enhancing drug discovery through explainability.
  • By incorporating cause-and-effect data into knowledge graphs, researchers can access unique insights that arise when data is aggregated in this manner.
  • The emergence of generative AI technologies has revolutionized the way we interact with data and explore its potential applications in drug discovery.
  • This talk aims to demonstrate the power of advanced cause-and-effect capturing methods, coupled with generative AI (genAI), in facilitating groundbreaking conclusions for drug discovery.
  • We believe that when combined together these technologies allow for more efficient and targeted experimentation, potentially accelerating the development of novel treatments and therapies



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