Transforming Drug Discovery with LLMs:

How to Stay on Top of the Capabilities Growth Curve


What to Expect

With advancements in AI, the application of LLMs carry the promise to become a game changer in the pharmaceutical industry, enabling swift, data-driven decision making, advancing research, and empowering scientists.
As a lot of effort across industry is being made on integrating and applying LLMs to work, but it is still challenging to formulate what true problem-solving capabilities and practical limitations of the new technology are and keep up with the rapid pace of developments in foundational models, associated tools and applications, infrastructure and services.
What you'll learn:
  • Latest Trends and Developments in LLMs: We will discuss the most recent advancements in Large Language Models and their application in the pharmaceutical industry.
  • Engineering Rigor in LLMs: Understand the engineering rigor necessary for building production-ready systems with LLMs. We will provide valuable insights into creating robust and reliable models.
  • Expecting the capability growth: Learn how to set up an effective benchmarking process to stay on top of rapid continuous improvement in the field and not miss a relevant application breakthrough
  • Relevant LLM Applications in Pharma: We'll review selected relevant LLM applications and their potential in Pharma, providing concrete examples of how these powerful tools can bring about transformative changes.
Whether you're a data scientist, a bioinformatics professional, a researcher or a strategic decision-maker in the drug discovery space, this webinar will provide you with insights on the most recent developments, challenges, and progress in LLMs as well as share with you some guidance and recommendations on how to engineer systems to adapt and onboard the rapid progress in the area.

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Meet the Speakers

Artur Saudabayev

Co-founder & CTO