AI and DNA-encoded libraries Synergy: Transforming Drug Discovery

Life Sciences, Drug Discovery & Development, Preclinical, Cell and Gene Therapy,
  • Wednesday, November 01, 2023

Discover a groundbreaking webinar delving into the integration of artificial intelligence (AI) and DNA-encoded libraries to accelerate drug discovery. AI has emerged as a transformative force in drug discovery. By analyzing vast datasets, AI can predict the properties and behavior of small molecules, accelerating the search for new medicines. However, AI is only as good as the data it learns from. This is where DNA-encoded libraries (DELs) come in. DNA-encoded library screening generates massive high-quality datasets to train AI models, enabling accurate predictions for drug hunters.

In this webinar, X-Chem will explore how the synergy between AI and DNA-encoded libraries is reshaping early-stage drug discovery and will walk through real-world case studies demonstrating AI’s ability to generate novel hits.

The featured speaker will also discuss how AI can rapidly predict pharmacological properties. By integrating AI with DNA-encoded libraries and proprietary data, drug hunters can be equipped with powerful new capabilities. Ultimately, the goal is a faster and more efficient discovery of high-quality leads. The combination of rich data from DNA-encoded libraries and the predictive power of AI stands to greatly accelerate the timeline from initial screening to pre-clinical candidates.

Join this webinar to learn how these powerful capabilities can be integrated and put into the hands of drug hunters to accelerate the process from screen to candidate.


Noor Shaker, X-Chem

Noor Shaker, Executive Business Development Consultant, X-Chem

Noor Shaker is a biotech entrepreneur and recognized healthcare innovator. Prior to Glamorous AI (acquired by X-Chem in October 2021), she was an assistant professor at Aalborg University. Noor is passionate about data and artificial intelligence (AI) and is on a mission to cure disease by pushing the boundaries for what is possible with AI.

She has a record of achievements in AI, including numerous papers published in the field and its application to drug discovery, as well as holding a number of AI patents. She sits on AI and diversity advisory boards for prestigious organizations and universities and is a recognized healthcare leader — she was one of the 2018 winners of Innovators Under 35 Europe from MIT Technology Review and named one of BBC’s 100 Women of 2019.

Message Presenter

Who Should Attend?

This webinar will appeal to professionals in pre-clinical drug discovery in the following roles:

  • Medicinal Chemists
  • Computational Chemists
  • Program Leaders/Researchers

What You Will Learn

Attendees will gain insights into:

  • DNA-encoded libraries (DEL) and how they generate high-quality data that is valuable for training AI models.
  • A combination of AI and DEL can enhance hit generation
  • AI’s ability to aid de novo hit generation (based on case studies), expanding on hits found through DEL screening and predicting pharmacological properties
  • AI platform integrates all these capabilities in an easy-to-use interface to enable drug hunters to do a better and faster drug discovery

Xtalks Partner


X-Chem is a leader in small molecule drug discovery services for pharmaceutical and biotech companies. As pioneers of DNA-encoded chemical library (DEL) technology, the company leverages its market-leading DEL platform to discover novel small molecule leads against challenging, high-value therapeutic targets. As experts in medicinal chemistry, X-Chem can take those leads and progress them to clinical candidates with unmatched speed. Throughout the process, X-Chem’s advanced proprietary artificial intelligence (AI) technology accelerates all steps in the process. X-Chem also provides libraries, reagents and informatic tools to allow DEL operators to get the most out of their DEL platform. X-Chem empowers its partners to effectively build drug pipelines from target to clinical candidate, enhanced with AI. For further information, please visit

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