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Gene Delivery and Gene Editing

Tech Session V: Gene Delivery and Gene Editing III

Enhancing mRNA-lipid nanoparticle prediction via the language model and multi-task learning

Thursday, July 17, 2025
11:27 AM – 11:38 AM EDT
Introduction:

Traditional screening of ionizable lipids of mRNA lipid nanoparticles (mRNA-LNPs) primarily relies on time-consuming and resource-intensive trial-and-error experiments. While machine learning approaches have offered promise in predicting the in vivo behavior of mRNA-LNPs, their applications are limited by small datasets.

Learning Objectives:

At the completion of this activity, participants will know
  • Explore the advanced AI techniques to facilitate the mRNA-LNP development in limited datasets
  • Learn how to enhance mRNA-LNP behavior prediction with correlated properties and multi-task learning
  • Identify key ionizable lipid substructures influencing in vivo behavior

    Oral Abstract Speaker(s)

  • YIYANG WU, ME

    PhD candidate
    University of Macau, China (People's Republic)