Generative Machine Learning Enables DGuide RNA Design for Precise RNA Editing

Time: 12:15 pm
day: Day Two


  • The therapeutic potential of recruiting endogenous ADAR for RNA editing is hindered by its natural preference to edit adenosines within certain sequence contexts and its proclivity to edit multiple adenosines in a dsRNA substrate
  • Using high-throughput screening and structurally-aware generative AI, we can rapidly design gRNAs that recruit ADAR to efficiently and specifically edit any disease target of interest, regardless of its sequence context