Overcoming Immunological Challenges Limiting Capsid-Mediated Gene Therapy With Machine Learning.

Journal: Frontiers in immunology
PMID:

Abstract

A key hurdle to making adeno-associated virus (AAV) capsid mediated gene therapy broadly beneficial to all patients is overcoming pre-existing and therapy-induced immune responses to these vectors. Recent advances in high-throughput DNA synthesis, multiplexing and sequencing technologies have accelerated engineering of improved capsid properties such as production yield, packaging efficiency, biodistribution and transduction efficiency. Here we outline how machine learning, advances in viral immunology, and high-throughput measurements can enable engineering of a new generation of de-immunized capsids beyond the antigenic landscape of natural AAVs, towards expanding the therapeutic reach of gene therapy.

Authors

  • Anna Z Wec
    Applied Biology, Dyno Therapeutics Inc, Cambridge, MA, United States.
  • Kathy S Lin
    Data Science, Dyno Therapeutics Inc, Cambridge, MA, United States.
  • Jamie C Kwasnieski
    Applied Biology, Dyno Therapeutics Inc, Cambridge, MA, United States.
  • Sam Sinai
    Data Science, Dyno Therapeutics Inc, Cambridge, MA, United States.
  • Jeff Gerold
    Data Science, Dyno Therapeutics Inc, Cambridge, MA, United States.
  • Eric D Kelsic
    Applied Biology, Dyno Therapeutics Inc, Cambridge, MA, United States.