Chief Investigator:

Dr Sandy Hung

 

Co-Investigators:

Dr Rajendra KC, Jon Ruddle, Leszek Lisowski, Andrew Deans

 

Aim

To develop an enhanced viral vector-based delivery system for CRISPR tools to correct inherited retinal disease patient-specific mutation.


Methods

Utilizing directed evolution technology to select for lentiviruses with improved transduction efficiency in retina cells.

 

Key results

We have established the human donor retinal explant culture and mouse systems for the experiments.

• Designed and generated non-binding lentivirus controls

• Established flow cytometry selection systems and downstream processing and verification protocols.


Implications for Clinical Practice/Science and Future Research

This project addresses a critical challenge in personalized gene therapy through the development of improved delivery systems to enable more efficient targeting and transduction into retinal cells. The project is part of a larger scheme where the improved delivery candidates will be further tested in clinically relevant disease mutation models for inherited retinal diseases. Utilizing patient specific iPSC and mouse disease models will allow for accelerated preclinical assessment of correction in clinically relevant cell types and to identify potential safety issues.

Establishment of the pipeline in this proposal will allow for the rapid generation and testing of gene editors and delivery vectors for not only genetic diseases of the retina but can be further extended to genetic diseases in other cell types and organs.

 

Conclusion

We are currently still in the process of screening for the improved evolved lentiviruses. With the identification of good lentivirus candidates, we will move on to test the candidates for their ability to package gene editors and its ability to edit clinically relevant mutations.

Lay Summary of Outcomes

We aimed to develop improved gene therapy delivery systems that can package larger cargo and deliver to the disease affected cells in the eye with higher efficiency than currently available systems.