AI selects promising viral vectors for gene therapy

Scientists from the University of Pittsburgh have developed artificial intelligence (AI) that helps to identify suitable viral vectors for delivering gene therapy to the retina.

The research, which was published in eLife, describes how a computational platform was developed using single-cell RNA sequencing to quickly decide which adeno-associated virus vector (AAV) is best suited to delivering a gene therapy to a specific part of the retina.

The platform, named scAAVengr, has the potential to speed up a process that would traditionally take years.

Leah Byrne, assistant professor of ophthalmology at University of Pittsburgh, highlighted that the field of vision restoration has entered a new era.

“Many patients have received effective treatment for the very first time. Because of that, the potential of our new platform is thrilling it will allow us to translate emergent therapies that are already working for some patients into the clinic much more rapidly," she said.

Byrne noted that the computational platform could have applications not only in vision restoration, but other fields.

"Rapidly developing fields of gene editing and optogenetics all rely on efficient gene delivery, so the ability to quickly and strategically choose the delivery vectors would be an exciting leap forward," she said.