WATCH – Customer success story | rAAVen Therapeutics
Background
Adeno-associated viral vectors, or AAVs, are viruses that can transport therapeutic genes into the body for gene therapy. AAV2, for example, has demonstrated the ability to deliver a gene into retinal pigment epithelial cells to treat vision loss. Swedish biotech rAAVen Therapeutics aims to broaden the therapeutic scope of AAVs available for treating devastating neurological disorders like Alzheimer’s, Parkinson’s, and ALS, as well as to repair damaged organs in conditions like heart disease and muscular disorders. The team does this by modifying different viral vector candidates to enhance their ability to target specific tissues and deliver therapeutic genes more efficiently and safely than naturally occurring AAVs.
VUGENE’s solution
Selecting the right adenovirus for the right indication is complex work, and rAAVen’s scientists have so far screened millions of modified viruses, generating huge datasets. To parse through these datasets, the team recruited VUGENE to develop machine learning tools that extract valuable insights from the data.
Dr. Patrick Aldrin-Kirk, Chief Scientific Officer at rAAVen Therapeutics, explains that VUGENE’s bespoke tools are essential. “They really help us with sorting out our big datasets and the many different sequencing requirements that we have for screening our vectors,” he said.
“We are streamlining, automating, and making things much faster,” said Dr. Juozas Gordevičius, VUGENE’s Founder and Chief Technology Officer. “If you want to target a particular type of cell, we come back with a machine learning tool that says, ‘You have to build this viral sequence.’”
Cover photo credits: sripfoto / Adobe Stock
