Roche tasks Avista with scAAVenging for better eye disease gene therapy vectors

Roche’s hunt for better eye disease gene therapy vectors has led to Avista Therapeutics. In a heavily backloaded deal, the Swiss Big Pharma has offered up $1 billion to secure the right to assess and license AAV capsids developed by Avista. 

The startup spun out of the University of Pittsburgh Medical Center to build on the research of Leah Byrne, Ph.D., Jose Sahel, M.D., and Paul Sieving, M.D., Ph.D., a trio of researchers whose work has previously spawned biotechs including Adverum Biotechnologies, Fovea Pharmaceuticals and GenSight Biologics. Last year, Byrne and Sahel co-authored a paper about scAAVengr, the platform that underpins Avista.

Using scAAVengr, an abbreviation of single-cell AAV engineering pipeline, the researchers quantified the ability of naturally occurring and newly engineered AAVs to mediate gene expression in primates. The study pointed to the potential for scAAVengr to rank AAV vector efficiency across all cell types. 

“Traditional therapies for retinal dystrophies address only symptoms and complications, neglecting the underlying biology of the diseases, and while current vector technologies hold promise, they have been greatly limited in their ability to target key cell types across the retina. Avista was founded to solve this problem,” Avista CEO Robert Lin, Ph.D., said in a statement. 

Roche sees promise in the approach, leading it to pay $7.5 million upfront to work with Avista. The deal tasks the biotech with using scAAVengr to develop intravitreal AAV capsids that match Roche’s capsid profile. If Roche takes up its right to license the vectors, it will handle further work, from preclinical to commercialization, and hand over milestones that could swell the deal value to north of $1 billion. 

The deal positions Avista to validate its technology in a Big Pharma partnership while separately working on its internal pipeline. By tagging AAV vectors with genetic barcodes, scAAVengr enables Avista to track and quantify multiple vectors simultaneously in cells and animal models. The quantification supports the ranking of the vectors by their ability to infect different cell types and deliver their genetic payloads.