In silico discovery platform drives forward Bavarian Nordic's MRSA vaccine program

Bavarian Nordic has signed up to work with Evaxion Biotech on the development of a vaccine against methicillin-resistant Staphylococcus aureus (MRSA). The project is underpinned by Eden Technology, an in silico vaccine discovery platform that combines data, algorithms and deep learning to unearth antigens.

Eden, which is Evaxion's contribution to the alliance, uses amino acid sequences from the proteome of a bacteria as its raw materials. When sequences are fed into Eden, the platform begins a two-day analytical process, at the end of which Evaxion has a list of proteins that are predicted to trigger an immune response. Armed with this information, Evaxion thinks it can create vaccines that result in a strong, broadly protective immune response. And, having had a look at the preclinical efficacy data, Bavarian Nordic has become enough of a believer to sign up to work with Evaxion.

Bavarian Nordic will use its engineering and manufacturing capabilities to turn the in silico work by Evaxion into a recombinant MVA-BN-based vaccine candidate. The Technical University of Denmark, the third partner in the collaboration, will then run further preclinical tests, setting Bavarian Nordic up to move the vaccine into Phase I in 2019. Innovation Fund Denmark is chipping in $2.5 million to finance the work. Bavarian Nordic will use some of the money in the manufacture of the vaccine candidates.

Having got the project started using its Eden Technology platform, Evaxion will leave its two partners to advance the vaccine. Evaxion has programs in its in-house pipeline to occupy its time. Having set up shop in 2010, Evaxion now lists 5 products in its pipeline, the most advanced of which are in preclinical development. The pipeline is built upon the work of Andreas Mattsson, who spent 6 years developing in silico platforms at Novo Nordisk ($NVO) before co-founding Evaxion. Mattsson has used deep learning to train Eden to identify novel protective protein antigens in amino acid data. 

- read the release