Collaboration identifies antibody drug candidates using AI  

Antiverse has partnered with a top 20 pharma company and has been successful in identifying antibody candidates for a target of interest, with greater diversity (2.3x) and accuracy compared to alternative bioinformatics pipeline selection methods. 

The sequencing 

Using Antiverse’s AI-Augmented Drug Discovery platform, 248 sequences were identified, of which over 230 were antibody binders. Five of these antibody candidates were found to be cross-reactive. 

The platform 

Antiverse is combining machine learning and phage display techniques to model antibody-antigen interactions. The current version of the platform uses next generation sequencing and AI to provide diverse antibody candidates for any given target.  

The technology is being developed to enable the development of drugs for “difficult” targets associated with cancer, heart, and lung diseases. The company aim for the platform to overcome limitations commonly associated with traditional screening including overcoming amplification bias which leads to diversity loss and selection bias which results in the loss of unique antibodies. 

Official comments 

Murat Tunaboylu, Chief Executive Officer of Antiverse, said: “We are pleased to collaborate with a top 20 pharma company on this discovery project. Our AI-powered antibody drug discovery platform successfully identified more binders with better diversity to state-of-the-art high-throughput colony picking and bioinformatics pipeline selection. Researchers can find more diverse antibodies by unlocking the full potential of their library/discovery process with our AI-augmented discovery platform and through our fee-for-service offering, we hope to partner with other biotech and pharma companies on projects to identify other challenging targets.” 

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