De novo prediction of therapeutic antibodies with deep learning

The limitations of drug development pipelines have been emphasised by the unprecedented demand for novel drug therapeutics, in the wake of the COVID-19 pandemic. Paramount to the development of novel drug therapeutics, is the identification of potential drug candidates: a process referred to as drug discovery. Drug discovery is still predominantly performed using in vitro and sometimes in vivo experimental approaches, which can incur a high financial cost and time requirement.

In this talk, I will discuss the application of state-of-the-art deep learning approaches for the rapid and low-cost identification of novel anti-SARS-CoV-2 therapeutic antibodies.