Objective

Therapeutic monoclonal antibodies must not only bind to their target but must also be free from 'developability issues', such as poor stability or high levels of aggregation. Both of these properties (binding and ‘developability’) depend upon the structure of the antibibody. In this talk I will provide an overview of the structural antibody database (SAbDab) and the computational antibody prediction toolset SAbPred for modelling and designing antibodies. I will show how predicted structural information can enrich data from next generation sequencing experiments. In particular describing our freely available new database - observed antibody space that contains over half a billion antibody sequences. In the last part of the talk I will describe – TAP our novel therapeutic antibody profiler that provides five computational developability guidelines.