ANTIBODY DISCOVERY AND OPTIMISATION BY RATIONAL DESIGN

Antibodies are key tools to address questions and enable discoveries in biomedical research, and are increasingly employed to diagnose and treat many diseases, including cancer and neurodegeneration.

By using a multidisciplinary approach that encompasses computational method development and in vitro experiments, we develop new data-driven technologies of rational antibody design at a computer. Our specific angle to antibody design is to exploit the increasing amount of available high quality structural data and biophysical measurements to develop empirical combinatorial approaches, sometimes leveraging machine learning techniques. This strategy is allowing us to introduce fast and reliable methods to deign antibody binding, and to predict essential biophysical properties for antibody development, including solubility and stability.

Our technologies are beginning to enable the discovery of antibodies against therapeutically relevant targets challenging to access with conventional approaches, and to provide novel time- and cost-effective alternatives. We also collaborate with the pharmaceutical industry and other academic groups in the Department and outside.