Monoclonal antibodies have taken a lead role in the drug landscape in recent years, in large part due to their potential in immuno-oncology, with global sales in monoclonal antibody therapeutics steadily increasing. Current early-stage antibody drug development relies heavily on time- and cost-intensive experimental screens.<br><br>
In my research, I aim to develop machine learning methods, with a particular focus on deep learning approaches, for the in-silico predictions of antibody properties from sequence or structure, in order to enable rapid explorations of the antibody space for drug development purposes.