Roche ML for Antibody Design
In a new two-year collaboration with Roche, the group will be supporting a Roche Postdoctoral Fellowship in the development of antibodies. We will make use of Roche’s existing antibody data to develop machine-learning models generating sequences of antibodies with desired biophysical properties. Our aims are to:
- Develop machine learning models that ingest in-house antibody engineering data on antibodies to generate novel sequences with increased likelihood of desired biophysical properties,
- Iteratively apply methods to antibody datasets,
- Collaborate with experimental teams to select and test model-generated candidate sequences in the wet lab,
- Embed machine learning models in discovery processes.