Antibody engineering by combining genome editing, deep sequencing, and deep learning

Monoclonal antibodies are one of the fastest growing classes of therapeutic drugs in today’s pharmaceutical market because of their uses in a wide-range of disease indications. Even with their unparalleled success, therapeutic antibody engineering and optimization is still a slow and disjointed process which relies on a multitude of experimental approaches that are both labor and resource intensive. By combining the three most impactful techniques in life sciences in the past 20 years: 1) genome editing, 2) deep sequencing, and 3) deep learning, we move beyond traditional experimental screening approaches and have developed a fundamentally new approach to augment the therapeutic antibody engineering and optimization process. One of the major issues associated with antibody engineering is the fact it relies extensively on directed evolution approaches, which are typically constrained to screening systems of phage or yeast display. These microbial expression hosts are in large part utilized because of their ability to stably replicate plasmid DNA and therefore accommodate large recombinant libraries of antibody variants. However, drawbacks of phage and yeast are that they lack the capacity to express full-length antibody molecules or provide post-translational modifications (e.g., glycosylation). Since nearly all therapeutic antibodies are ultimately expressed in full-length format in mammalian cells, phage- and yeast-derived antibodies often have different biophysical properties that require additional optimization when transferred to mammalian cells. In this thesis, I describe a novel approach to engineering antibodies directly in mammalian cells by taking advantage of recent advances in genome editing, name CRISPR-Cas9. We developed homology-directed mutagenesis, a novel method for the targeted mutagenesis of genes directly in the genome of mammalian cells. By applying this technique to a previously developed, mammalian-based antibody expression and display platform, we are now able to engineer and optimize ...