Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties

Animal immunization merges with innovative technologies: A new paradigm shift in antibody discovery

Animal-derived antibody sources, particularly, transgenic mice that are engineered with human immunoglobulin loci, along with advanced antibody generation technology platforms have facilitated the discoveries of human antibody therapeutics. For example, isolation of antigen-specific B cells, microfluidics, and next-generation sequencing have emerged as powerful tools for identifying and developing monoclonal antibodies (mAbs). These technologies enable not only antibody drug discovery but also lead to the understanding of B cell biology, immune mechanisms and immunogenetics of antibodies. In this perspective article, we discuss the scientific merits of animal immunization combined with advanced methods for antibody generation as compared to animal-free alternatives through in-vitro-generated antibody libraries. The knowledge gained from animal-derived antibodies concerning the recombinational diversity, somatic hypermutation patterns, and physiochemical properties is found more valuable and prerequisite for developing in vitro libraries, as well as artificial intelligence/machine learning methods to discover safe and effective mAbs.