Technologies for Monoclonal Antibody Discovery and Development

Abstract

Monoclonal antibodies (mAbs) represent one of the most successful classes of biopharmaceuticals, with more than 100 approved for treating oncological, immunological, and infectious diseases. Antibody discovery and development have been driven by diverse methodologies. Classical strategies such as mouse hybridoma technology, phage display, transgenic mouse models, and single B cell isolation have enabled the generation of high-affinity therapeutic antibodies. Beyond binding affinity, recent innovations in combinatorial antibody libraries have facilitated the selection of functional antibodies within cellular environments, revealing their ability to act as agonists or antagonists and influence signal transduction pathways. These insights expand therapeutic applications by enabling modulation of complex cellular responses. Recent breakthroughs in artificial intelligence, involving antibody generation supported by rapidly growing antibody sequence and structure databases, are transforming computational protein design. This review highlights five major approaches (hybridoma technology, phage display, transgenic mouse models, and single B cell isolation, de novo antibody design) for antibody discovery and development. These approaches offer innovative strategies designed to accelerate the discovery process and enhance therapeutic outcomes for human diseases.