Rabbits transgenic for human IgG genes recapitulating rabbit B-cell biology to generate human antibodies of high specificity and affinity

Prediction of polyspecificity from antibody sequence data by machine learning

Antibodies are generated with great diversity in nature resulting in a set of molecules, each optimized to bind a specific target. Taking advantage of their diversity and specificity, antibodies make up for a large part of recently developed biologic drugs. For therapeutic use antibodies need to fulfill several criteria to be safe and efficient. Polyspecific antibodies can bind structurally unrelated molecules in addition to their main target, which can lead to side effects and decreased efficacy in a therapeutic setting, for example via reduction of effective drug levels. Therefore, we created a neural-network-based model to predict polyspecificity of antibodies using the heavy chain variable region sequence as input. We devised a strategy for enriching antibodies from an immunization campaign either for antigen-specific or polyspecific binding properties, followed by generation of a large sequencing data set for training and cross-validation of the model. We identified important physico-chemical features influencing polyspecificity by investigating the behaviour of this model. This work is a machine-learning-based approach to polyspecificity prediction and, besides increasing our understanding of polyspecificity, it might contribute to therapeutic antibody development.

Assessing developability early in the discovery process for novel biologics

Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

Breaking barriers in antibody discovery: harnessing divergent species for accessing difficult and conserved drug targets

To exploit highly conserved and difficult drug targets, including multipass membrane proteins, monoclonal antibody discovery efforts increasingly rely on the advantages offered by divergent species such as rabbits, camelids, and chickens. Here, we provide an overview of antibody discovery technologies, analyze gaps in therapeutic antibodies that stem from the historic use of mice, and examine opportunities to exploit previously inaccessible targets through discovery now possible in alternate species. We summarize the clinical development of antibodies raised from divergent species, discussing how these animals enable robust immune responses against highly conserved binding sites and yield antibodies capable of penetrating functional pockets via long HCDR3 regions. We also discuss the value of pan-reactive molecules often produced by these hosts, and how these antibodies can be tested in accessible animal models, offering a faster path to clinical development.

Retrospective analysis of the preparation and application of immunotherapy in cancer treatment (Review)

Monoclonal antibody technology plays a vital role in biomedical and immunotherapy, which greatly promotes the study of the structure and function of genes and proteins. To date, monoclonal antibodies have gone through four stages: murine monoclonal antibody, chimeric monoclonal antibody, humanised monoclonal antibody and fully human monoclonal antibody; thousands of monoclonal antibodies have been used in the fields of biology and medicine, playing a special role in the pathogenesis, diagnosis and treatment of disease. In this review, we compare the advantages and disadvantages of hybridoma technology, phage display technology, ribosome display technology, transgenic mouse technology, single B cell monoclonal antibody generation technologies, and forecast the promising applications of these technologies in clinical medicine, disease diagnosis and tumour treatment.