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Antibody-based therapies provide highly specific treatments for various diseases. Among these, VHH antibodies, derived from camelids, have garnered significant attention due to their unique properties. Unlike conventional antibodies, which are composed of two heavy and two light chains, VHH antibodies consist of a single variable heavy chain domain. Previously, scientists viewed single-chain variable fragments (scFvs)—comprising VH […]

Biologics, particularly antibodies, have become indispensable in biomedical research and therapeutic development. Research-use-only (RUO) biologics play a pivotal role in preclinical studies, providing researchers with the necessary tools to explore antibody functions and therapeutic potential in vivo. RUO biologics are products intended exclusively for laboratory research and preclinical studies. Unlike clinical-grade biologics, RUO products are

Antibody labeling is an invaluable tool for clinical and research experiments, allowing scientists to detect and visualize the location of specific antigens in biological samples such as cells, tissues, or proteins. It is often used in conjunction with an immunoassay, and both primary and secondary antibodies can be labeled, depending on research needs. The primary

Technological advancements in recent years, such as next-generation sequencing, have made it possible for large antibody repertoire databases to exist. Databases provide an invaluable resource for researchers worldwide, providing scientists with insights into antibody structure, function, and design. This article will provide an overview and examples for sequence, antibody structure, therapeutic, and experimental databases, and

Artificial intelligence (AI) and computational methods are a powerful tool for antibody discovery and engineering. Despite historical prevalence in small molecule-related applications, AI is progressively being utilized in the discovery and advancement of therapeutic antibodies, backed by the surge in computational power and innovative algorithms, with an increasing amount of data obtained through next-generation sequencing

Although the incorporation of artificial intelligence (AI) in antibody research is still in its early stages, research scientists studying AI, bioinformatics, and protein engineering have used AI models to demonstrate its potential to transform the R&D space of the biotech and pharmaceutical industries. The accessibility of high-throughput experimental data has also enabled a shift in

Once potential therapeutic antibodies are engineered, they undergo rigorous screening and selection to identify the most promising candidates. Screening Methods Traditionally, screening for potential therapeutic antibodies includes enzyme-linked immunosorbent assay (ELISA), a versatile tool measuring the binding affinity of antibodies to their target antigens. This provides valuable insights into the strength of their interaction. Surface

Therapeutic antibodies have revolutionized treatment paradigms across a range of diseases, including cancers, autoimmune disorders, and infectious diseases. Their production is a complex, multi-step process that begins with the development of specialized cell lines and extends through to careful optimization of growth conditions to maximize yield. Cell Line Development Among the host cells used for

Afucosylated antibodies are characterized by the absence of fucose sugar residues on their Fc (fragment crystallizable) region. This modification has major implications for the antibody’s functionality, particularly in enhancing antibody-dependent cellular cytotoxicity (ADCC).   The primary mechanism of action of afucosylated antibodies is through enhanced ADCC. ADCC is a critical immune response where immune cells,

Before the road towards clinical trials, the developability properties of therapeutic antibodies need to be evaluated. Antibody molecules are assessed for developability characteristics including aggregation, immunogenicity, pharmacokinetic clearance, viscosity, and half-life span.1 This is important to ensure a stable and efficacious drug before clinical trials. These properties can be understood through in silico methods, such as