Resource Overview:
For scientists engaged in drug discovery, particularly those dedicated to combating emerging infectious diseases, this application note offers insights into modern methodologies for optimal antibody selection during development. It details a cutting-edge study focused on the high-throughput screening of monoclonal antibodies targeting the highly pathogenic avian influenza strain H5N1, clade 2.3.4.4b, which poses a significant threat due to its potential for cross-species transmission, including humans. Furthermore, the study aims to develop robust immunoassay tools to advance research efforts against HPAI H5N1, enhancing our ability to effectively combat this significant threat.
Rockland Immunochemicals, Inc. has contributed significantly to advancing the methodologies outlined in this application note. Their expertise in producing well-characterized antibodies supports advanced screening processes, facilitating the selection of fit-for-purpose clones for further development. Rockland has made a subset of H5N1 2.3.4.4b HA antibodies commercially available here.
Key Takeaways:
- Advanced Screening Techniques: Utilizing the Octet® RH96 platform for label-free biolayer interferometry (BLI), the study provides a robust method for real-time assessment of antibody libraries even with crude or non-purified samples.
- Automation and Efficiency: The integration of a Biosero® GoSimple™ workcell facilitates automated workflows, enabling high-throughput screening and unattended operation to maximize productivity.
- Comprehensive Antibody Characterization: Early screening for critical antibody attributes such as titer, binding kinetics, and epitope binning allows for the identification of non-competing monoclonal antibodies, paving the way for further therapeutic development.
- Impact on Therapeutic Development: This approach not only accelerates the antibody discovery process but also supports the development of vaccines and therapeutics essential for responding to emerging pathogens.
Resource Details:
- Document Type: Application Note
- Page Count: 10
- Read Time: 22 minutes