Machine Learning and Artificial Intelligence in Antibody Discovery: Breakthroughs, Blind Spots, and the Road Ahead To date, Machine Learning (ML) has proved itself as a powerful tool in improving the workflow and timelines of antibody discovery— for instance, ranking,...
How VHHs Can Redefine the Next Generation of ADCs Introduction Antibody–drug conjugates (ADCs) have transformed oncology by combining the specificity of antibodies with the potency of cytotoxic payloads. Over time, ADCs have improved greatly, evolving from...
The Proteins We Work With: A Guide to Supported Antigen Materials Introduction In the pursuit of new therapeutics, discovery teams encounter a huge variety of target proteins – from simple soluble enzymes to complex multi-pass receptors. Many of these targets...
Building Smarter Therapeutics with VHH Bolt-Ons Single-domain antibodies derived from camelids, also known as VHHs or nanobodies, are highly adaptable binding domains widely used in protein engineering. They were pioneered by Raymond Hamers at Vrije Universiteit...
CIS Display™ vs. Phage Display: Choosing the Right Fit for VHH or Peptide Discovery Choosing the right display technology is a critical decision in therapeutic and diagnostic discovery procedures. This article compares CIS Display™ with Phage Display, focusing on...
NGS in Antibody Discovery: How Deep is Your Sequence? Next-generation sequencing (NGS) has revolutionized antibody discovery by enabling high-depth analysis of diverse libraries, surpassing the limitations of traditional methods like Sanger sequencing. This article...
