Custom VHHs are traditionally generated by inoculating camelids (typically alpacas or llamas) with a target antigen of interest, extracting the animal’s heavy chain antibody (HCAb) library, and panning for binders. However, this approach has several significant drawbacks, including the long VHH development timeframe required (about six months), the expense ($50K or more per analyte), and the disfavor animal products (including antibodies) can illicit if alternative methods exist. The time and cost risks are amplified significantly by the all-too-common result that a VHH binder of sufficient affinity or specificity is not found, which is generally known only after the project timeline has fully elapsed and the money has been spent.

QBI’s alternative, far superior to animal inoculation, is a fully synthetic, randomized VHH library containing 10¹² unique members. To create the library, QBI researchers used degenerate polymerases to randomize the three VHH CDRs from multiple framework regions. These CDRs are a subset of the VHH domain and the most variable portion of a VHH, the theoretical variability of which in our synthetic library generally exceeds that found in animals. This approach takes advantage of the nearly limitless binding potential of VHHs, the foundation of an entirely new VHH discovery paradigm.

QBI deploys multiplexed next generation sequencing (NGS) technologies on an advanced, in-house designed computational platform to confirm library diversity and characterize the sequence distributions of functionally expressed VHHs found to bind to client-submitted samples. QBI’s unique library, combined with state-of-the-art NGS technologies that apply machine learning based on extensive training, can parse VHH interaction data to enhance the discovery of candidates with high affinity and high specificity binding to target antigens.