VHH / Nanobody Discovery Service
Pre-humanised phage display library · CAAD lead optimisation · From sequence to characterised lead in ~4 months
Overview
Single-domain antibodies (VHHs, also known as nanobodies) derived from camelid heavy-chain-only immunoglobulins offer a compelling combination of small size (~15 kDa), high stability, deep tissue penetration, and access to epitopes that are sterically inaccessible to conventional IgG antibodies. These properties make VHHs ideal building blocks for bispecific and multispecific therapeutic formats, inhaled or intranasal delivery, enzyme inhibitors, and imaging agents.
ICDMO's VHH discovery platform is built around a pre-humanised phage display library constructed from 65 naïve llamas, with a diversity of 1×10¹⁰ unique clones. By replacing llama framework residues with human germline sequences at the library construction stage — rather than after lead selection — we eliminate the 3–4 month humanisation step that is unavoidable with conventional llama immunisation workflows. The result is a fully characterised, humanised lead antibody in approximately 4 months from project initiation.
Lead optimisation and multi-specific format assembly are guided by Computer-Aided Antibody Design (CAAD), which applies structural modeling, binding affinity prediction, and immunogenicity analysis to rank candidates and design VHH-Fc, bispecific (BsAb), and trispecific (TriAb) constructs with optimal geometry and cooperativity.
Platform Highlights
65
Naïve Llamas
PBMC repertoire sourced from 65 non-immunised llamas to maximise CDR diversity
1×10¹⁰
Library Size
Largest pre-humanised VHH phage display library available for therapeutic discovery
>15
Case Studies
Validated across oncology, virology, immunology and GPCR targets
~4
Months to Lead
Skip immunisation and humanisation — deliver characterised leads in ~4 months
Time Savings vs. Traditional Workflow
| Workflow Step | Traditional Technology | ICDMO Pre-humanised VHH Library |
|---|---|---|
| Immunisation | ~2–3 months | ✓ N/A — not required |
| VHH library construction | ~1 month | ✓ N/A — library ready |
| Panning & screening | ~1 month | ~1 month |
| Lead selection | ~1 month | ~1 month |
| Lead characterisation | ~2 months | ~2 months |
| Lead humanisation | ~3–4 months | ✓ N/A — pre-humanised |
| Total Time | ~10–12 months | ~4 months! |
Save 6 to 8 months with ICDMO's pre-humanised VHH platform!
Discovery Workflow
The ICDMO VHH discovery workflow integrates pre-humanised library construction, multi-strategy phage panning, format engineering, and computer-aided lead optimisation into an end-to-end service:
65 Llama PBMC Preparation
PBMCs isolated from 65 naïve llamas; IgG heavy-chain-only B cells enriched
→
VHH cDNA Amplification
RT-PCR amplification of VHH-encoding cDNA from total B-cell RNA
→
Pre-humanised VHH Library (1×10¹⁰)
Llama FRs replaced with human germline FRs; CDR1/2/3 shuffled via overlapping PCR
VHH Phage Panning (3 rounds)
P: Recombinant Protein Panning
Three rounds of panning against purified recombinant antigen protein. Optimal for well-characterised, soluble extracellular domains.
C: Cell-Based Panning
Panning directly on antigen-expressing cells. Enables discovery of VHHs that recognise native conformational epitopes under physiological membrane context.
B: Biotinylated Antigen Panning
Panning with streptavidin-bead-captured biotinylated antigen. Provides controlled antigen orientation and improved sensitivity for low-density epitopes.
Panning strategy combinations (PPP, CCC, BBB, BBC, BCC, PCC…) selected based on antigen type and target epitope requirements.
Format Engineering
VHH · VHH-Fc · Bispecific (BsAb) · Trispecific (TriAb) — format selected based on MOA and clinical indication
→
Computer-Aided Antibody Design (CAAD)
Lead selection and ranking by predicted affinity, stability, immunogenicity and manufacturability; multi-specific structural assembly
Panning Strategy Selection Guide
P
Recombinant Protein Panning (PPP)
Three rounds of panning against purified recombinant antigen protein. Optimal for well-characterised, soluble extracellular domains.
C
Cell-Based Panning (CCC)
Panning directly on antigen-expressing cells. Enables discovery of VHHs that recognise native conformational epitopes under physiological membrane context.
B
Biotinylated Antigen Panning (BBB)
Panning with streptavidin-bead-captured biotinylated antigen. Provides controlled antigen orientation and improved sensitivity for low-density epitopes.
Case Studies
The following validated studies demonstrate the breadth of ICDMO's VHH discovery platform across antiviral therapy, immuno-oncology T-cell engagement, and epitope-selective membrane protein targeting.
Case Study 1
World's First Trispecific Nanobody Targeting SARS-CoV-2 and Its Variants
A trispecific VHH-Fc antibody was engineered to simultaneously engage three distinct epitopes on the SARS-CoV-2 spike protein, including receptor-binding domains targeted by multiple circulating variants. By covering multiple non-overlapping epitopes, the trispecific design maintains broad-spectrum neutralisation against wildtype, Delta, Omicron, and other variant strains through a combination of direct receptor-binding blockade and Fc-mediated immune effector recruitment.
🔬
Trispecific Design
- Targets 3 independent spike epitopes
- Multiple mechanisms of action (Fc fusion)
- Sequence-optimised for manufacturability
⚡
Efficacy
- Potent intranasal therapy — validated in vivo
- Maintains neutralisation across key variants
- ~100-fold viral titer reduction in huACE2 mice
🏭
Manufacturability
- Excellent thermostability maintained
- Research-grade expression cell line established
- Kd (trispecific) at 1×10⁻¹¹ M level
Cross-Variant Binding & Blocking Activity
| SARS-CoV-2 Variant | Binding Activity | ACE2 Blocking |
|---|---|---|
| Wildtype | +++ | +++ |
| Other variants | +++/++ | +++/++ |
| Delta | ++ | ++ |
| Omicron | +++/++ | +++/++ |
~1×10⁻¹¹ M
Kd — Trispecific VHH-Fc
~1×10⁻¹⁰ M
Kd — Single VHH domain
Methodology: (1) Generate library from 65 naïve llamas · (2) Triple protein panning against SARS-CoV-2 S1 · (3) S/ACE2 competition ELISA · (4) Pairwise competition ELISA to identify synergistic VHH pairs · (5) CAAD-guided trispecific VHH-Fc structural assembly · (6) In vivo functional validation in huACE2 mice
Case Study 2
Anti-CD3 VHH Development for T Cell Engager (TCE) Bispecific Antibody
VHHs binding human CD3-γ and CD3-ε subunits were identified by cell-based panning against Jurkat T cells, with counter-depletion on 293T cells to eliminate non-specific binders. Selected leads demonstrated selective binding to CD3-expressing Jurkat cells and competitive displacement of reference anti-CD3 antibodies (12F6 and the CD3 arm of REGN1979/Odronextamab), confirming epitope overlap with clinically validated binding sites.
Panning Methodology (CCC)
1
Depletion with parental 293T cells to remove non-specific and Fc-binding clones
2
Three-round cell panning on Jurkat cells (CD3+) under progressively stringent wash conditions
3
Phage-infected colony selection and monoclonal ELISA screening
4
Phage elution and sequence analysis of positive clones
5
Transfer enriched phage pool to next panning round for further selection pressure
Key Results
Selective cell binding
Lead VHHs bind Jurkat (CD3+) cells but show no binding to parental 293T (CD3−) cells, confirming CD3 specificity.
Competitive epitope mapping
Multiple leads show competitive displacement with reference anti-CD3 antibodies 12F6 and the REGN1979 CD3 arm, confirming overlap with clinically validated epitopes.
Cross-species activity
Binding to both human and cynomolgus macaque CD3-δ and CD3-ε subunits confirmed, supporting IND-enabling toxicology studies.
TCE functional validation
BCMA × CD3 bispecific constructs demonstrate dose-dependent T cell activation (CD69+) and tumour cell killing (7AAD+ cells) in PBMC/H929 co-culture assays.
Case Study 3
Epitope-Selective VHH Discovery Against a Membrane Protein Target (Antigen-A)
This programme required isolation of VHHs that bind specifically to a defined extracellular domain (ECD) epitope present on the full-length membrane protein but absent in an ECD-deletion construct. A hybrid panning strategy (BB/C) combining biotinylated antigen panning with epitope-directed counter-panning was designed to achieve this selectivity.
Panning Strategy (BBC)
Rounds 1 & 2 (BB)
- Biotinylated antigen panning using streptavidin-bead capture
- Selects initial pool of antigen-binding clones with high stringency
Round 3 (C — Counter/Panning)
- Counter-panning with 293T-ECD-Deletion cells to deplete non-epitope binders
- Positive panning on 293T-ECD-Full Length cells to enrich epitope-specific clones
FACS Binding Validation
Lead VHH specificity was confirmed by FACS binding assays across three cell lines:
✅
293T-ECD-Full Length
High binding (dose-dependent, EC₅₀ ~0.1 nM)
❌
293T-ECD-Deletion
No significant binding — epitope absent
❌
293T (parental)
No binding — confirms antigen specificity
FACS binding assay demonstrates that the lead VHH candidate binds exclusively to cells expressing the full-length antigen with the target epitope intact, confirming both specificity and correct epitope selectivity.
What We Need From You
▸VHH sequences, or sequencing output from an immunisation or display campaign for triage
▸Antigen sequence or structure with epitope information where mapping has been performed
▸Measured affinity, stability, expression or aggregation data for any existing candidates
▸The objective: affinity, specificity, stability, humanisation or conversion to a multivalent format
▸Intended application, since therapeutic, diagnostic and imaging uses impose different constraints
How the Work Is Performed
▸Repertoire analysis and clustering to identify genuine families rather than sequencing duplicates
▸Structure prediction with dedicated CDR3 loop modelling and conformational ensemble generation
▸Framework analysis against camelid and human germlines, including the hallmark framework-2 positions
▸Antigen complex modelling and epitope-directed loop design where the target site is known
▸Sequence optimisation applying stability and solubility constraints alongside affinity objectives
▸Developability screening: aggregation-prone regions, charge distribution and chemical liability motifs
What You Receive
▸Ranked candidates or designed sequences with the rationale for each modification
▸Structural models including CDR3 ensembles and antigen complexes where applicable
▸Humanness assessment with graded humanisation designs and back-mutation recommendations
▸Developability report covering aggregation, solubility and chemical liabilities
▸A prioritised construction and testing plan across the delivered panel
Interpretation and Limitations
Long CDR3 loops remain among the harder modelling problems, so designs are checked across an ensemble rather than a single predicted pose. Humanising the framework-2 hallmark positions can cost solubility and stability, which is why graded series are delivered for measurement. Predicted affinity and aggregation values indicate rank order and risk, not outcome. Expression, purification and binding characterisation are performed by your team or a partner.
Questions We Are Asked Before Scoping
Can you triage sequencing output from a selection campaign?
Yes, and it is one of the most efficient uses of computation in nanobody programmes: clustering, germline analysis, modelling and developability screening across hundreds of sequences before any are expressed.
Will humanisation cost stability?
It can, particularly at the hallmark framework-2 positions that substitute for the light chain interface. Designs are delivered as a graded series so the trade-off is measured across a small panel.
Are nanobodies better than conventional antibodies?
For reaching concave or cryptic epitopes, for stability, and for simple multivalent assembly, often yes. For long circulating half-life and effector function without engineering, no. The right choice depends on the application.
What Published Work Reports
The results below were published by independent groups and are cited to show what these computational approaches have achieved in the literature. They are not ICDMO project results, and outcomes vary substantially between targets, datasets and programmes. We do not promise comparable results for any particular project.
10- to 140-fold affinity improvements from computational design
Computational interface redesign produced a tenfold affinity improvement in cetuximab, reaching 52 pM, and a 140-fold improvement to 30 pM for an anti-lysozyme model antibody — improvements achieved by designing a small number of interface substitutions rather than by library selection.
Lippow, Wittrup & Tidor, Nature Biotechnology, 2007 ↗Interface models predict which substitutions help, with measurable accuracy
A 2024 study combining structural interface analysis with sequence-derived evolutionary information reported a predictive model for antibody–antigen interaction with an area under the curve of 0.83 and precision of 0.89 on held-out data, and experimentally confirmed a designed point mutation that improved affinity 2.5-fold to 2 nM. Typical computational maturation gains are modest per mutation, which is why a designed panel is measured rather than a single variant.
Experimental validation study, 2024 ↗In the Lab and In Silico
What the work looks like
Single-domain antibody programmes combine library or immunisation-derived sequences with computational triage, structural modelling and developability screening before anything is expressed.
ICDMO's pre-humanised VHH discovery platform is the fastest route from target to characterised, clinical-ready nanobody lead. With a 1×10¹⁰-clone library, flexible multi-strategy panning, and integrated CAAD-guided lead optimisation and multi-specific format assembly, we deliver validated VHH candidates in approximately 4 months.
Contact our antibody discovery team to discuss your target, panning strategy, and desired therapeutic format.