LENSai BioIntelligence Suite

Epitope Binning

Effortless in silico mAb Epitope Binning with proven wet lab validation

Next-level in silico epitope binning, powered by LENSai™ technology, offers a pivotal advancement with its ability to analyze over 5,000 sequences, delivering rapid insights for early triaging. This advanced method allows you, within large pools of antibodies, to detect clusters of clones that share similar target binding regions ensuring a thorough and inclusive selection process. LENSai epitope binning smart algorithms enhance biological research, offering accurate, high-throughput candidate selection while reducing time and costs.

Innovate earlier. Scale smarter.

Set your antibody discovery path with precision and promise.

Significant high-throughput analysis for early triaging

Advance all mAb program types including challenging and hard to produce target proteins

Click the grid for an interactive view

Designed to reduce time and costs

Easily profile the epitope landscape

Key benefits

Speed and High‑throughput:

Results within hours for small subsets to 2 weeks for >5k antibodies.

Early epitope landscape profiling:

More-informed early triaging of lead candidate panel.

Proven:

Matches wet lab binning methods with high accuracy.

Effortless:

Only requires protein sequences — no need to produce physical materials.

Results within hours for small subsets to 2 weeks for >5k antibodies.

A critical step in antibody selection.

Epitope binning is crucial in the early stages of antibody discovery, as it facilitates the categorization of antibodies with similar target binding regions on the target. In general, insights in the epitope landscape of antibody panels significantly advance development of multi-targeting approaches. Additionally, understanding which protein regions are targeted by your antibody panel can significantly enhance intellectual property security.

Maximize early triaging with high efficiency

High precision with multi-dimensional clustering

LENSai proprietary Epitope Binning algorithm includes:

  • Antibody sequential and structural profiling
  • Docking information, accounting for steric hindrance and glycosylation sites
  • Atomic interactions of Ab-Ag complexes
Multiple output formats providing actionable insights:

3D Grid view:

Clusters group antibodies that share a similar target binding region. Quick view on cluster proximity.

Graph view:

Lines show similarity between Abs within and between clusters (red=high, blue = low). Select and zoom in (panel on right). Ab closest to all other members of its cluster are denoted with black border.

Proven results with Cohen’s Kappa testing

Proven results
Blinded wet lab validation of in silico prediction of epitope bins:
  • Example set of 29 antibodies
  • LENSai in silico epitope prediction versus classical in vitro competition assay for binning
  • Inter-annotator agreement analysis (Cohen’s Kappa Test) using a majority consensus label mapping
Case study conclusion:
Near perfect agreement between LENSai in silico Epitope Binning and classical wet-lab binning results.

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  • Label mapping κ
  • LENSai cluster ids >
    Wet lab bin 0.925
  • Wet lab bin labels >
    LENSai cluster ids 0.842
  • Cohen's Kappa Coefficient value key:
    > 0.8: Near perfect agreement

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