Antibody developability assessment

Antibody sequences often contain unwanted motifs that, when exposed at the surface of the molecule, can significantly impact developability. Early identification of these liabilities as well as features like hydrophobic patches facilitates the selection of candidates that require less engineering. Our high-throughput 3D-model-based developability profiling offers unparalleled accuracy, enabling better clone selection, significantly reducing costly lab iterations and increasing efficiency.

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Accurately identify and annotate exposed liabilities and molecular properties, like hydrophobic patches and charge distributions, using high-throughput structural modeling. Compare candidate antibodies with clinically approved ones to assess developability and select diverse candidates with optimal developability profiles, enhancing efficiency and streamlining development.

  • Easily prioritize more developable candidates during early hit selection
  • Accurately predict exposed liabilities based on ML-generated 3D models
  • Benchmark clones of interest against clinical antibodies
  • Interrogate the liability patterns in detail on the sequence level.
  • Easily compare and rank thousands of clones by overlaying intuitive summary statistics in any visualization
  • By partnering with OPIG (Prof. Deane’s lab), we leverage their well-validated, industry-leading deep learning models from the SabPred ImmuneBuilder suite. Our user-friendly interface enables you to independently perform structural modeling and accurately annotate liabilities, ensuring only your best candidates progress in development.

  • Using a structure-first approach provides nuanced insights, allowing you to strike the perfect balance and pick the best candidates. Our approach prevents disqualifying promising clones due to non-exposed motifs while considering important molecular properties, such as charged or hydrophobic patches, that can negatively impact developability.

  • Compute developability profiles for thousands of sequences with a single click and easily integrate this data for decision making throughout your entire discovery workflow.

  • Fine-tune which aspects of developability matter the most to you and align the developability profile with your engineering strategy. Decide which liabilities are critical and adjust the penalties accordingly, ensuring that the developability scoring aligns perfectly with your objectives and engineering approach.

  • See how your candidates’ properties compare to a database of all clinically validated antibodies and prioritize candidates with similar developability profiles.