Predicting whether a therapeutic protein can be manufactured and formulated successfully typically requires a dedicated experimental campaign for each molecular format. However, the ability to apply existing antibody datasets across different molecular formats could improve developability assessments and inform antibody development decisions. This webinar explores the potential of cross-format predictive modeling using data from conventional IgG antibodies to assess VHH-Fc developability.
The session will introduce GDPa5, a 160-member VHH-Fc library profiled across ten standardized biophysical assays and examine whether models trained only on 559 IgGs can predict developability properties in a scaffold lacking both a light chain and a CH1 domain. Results demonstrate that 559 examples from a different antibody format can provide greater predictive value than 100 examples from the target format.
The webinar will also examine how prediction accuracy varies across biophysical properties. Transfer succeeds for properties encoded in local surface features, including heparin binding (Spearman ρ = 0.82), hydrophobicity (0.63) and self-association (0.62), but performs poorly for thermostability (0.16), which emerges from interdomain cooperativity absent in the target scaffold. The findings also highlight differences in model performance, with tabular neural networks better accommodating cross-format differences than linear and tree-based approaches.
Register for this webinar to explore how IgG data and predictive modeling can support VHH-Fc developability assessment and antibody development decisions.
Who Should Attend
This webinar will appeal to scientists and professionals involved in antibody development, protein engineering, biophysical characterization and predictive modeling, including:
Antibody Discovery and Development Scientists
Protein Design and Protein Engineering Scientists
Antibody Developability and Characterization Scientists
Computational Biology and AI/ML Scientists
Large Molecule Discovery Scientists
Research Managers, Directors and VPs in biopharma R&D
Register free on Xtalks: https://xtalks.com/webinars/improve-antibody-development-with-igg-trained-predictive-models/
