CrossAbSense oracles using frozen PLM encoders plus self- or cross-attention decoders improve prediction accuracy by 12-20% on three of five developability assays for therapeutic IgGs, with architecture choices revealing that aggregation depends on single-chain signals while stability requires heavy
Shuai, Jeffrey A
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Biologically-Grounded Multi-Encoder Architectures as Developability Oracles for Antibody Design
CrossAbSense oracles using frozen PLM encoders plus self- or cross-attention decoders improve prediction accuracy by 12-20% on three of five developability assays for therapeutic IgGs, with architecture choices revealing that aggregation depends on single-chain signals while stability requires heavy