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Updated: Sep 21, 2026

Single-cell Screening Method for the Selection and Recovery of Antibodies with Desired Specificities from Enriched Human Memory B Cell Populations
Published on: August 22, 2019
Against All Odds: Computational Screening Via Machine Learning Ranking and Generation of Antibody Candidates for
Vinayan Tiruvellore1,2, Mike Koegle2,1
1College of the Canyons, Santa Clarita, California, United States.
Abstract:
Creutzfeldt-Jakob disease (CJD) is a fatal prion disorder with no approved treatments. This study developed a machine learning pipeline trained on 21 literature-curated PrP-targeting CDR sequences to rank 29,574 original and mutation-generated candidate sequences using neutralization, selectivity, and literature-based blood-brain barrier (BBB) proxy scores. The models showed internal performance (neutralization AUC = 0.9239; selectivity AUC = 0.7759), identified 10 high-percentile candidates, and generated 7,309 novel variants. These findings support hypothesis-generating sequence-level prioritization of PrP-targeting candidates, but do not establish native PrP Sc -specific binding, full-antibody efficacy, exact PrP epitope recognition, or in vivo BBB penetration and require further experimental validation and testing.

