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COVID-19: BioMaking Solutions - Dr. David Gifford, MIT, "Computationally optimized SARS-CoV-2 MHC class I and II vaccine formulations predicted to target human haplotype distributions"
We present a combinatorial machine learning method to evaluate and optimize peptide vaccine formulations for SARS-CoV-2. Our approach optimizes the presentation likelihood of a diverse set of vaccine peptides conditioned on a target human population HLA haplotype distribution and expected epitope drift. Our proposed SARS-CoV-2 MHC class I vaccine formulations provide 93.21% predicted population coverage with at least five vaccine peptide-HLA hits on average per person (>= 1 peptide 99.91%) with all vaccine peptides perfectly conserved across 4,690 geographically sampled SARS-CoV-2 genomes. Our proposed MHC class II vaccine formulations provide 97.21% predicted coverage with at least five vaccine peptide-HLA hits on average per person with all peptides having observed mutation probability <= 0.001.

Aug 5, 2020 12:00 PM in Eastern Time (US and Canada)

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