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A machine learning strategy for the identification of key in silico descriptors and prediction models for IgG monoclonal antibody developability properties

Andrew B. Waighta Discovery Biologics, Protein Sciences, Merck & Co., Inc, South San Francisco, CA, USACorrespondence[email protected]

https://orcid.org/0000-0002-4110-1452 View further author information

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David Prihodab Discovery Informatics, MSD Czech Republic s.r.o, Prague, Czech RepublicView further author information

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Rojan Shresthaa Discovery Biologics, Protein Sciences, Merck & Co., Inc, South San Francisco, CA, USAView further author information

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Kevin Metcalfa Discovery Biologics, Protein Sciences, Merck & Co., Inc, South San Francisco, CA, USAView further author information

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Marc Baillya Discovery Biologics, Protein Sciences, Merck & Co., Inc, South San Francisco, CA, USAView further author information

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Marco Anconab Discovery Informatics, MSD Czech Republic s.r.o, Prague, Czech RepublicView further author information

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Talal Widatallac Computational and Structural Chemistry, Merck & Co., Inc, South San Francisco, CA, USAView further author information

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Zachary Rollinsc Computational and Structural Chemistry, Merck & Co., Inc, South San Francisco, CA, USAView further author information

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Alan C Chengc Computational and Structural Chemistry, Merck & Co., Inc, South San Francisco, CA, USAView further author information

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Danny A. Bittonb Discovery Informatics, MSD Czech Republic s.r.o, Prague, Czech RepublicView further author information

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Laurence Fayadat-Dilmana Discovery Biologics, Protein Sciences, Merck & Co., Inc, South San Francisco, CA, USAView further author information