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• W1516451386 abstract "Aggregation is a common problem affecting biopharmaceutical development that can have a significant effect on the quality of the product, as well as the safety to patients, particularly because of the increased risk of immune reactions. Here, we describe a new high-throughput screening algorithm developed to classify antibody molecules based on their propensity to aggregate. The tool, constructed and validated on experimental aggregation data for over 500 antibodies, is able to discern molecules with a high aggregation propensity as defined by experimental criteria relevant to bioprocessing and manufacturing of these molecules. Furthermore, we show how this tool can be combined with other computational approaches during early drug development to select molecules with reduced risk of aggregation and optimal developability properties." @default.
• W1516451386 created "2016-06-24" @default.
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• W1516451386 date "2015-03-04" @default.
• W1516451386 modified "2023-10-14" @default.
• W1516451386 title "Aggregation risk prediction for antibodies and its application to biotherapeutic development" @default.
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• W1516451386 doi "https://doi.org/10.1080/19420862.2015.1007828" @default.
• W1516451386 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4622581" @default.
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