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Explainable Machine Learning Models to Predict Gibbs-Donnan Effect During Ultrafiltration and Diafiltration of High-Concentration Monoclonal Antibody Formulations.

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Title: Explainable Machine Learning Models to Predict Gibbs-Donnan Effect During Ultrafiltration and Diafiltration of High-Concentration Monoclonal Antibody Formulations.
Authors: Chen CS; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan., Ujiie S; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan., Tanibata R; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan., Kawase T; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan., Kobayashi S; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.
Source: Biotechnology journal [Biotechnol J] 2024 Oct; Vol. 19 (10), pp. e202400212.
Publication Type: Journal Article
Journal Info: Publisher: Wiley-VCH Verlag Country of Publication: Germany NLM ID: 101265833 Publication Model: Print Cited Medium: Internet ISSN: 1860-7314 (Electronic) Linking ISSN: 18606768 NLM ISO Abbreviation: Biotechnol J Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Explainable Machine Learning Models to Predict Gibbs-Donnan Effect During Ultrafiltration and Diafiltration of High-Concentration Monoclonal Antibody Formulations.
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  Data: <searchLink fieldCode="AU" term="%22Chen+CS%22">Chen CS</searchLink>; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Ujiie+S%22">Ujiie S</searchLink>; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Tanibata+R%22">Tanibata R</searchLink>; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Kawase+T%22">Kawase T</searchLink>; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Kobayashi+S%22">Kobayashi S</searchLink>; API Process Development Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley-VCH+Verlag%22">Wiley-VCH Verlag </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>101265833 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1860-7314 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2218606768%22">18606768 </searchLink><i>NLM ISO Abbreviation: </i>Biotechnol J <i>Subsets: </i>MEDLINE
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        Value: 10.1002/biot.202400212
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      – Code: eng
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      – TitleFull: Explainable Machine Learning Models to Predict Gibbs-Donnan Effect During Ultrafiltration and Diafiltration of High-Concentration Monoclonal Antibody Formulations.
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              Text: 2024 Oct
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