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. |
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| 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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| ISSN: | 1860-7314 |
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| DOI: | 10.1002/biot.202400212 |
