中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Visible Particle Identification Using Raman Spectroscopy and Machine Learning

文献类型:期刊论文

作者H. Sheng; Y. P. Zhao; X. A. Long; L. W. Chen; B. Li; Y. Y. Fei; L. Mi and J. Ma
刊名Aaps Pharmscitech
出版日期2022
卷号23期号:6页码:12
ISSN号1530-9932
DOI10.1208/s12249-022-02335-4
英文摘要Visible particle identification is a crucial prerequisite step for process improvement and control during the manufacturing of injectable biotherapeutic drug products. Raman spectroscopy is a technology with several advantages for particle identification including high chemical sensitivity, minimal sample manipulation, and applicability to aqueous solutions. However, considerable effort and experience are required to extract and interpret Raman spectral data. In this study, we applied machine learning algorithms to analyze Raman spectral data for visible particle identification in order to minimize expert support and improve data analysis accuracy. We manually prepared ten types of particle standard solutions to simulate the particle types typically observed during manufacturing and established a Raman spectral library with accurate peak assignments for the visible particles. Five classification algorithms were trained using visible particle Raman spectral data. All models had high prediction accuracy of >98% for all types of visible particles. Our results demonstrate that the combination of Raman spectroscopy and machine learning can provide a simple and accurate data analysis approach for visible particle identification.
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语种英语
源URL[http://ir.ciomp.ac.cn/handle/181722/67232]  
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714
H. Sheng,Y. P. Zhao,X. A. Long,et al. Visible Particle Identification Using Raman Spectroscopy and Machine Learning[J]. Aaps Pharmscitech,2022,23(6):12.
APA H. Sheng.,Y. P. Zhao.,X. A. Long.,L. W. Chen.,B. Li.,...&L. Mi and J. Ma.(2022).Visible Particle Identification Using Raman Spectroscopy and Machine Learning.Aaps Pharmscitech,23(6),12.
MLA H. Sheng,et al."Visible Particle Identification Using Raman Spectroscopy and Machine Learning".Aaps Pharmscitech 23.6(2022):12.

入库方式: OAI收割

来源:长春光学精密机械与物理研究所

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