Your browser doesn't support javascript.
loading
Analysis of Biologics Molecular Descriptors towards Predictive Modelling for Protein Drug Development Using Time-Gated Raman Spectroscopy.
Itkonen, Jaakko; Ghemtio, Leo; Pellegrino, Daniela; Jokela Née Heinonen, Pia J; Xhaard, Henri; Casteleijn, Marco G.
Afiliação
  • Itkonen J; Drug Research Program, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, 00100 Helsinki, Finland.
  • Ghemtio L; Drug Research Program, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, 00100 Helsinki, Finland.
  • Pellegrino D; Drug Research Program, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, 00100 Helsinki, Finland.
  • Jokela Née Heinonen PJ; Drug Research Program, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, 00100 Helsinki, Finland.
  • Xhaard H; Orion Pharma, 02101 Espoo, Finland.
  • Casteleijn MG; Drug Research Program, Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, 00100 Helsinki, Finland.
Pharmaceutics ; 14(8)2022 Aug 05.
Article em En | MEDLINE | ID: mdl-36015265
ABSTRACT
Pharmaceutical proteins, compared to small molecular weight drugs, are relatively fragile molecules, thus necessitating monitoring protein unfolding and aggregation during production and post-marketing. Currently, many analytical techniques take offline measurements, which cannot directly assess protein folding during production and unfolding during processing and storage. In addition, several orthogonal techniques are needed during production and market surveillance. In this study, we introduce the use of time-gated Raman spectroscopy to identify molecular descriptors of protein unfolding. Raman spectroscopy can measure the unfolding of proteins in-line and in real-time without labels. Using K-means clustering and PCA analysis, we could correlate local unfolding events with traditional analytical methods. This is the first step toward predictive modeling of unfolding events of proteins during production and storage.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article