Rapid Identification and Characterization of Formulated Protein Products by Raman Spectroscopy Coupled with Discriminant Analysis

• Published in: PDA journal of pharmaceutical science and technology Vol. 70; no. 1; p. 62
• Main Authors: Cao, Xiaolin, Zhou, Dan, Loussaert, James A, Meriage, David S, Levine, Joseph D, Gabrielson, John P, Wen, Zai-Qing
• Format: Journal Article
• Language: English
• Published: United States 01.01.2016
• Subjects: Discriminant Analysis; Drug Compounding; Humans; Immunoglobulin G - analysis; Proteins - analysis; Proteins - chemical synthesis; Recombinant Fusion Proteins - analysis; Spectrum Analysis, Raman - methods; Time Factors; Discriminant analysis; Rapid characterization; Formulated protein products; Rapid identification; Raman spectroscopy; Mahalanobis distance; Principal component analysis
• ISSN: 1948-2124
• DOI: 10.5731/pdajpst.2015.005769

The rapid identification of protein drug products for packaging and receiving can significantly reduce disposition cycle time, and thereby improve the efficiency and productivity of the supply chain to better meet the needs of patients. In this feasibility study, we demonstrate a novel methodology that combines Raman spectroscopy with discriminant analysis that can be used for rapid identification or verification of finished products. With this methodology, Raman spectra of formulated therapeutic proteins were collected non-invasively with the samples either in a quartz cuvette or in the original glass vials, and analyzed without subtraction of buffer or placebo solutions. The algorithm used for the discriminant analysis was Mahalanobis distance by principal component analysis with residuals. In addition to product identification, the methodology has the potential to be used for characterizing formulated proteins when exposed to external stresses based on the changes of Mahalanobis distances. The rapid identification of protein drug products for packaging and receiving can significantly reduce disposition cycle time, and thereby improve the efficiency and productivity of the supply chain. In this study, we demonstrate a novel methodology that combines Raman spectroscopy with discriminant analysis to rapidly identify formulated proteins non-invasively.