| Literature DB >> 34965193 |
Bingchuan Wei1,2, Nicholas Woon1, Lu Dai1, Raphael Fish1, Michelle Tai1, Winode Handagama1, Ashley Yin1, Jia Sun3, Andrew Maier4, Dana McDaniel1, Elvira Kadaub1, Jessica Yang3, Miguel Saggu3, Ann Woys3, Oxana Pester5, Danny Lambert6, Alex Pell1, Zhiqi Hao7, Gordon Magill8, Jack Yim7, Jefferson Chan7, Lindsay Yang7, Frank Macchi1, Christian Bell6, Galahad Deperalta1, Yan Chen9.
Abstract
Rapid release of biopharmaceutical products enables a more efficient drug manufacturing process. Multi-attribute methods that target several product quality attributes (PQAs) at one time are an essential pillar of the rapid-release strategy. The novel, high-throughput, and nondestructive multi-attribute Raman spectroscopy (MARS) method combines Raman spectroscopy, design of experiments, and multivariate data analysis (MVDA). MARS allows the measurement of multiple PQAs for formulated protein therapeutics without sample preparation from a single spectroscopic scan. Variable importance in projection analysis is used to associate the chemical and spectral basis of targeted PQAs, which assists in model interpretation and selection. This study shows the feasibility of MARS for the measurement of both protein purity-related and formulation-related PQAs; measurements of protein concentration, osmolality, and some formulation additives were achieved by a generic multiproduct model for various protein products containing the same formulation components. MARS demonstrates the potential to be a powerful methodology to improve the efficiency of biopharmaceutical development and manufacturing, as it features fast turnaround time, good robustness, less human intervention, and potential for automation.Entities:
Keywords: Multi-attribute methods; Raman spectroscopy; design of experiments; formulation; monoclonal antibody; multivariate data analysis; product quality attributes; protein characterization; quality control; real-time release testing
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Year: 2022 PMID: 34965193 PMCID: PMC8726703 DOI: 10.1080/19420862.2021.2007564
Source DB: PubMed Journal: MAbs ISSN: 1942-0862 Impact factor: 5.857