Abstract
Raman spectroscopy has the potential to revolutionise many aspects of biopharmaceutical process development. The widespread adoption of this promising technology has been hindered by the high cost associated with individual probes and the challenge of measuring low sample volumes. To address these issues, this paper investigates the potential of an emerging new high-throughput (HT) Raman spectroscopy microscope combined with a novel data analysis workflow to replace off-line analytics for upstream and downstream operations. On the upstream front, the case study involved the at-line monitoring of an HT micro-bioreactor system cultivating two mammalian cell cultures expressing two different therapeutic proteins. The spectra generated were analysed using a partial least squares (PLS) model. This enabled the successful prediction of the glucose, lactate, antibody, and viable cell density concentrations directly from the Raman spectra without reliance on multiple off-line analytical devices and using only a single low-volume sample (50–300 μL). However, upon the subsequent investigation of these models, only the glucose and lactate models appeared to be robust based upon their model coefficients containing the expected Raman vibrational signatures. On the downstream front, the HT Raman device was incorporated into the development of a cation exchange chromatography step for an Fc-fusion protein to compare different elution conditions. PLS models were derived from the spectra and were found to predict accurately monomer purity and concentration. The low molecular weight (LMW) and high molecular weight (HMW) species concentrations were found to be too low to be predicted accurately by the Raman device. However, the method enabled the classification of samples based on protein concentration and monomer purity, allowing a prioritisation and reduction in samples analysed using A280 UV absorbance and high-performance liquid chromatography (HPLC). The flexibility and highly configurable nature of this HT Raman spectroscopy microscope makes it an ideal tool for bioprocess research and development, and is a cost-effective solution based on its ability to support a large range of unit operations in both upstream and downstream process operations.
Highlights
Process analytical technology (PAT) has been a major talking point within the biopharmaceutical sector since the release of the FDA’s guidance for industry on PAT in 2004 [1]
The research outlined in this paper investigates the predictive capabilities of an HT Raman microscope combined with advanced data analytics to support both upstream processing (USP) and Downstream Processing (DSP) research and development operations
This paper evaluates the performance of a novel HT-Raman spectroscopy device applied to two critical USP and DSP operations within biopharmaceutical manufacturing
Summary
Process analytical technology (PAT) has been a major talking point within the biopharmaceutical sector since the release of the FDA’s guidance for industry on PAT in 2004 [1]. These operations differ widely in terms of scale, where R&D operations utilise small volumes in the range of μL to L and commercial manufacturing processes operate with volumes in the range of 500 to 20,000 L This large-scale difference can limit the universal application of a proposed PAT technology in the early stages of the drug development pipeline, reducing the adoption of these core technologies within late-stage process development and commercialisation. To help bridge this gap, this paper focuses on the application of multivariate data analysis (MVDA) to better leverage at-line spectral measurements generated by a novel Raman spectroscopy microscope and utilise this information to support research and development (R&D) activities within the biopharmaceutical sector
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