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Human serum albumin (HSA) is the most abundant protein in plasma and plays an essential physiological role in the human body. Ethanol precipitation is the most widely used way to obtain HSA, and pH and ethanol are crucial factors affecting the process. In this study, infrared (IR) spectroscopy and near-infrared (NIR) spectroscopy in combination with chemometrics were used to investigate the changes in the secondary structure and hydration of HSA at acidic pH (5.6–3.2) and isoelectric pH when ethanol concentration was varied from 0% to 40% as a perturbation. IR spectroscopy combined with the two-dimensional correlation spectroscopy (2DCOS) analysis for acid pH system proved that the secondary structure of HSA changed significantly when pH was around 4.5. What’s more, the IR spectroscopy and 2DCOS analysis showed different secondary structure forms under different ethanol concentrations at the isoelectric pH. For the hydration effect analysis, NIR spectroscopy combined with the McCabe–Fisher method and aquaphotomics showed that the free hydrogen-bonded water fluctuates dynamically, with ethanol at 0–20% enhancing the hydrogen-bonded water clusters, while weak hydrogen-bonded water clusters were formed when the ethanol concentration increased continuously from 20% to 30%. These measurements provide new insights into the structural changes and changes in the hydration behavior of HSA, revealing the dynamic process of protein purification, and providing a theoretical basis for the selection of HSA alcoholic precipitation process parameters, as well as for further studies of complex biological systems.

Precipitation is a key manufacturing unit during the immunoglobulin G (IgG) production, which guarantees the quality of the final product. Ethanol is usually used to purify IgG during the precipitation process, so it is important to monitor the ethanol concentration online. Near-infrared (NIR) spectroscopy is a powerful process analytical technology (PAT) which has been proved to be feasible to determine the ethanol concentration during the precipitation process. However, the NIR model is usually established based on the specific process, so a universal model is needed. And the clarity degree of solution will affect the quality of the spectra. Therefore, in this study an integrated NIR system was introduced to establish a universal NIR model which could predict the ethanol concentration online and determine the end-point of the whole process. First, a spectra acquisition device was designed and established in order to get high-quality NIR spectra. Then, a simple prepared ethanol NIR model was constructed to predict the actual manufacturing process. Finally, the end-point was determined to stop the peristaltic pump when the ethanol concentration reached 20%. The results showed that the spectra quality was good, model prediction was accurate, and process monitoring was accurate. In conclusion, all results indicated that the integrated NIR system could be used to monitor the biopharmaceutical process to help us understand the pharmaceutical process.

At present, Tradition Chinese Medicine (TCM) industry in China is in the stage from the empirical development to industrial production. Near infrared (NIR) spectroscopy has been widely used in the quality control of TCM’s modernization with its characteristics including rapidness, nondestruction, simplicity, economy, and so on. In this study, as one type of a portable micro NIR spectrometer, Micro NIR 1700 was used to establish the qualitative models for identification of geographical region and authenticity of Radix codonopsis based on discriminant analysis (DA) method. Both of the DA models had better predictive ability with 100% accuracy. In addition, a method for rapid quantitative analysis of polysaccharide in Radix codonopsis was also developed based on Micro NIR 1700 spectrometer with partial least-squares (PLS) algorithm. In the PLS calibration model, the NIR spectra of samples were pretreated with different preprocessing methods and the spectral region was selected with different variable selection methods as well. The performance of the final PLS model was evaluated according to correlation coefficient of calibration ([Formula: see text]), correlation coefficient of prediction ([Formula: see text]), root mean squared error of cross validation (RMSECV), and root mean squared of prediction (RMSEP). The values of [Formula: see text], [Formula: see text], RMSECV, and RMSEP were 0.9775, 0.9602, 2.496, and 2.734[Formula: see text]g/mL, respectively. This work demonstrated that micro infrared spectrometer could be more convenient and rapid for quality control of Radix codonopsis, and the presented models would be a useful reference for quality control of other similar raw materials of TCM.