Deep UV Laser-Induced Fluorescence for Pharmaceutical Cleaning Validation

Experimental design of a film flow cleaning rig equipped with in-line process analytical technology (PAT) tool for real-time monitoring

The main purpose of this research was to develop an experimental film flow cleaning rig that can be combined with Process analytical technology (PAT) tools to reduce cleaning time and costs. Here, we show that the use of in-line UV-Vis was successful for real-time monitoring of the cleaning process of olanzapine as a challenging residue to clean. The cleaning process was found to be affected by the properties of the olanzapine soil, and the study showed the competing effects of mechanical lift-off and dissolution action with methanol as a solvent. However, The method is limited by the cleaning mechanisms, with the dissolution being the only mechanism that can be accurately quantified using an in-line UV-Vis PAT tool. This experimental approach can be used to optimize cleaning process conditions and solvent choices at the bench scale before deployment. The material of which the cleaning rig was printed limited the solvent that could be used for this study, and future modifications will include a more chemical-resistant material.

Selection of characteristic wavelengths using SMA for laser induced fluorescence spectroscopy of power transformer oil

As the core component of the power system, the accurate analysis of its state and fault type is very important for the maintenance and repair of the transformer. The detection method represented by the transformer oil dissolved gas has the disadvantages of complicated processing steps and high operation requirements. Here, laser induced fluorescence (LIF) spectroscopy was applied for the analysis of transformer oil. Specifically, the slime mould algorithm (SMA) was used to select the characteristic wavelengths of the transformer oil fluorescence spectrum, and on this basis, a transformer fault diagnosis model was constructed. First, samples of transformer oil in different states were collected, and the fluorescence spectrum of the transformer oil was obtained with the help of the LIF acquisition system. Then, different spectral pretreatments were performed on the original fluorescence spectra, and it was found that the pretreatment effect of Savitzky-Golay smoothing (SG) was the best. Then, SMA was used to screen the characteristic wavelengths of the fluorescence spectrum, and 137 characteristic wavelengths were screened out to realize the accurate identification of the fluorescence spectrum of the transformer oil. In addition, the advantages of SMA for feature wavelength screening of transformer oil fluorescence spectra were demonstrated by comparing with traditional feature extraction strategies using principal components analysis (PCA). The research results show that it is effective to use SMA to screen the characteristic wavelengths of the LIF spectroscopy of transformer oil and use it for transformer fault diagnosis, which is of great significance for promoting the development of transformer fault diagnosis technology.

Detection of the Adulteration of Motor Oil by Laser Induced Fluorescence Spectroscopy and Chemometric Techniques

Petroleum products are the target of fraudulent practices due to their high commercial value. The aim of this study is to provide a new analysis system to assess motor oil adulteration. For this purpose, Laser Induced Fluorescence (LIF) spectroscopy was exploited coupled with chemometric tools to detect motor oil adulteration by three types of cheap motor oils. Principal Component Analysis (PCA) was able to distinguish samples in three groups according to the type of adulterant. Besides, Partial Least Squares Regression (PLSR) was exploited to determine the percentage of adulteration. The best model was obtained with a regression coefficient of 0.96, Root Mean Square Error of Prediction (RMSEP) of 2.83, Standard Error of Prediction (SEP) of 2.83 and Bias of 0.40. The main results of this work provide new analysis system using the combination of LIF spectroscopy combined to PCA and PLS as an efficient and fast method for motor oil analysis.

Understanding the Adsorption and Desorption of Sitagliptin Phosphate Monohydrate on SS2343, Glass, and PTFE Using QCM-D and Raman Spectroscopy

Cross-contamination during pharmaceutical drug manufacturing can result in expensive recalls. To counter that, companies spend significant time and resources to ensure equipment cleanliness, often relying on the compound solubility data in various solvents as the main indicator of cleaning success. The aim of this work is to provide an alternative way to analyze the fouling and cleaning of surfaces in pharmaceutical manufacturing processes by using the quartz crystal microbalance with dissipation (QCM-D) and Raman spectroscopy. In this study, we chose an active pharmaceutical ingredient (API), sitagliptin phosphate monohydrate (SIT), as the model drug compound and observed its adsorption and desorption on stainless steel (SS2343), borosilicate glass (glass), and polytetrafluoroethylene (PTFE) surfaces. SIT was selected as the model API since it is a product manufactured on a large scale and is part of the widely used dipeptidyl peptidase-IV inhibitor class of oral hypoglycemics used to treat type 2 diabetes mellitus, while the chosen surfaces mimic the wall materials of manufacturing equipment and components such as reactors, transfer lines, and valves. Both the QCM-D and Raman spectroscopy results show the highest physisorption on PTFE, followed by SS2343 and glass. Additionally, QCM-D revealed a harder removal of SIT from SS2343 compared to glass and PTFE. Raman analysis of the chemical interactions disclosed C-F and C═O bond interactions between SIT and the surfaces, and the lack of a peak shift suggested dipole-dipole interactions. Furthermore, contact angle measurements indicate that hydrophobic attraction contributed to SIT adhesion to the PTFE surface. Subsequently, SIT coverage upon deposition on a PTFE surface has a significantly smaller surface area than on SS2343 and glass due to surface hydrophobicity, hence resulting in a longer removal time. These results provide a practical use of QCM-D and Raman spectroscopy to enhance the understanding of fouling and improve the cleaning of complex small molecules on relevant surfaces during the pharmaceutical manufacturing process.

Fluorescence spectroscopy for the determination of reconstitution time of an in-vial lyophilised product

Lyophilisation is a prominent technique used to create stabilised, dried forms of biopharmaceutical formulations. Reconstitution of lyophilised parenteral formulations is a key step prior to patient administration. The accurate determination of reconstitution time is a necessity to aid formulation development and support product quality control. Traditional methods for quantifying reconstitution time involve the visual identification of the endpoint, which has led to variable values reported across studies. In this work, the use of ultra-violet (UV) excited fluorescence spectroscopy as an alternative to the visual quantification of the reconstitution time was investigated. Spectrographic information was collected via a bespoke setup that allowed the measurement of the reconstitution time in a standard sealed lyophilisation vial. The spectra were analysed via principal component analysis (PCA) to obtain a time-based representation of the changes in a reconstituting formulation. The analysis was followed by the identification of an endpoint using three techniques ranging from fully automated to manual with regards to the required level of user input. At high protein concentration, the variability of the reconstitution time measurements was reduced from 80.4% relative standard deviation obtained via the traditional method to 8.2% for the instrumental method presented in.