Use of inline near-infrared spectroscopy to predict the viscosity of shampoo using multivariate analysis

Investigating the Design and Implementation of an In-Line Near-Infrared Probe Using Computational Fluid Dynamics for Measurement of Non-Newtonian Fluids

Process analytical technology (PAT) has developed significantly since its introduction in pharma where many in situ analytical probes and measuring devices are now commercially available, replacing the use of off-line quality control measurements that are typically laborious and time intensive. The use of PAT instrumentation should not interfere with the process itself and subsequently should have no effect on the product whilst measuring representative samples. Implementation of these devices is typically arbitrary using empirical means. Therefore, the objective of this study is to highlight the use of computational fluid dynamics modeling to investigate the effect of interfacing parameters and process parameters of an inline near-infrared (NIR) probe used to determine the viscosity of a non-Newtonian micellar liquid. The parameters investigated for the probe were immersion depth, immersion angle, gap size, and fluid velocity. The results conclude that the immersion angle and depth should both be optimized to prevent stagnant fluid accumulating in the measuring gap ensuring that the NIR measurements are representative of the bulk. The gap size determines the optical pathlength and therefore was also investigated against an existing predictive viscosity model showing no changes in model performance with varying gap size. The use of computational modeling to develop a digital twin prior to PAT implementation at the equipment design stage ensures the technology can perform at its best and will also aid in calibration transfer studies.

Comparison of Individual and Integrated Inline Raman, Near-Infrared, and Mid-Infrared Spectroscopic Models to Predict the Viscosity of Micellar Liquids

In many industries, viscosity is an important quality parameter which significantly affects consumer satisfaction and process efficiency. In the personal care industry, this applies to products such as shampoo and shower gels whose complex structures are built up of micellar liquids. Measuring viscosity offline is well established using benchtop rheometers and viscometers. The difficulty lies in measuring this property directly in the process via on or inline technologies. Therefore, the aim of this work is to investigate whether proxy measurements using inline vibrational spectroscopy, e.g., near-infrared (NIR), mid-infrared (MIR), and Raman, can be used to predict the viscosity of micellar liquids. As optical techniques, they are nondestructive and easily implementable process analytical tools where each type of spectroscopy detects different molecular functionalities. Inline fiber optic coupled probes were employed; a transmission probe for NIR measurements, an attenuated total reflectance probe for MIR and a backscattering probe for Raman. Models were developed using forward interval partial least squares variable selection and log viscosity was used. For each technique, combinations of pre-processing techniques were trialed including detrending, Whittaker filters, standard normal variate, and multiple scatter correction. The results indicate that all three techniques could be applied individually to predict the viscosity of micellar liquids all showing comparable errors of prediction: NIR: 1.75 Pa s; MIR: 1.73 Pa s; and Raman: 1.57 Pa s. The Raman model showed the highest relative prediction deviation (RPD) value of 5.07, with the NIR and MIR models showing slightly lower values of 4.57 and 4.61, respectively. Data fusion was also explored to determine whether employing information from more than one data set improved the model quality. Trials involved weighting data sets based on their signal-to-noise ratio and weighting based on transmission curves (infrared data sets only). The signal-to-noise weighted NIR-MIR-Raman model showed the best performance compared with both combined and individual models with a root mean square error of cross-validation of 0.75 Pa s and an RPD of 10.62. This comparative study provides a good initial assessment of the three prospective process analytical technologies for the measurement of micellar liquid viscosity but also provides a good basis for general measurements of inline viscosity using commercially available process analytical technology. With these techniques typically being employed for compositional analysis, this work presents their capability in the measurement of viscosity-an important physical parameter, extending the applicability of these spectroscopic techniques.

Evaluation of the analytical performances of two Raman handheld spectrophotometers for pharmaceutical solid dosage form quantitation

This paper addresses the issue of pharmaceutical solid dosage form quantitation using handheld Raman spectrophotometers. The two spectrophotometers used are designed with different technologies: one allows getting a more representative sampling with the Orbital Raster Scanning technology and the other one allows setting acquisition parameters. The goal was to evaluate which technology could provide the best analytical results. Several parameters were optimized to get the lowest prediction error in the end. The main objective of this study was to evaluate if this kind of instrument would be able to identify substandard medicines. For that purpose, two case-study were explored. At first, a full ICH Q2 (R1) compliant validation was performed for moderate Raman scatterer active pharmaceutical ingredient (API) in a specific formulation. It was successfully validated in the ±15% relative total error acceptance limits, with a RMSEP of 0.85% (w/w). Subsequently, it was interesting to evaluate the influence of excipients when the API is a high Raman scatterer. For that purpose, a multi-formulation model was developed and successfully validated with a RMSEP of 2.98% (w/w) in the best case. These two studies showed that thanks to the optimization of acquisition parameters, Raman handheld spectrophotometers methods were validated for two different case-study and could be applied to identify substandard medicines.