In situ real time monitoring of emulsification and homogenization processes for vaccine adjuvants

Process analytical technology was used to monitor formation of a stable emulsion product, with results providing improved understanding of emulsion-based vaccine adjuvant formation processes.

A FT-NIR Process Analytical Technology Approach for Milk Renneting Control

The study proposes a process analytical technology (PAT) approach for the control of milk coagulation through near infrared spectroscopy (NIRS), computing multivariate statistical process control (MSPC) charts, based on principal component analysis (PCA). Reconstituted skimmed milk and commercial pasteurized skimmed milk were mixed at two different ratios (60:40 and 40:60). Each mix ratio was prepared in six replicates and used for coagulation trials, monitored by fundamental rheology, as a reference method, and NIRS by inserting a probe directly in the coagulation vat and collecting spectra at two different acquisition times, i.e., 60 s or 10 s. Furthermore, three failure coagulation trials were performed, deliberately changing temperature or rennet and CaCl2 concentration. The comparison with fundamental rheology results confirmed the effectiveness of NIRS to monitor milk renneting. The reduced spectral acquisition time (10 s) showed data highly correlated (r > 0.99) to those acquired with longer acquisition time. The developed decision trees, based on PC1 scores and T2 MSPC charts, confirmed the suitability of the proposed approach for the prediction of coagulation times and for the detection of possible failures. In conclusion, the work provides a robust but simple PAT approach to assist cheesemakers in monitoring the coagulation step in real-time.

Development of a General PAT Strategy for Online Monitoring of Complex Mixtures—On the Example of Natural Product Extracts from Bearberry Leaf (Arctostaphylos uva-ursi)

For the first time, a universally applicable and methodical approach from characterization to a PAT concept for complex mixtures is conducted—exemplified on natural products extraction processes. Bearberry leaf (Arctostaphylos uva-ursi) extract is chosen as an example of a typical complex mixture of natural plant origin and generalizable in its composition. Within the quality by design (QbD) based process development the development and implementation of a concept for process analytical technology (PAT), a key enabling technology, is the next necessary step in risk and quality-based process development and operation. To obtain and provide an overview of the broad field of PAT, the development process is shown on the example of a complex multi-component plant extract. This study researches the potential of different process analytical technologies for online monitoring of different component groups and classifies their possible applications within the framework of a QbD-based process. Offline and online analytics are established on the basis of two extraction runs. Based on this data set, PLS models are created for the spectral data, and correlations are conducted for univariate data. In a third run, the prediction potential is researched. Conclusively, the results of this study are arranged in the concept of a holistic quality and risk-based process design and operation concept.

High-Throughput Analysis from Complex Matrices: Acoustic Ejection Mass Spectrometry from Phase-Separated Fluid Samples

Acoustic ejection mass spectrometry is a novel high-throughput analytical technology that delivers high reproducibility without carryover observed. It eliminates the chromatography step used to separate analytes from matrix components. Fully-automated liquid–liquid extraction is widely used for sample cleanup, especially in high-throughput applications. We introduce a workflow for direct AEMS analysis from phase-separated liquid samples and explore high-throughput analysis from complex matrices. We demonstrate the quantitative determination of fentanyl from urine using this two-phase AEMS approach, with a LOD lower than 1 ng/mL, quantitation precision of 15%, and accuracy better than ±10% over the range of evaluation (1–100 ng/mL). This workflow offers simplified sample preparation and higher analytical throughput for some bioanalytical applications, in comparison to an LC-MS based approach.