In-line Monitoring of Monomer and Polymer Content During Microgel Synthesis Using Precipitation Polymerization via Raman Spectroscopy and Indirect Hard Modeling

Raman-based PAT for VLP precipitation: systematic data diversification and preprocessing pipeline identification

Virus-like particles (VLPs) are a promising class of biopharmaceuticals for vaccines and targeted delivery. Starting from clarified lysate, VLPs are typically captured by selective precipitation. While VLP precipitation is induced by step-wise or continuous precipitant addition, current monitoring approaches do not support the direct product quantification, and analytical methods usually require various, time-consuming processing and sample preparation steps. Here, the application of Raman spectroscopy combined with chemometric methods may allow the simultaneous quantification of the precipitated VLPs and precipitant owing to its demonstrated advantages in analyzing crude, complex mixtures. In this study, we present a Raman spectroscopy-based Process Analytical Technology (PAT) tool developed on batch and fed-batch precipitation experiments of Hepatitis B core Antigen VLPs. We conducted small-scale precipitation experiments providing a diversified data set with varying precipitation dynamics and backgrounds induced by initial dilution or spiking of clarified Escherichia coli-derived lysates. For the Raman spectroscopy data, various preprocessing operations were systematically combined allowing the identification of a preprocessing pipeline, which proved to effectively eliminate initial lysate composition variations as well as most interferences attributed to precipitates and the precipitant present in solution. The calibrated partial least squares models seamlessly predicted the precipitant concentration with R 2 of 0.98 and 0.97 in batch and fed-batch experiments, respectively, and captured the observed precipitation trends with R 2 of 0.74 and 0.64. Although the resolution of fine differences between experiments was limited due to the observed non-linear relationship between spectral data and the VLP concentration, this study provides a foundation for employing Raman spectroscopy as a PAT sensor for monitoring VLP precipitation processes with the potential to extend its applicability to other phase-behavior dependent processes or molecules.

Pre- and post-functionalization of thermoresponsive cationic microgels with ionic liquid moieties carrying different counterions

We investigate the effect of different anions on the temperature-dependent solution properties of poly(N-vinylcaprolactam) microgels carrying alkylated ionic liquid vinylimidazolium moieties synthesized by a pre- and post-functionalization approach.

A Component Content Measurement Method Modified Using Indirect Hard Modeling for Polymer Blends Based on Raman Spectroscopy

Raman spectroscopy has been proven to be useful for the component content measurement of polymer blends. However, the soft modeling methods commonly used in quantitative analysis of Raman spectroscopy require a large number of training samples, resulting in a waste of materials and time. This work adopted a modified indirect hard modeling (IHM) method to measure the component content of polymer blends based on Raman spectroscopy. The Raman spectra of polypropylene (PP)/polystyrene (PS) blends with different component content were collected and resolved into the sum of multiple Voigt peak functions. For a large number of peak parameters, the two-dimensional correlation spectroscopy was used to screen out the characteristic Voigt peaks highly correlated with component content to reduce the parameter dimensions and build the parameterized spectral models. The spectral model of the blend was expressed as the weighted sum of the pure component spectral models, during which the parameters of the pure component models were adjusted within a range. According to the relationship between the weight and content of the pure component, a linear regression model for component content prediction was established. The coefficient of determination (R²)/root mean squared error of the IHM component content prediction model was 0.9931/0.4367 wt%. Besides, two popular soft modeling methods, partial least squares and artificial neural network, were compared with the IHM method, which showed that the IHM model had higher prediction accuracy with fewer training samples.

Process Analytical Technology for Precipitation Process Integration into Biologics Manufacturing towards Autonomous Operation—mAb Case Study

The integration of real time release testing into an advanced process control (APC) concept in combination with digital twins accelerates the process towards autonomous operation. In order to implement this, on the one hand, measurement technology is required that is capable of measuring relevant process data online, and on the other hand, a suitable model must be available to calculate new process parameters from this data, which are then used for process control. Therefore, the feasibility of online measurement techniques including Raman-spectroscopy, attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR), diode array detector (DAD) and fluorescence is demonstrated within the framework of the process analytical technology (PAT) initiative. The best result is achieved by Raman, which reliably detected mAb concentration (R2 of 0.93) and purity (R2 of 0.85) in real time, followed by DAD. Furthermore, the combination of DAD and Raman has been investigated, which provides a promising extension due to the orthogonal measurement methods and higher process robustness. The combination led to a prediction for concentration with a R2 of 0.90 ± 3.9% and for purity of 0.72 ± 4.9%. These data are used to run simulation studies to show the feasibility of process control with a suitable digital twin within the APC concept.

Acrylamide precipitation polymerization in a continuous flow reactor: an in situ FTIR study reveals kinetics

In this work, we present a combination of a continuous flow reactor with in situ monitoring of the monomer conversion in a precipitation polymerization. The flow reactor is equipped with a preheating area for the synthesis of thermoresponsive microgels, based on N-isopropylacrylamide (NIPAM). The reaction progress is monitored with in situ FTIR spectroscopy. The monomer conversion at defined residence times is determined from absorbance spectra of the reaction solutions by linear combination with reference spectra of the stock solution and the purified microgel. The reconstruction of the spectra appears to be in good agreement with experimental data in the range of 1710 to 1530 cm− 1, in which prominent absorption bands are used as probes for the monomer and the polymer. With increasing residence time, we observed a decrease in intensity of the ν(C=C) vibration, originating from the monomer, while the ν(C=O) vibration is shifted to higher frequencies by polymerization. Differences between the determined inline conversion kinetics and offline growth kinetics, determined by photon correlation spectroscopy (PCS), are discussed in terms of diffusion and point to a crucial role of mixing in precipitation polymerizations.

Model-based design and synthesis of ferrocene containing microgels

Modelling and synthesis go hand in hand to efficiently engineer copolymer microgels with various architectures: core–shell structures (with ferrocene mainly in the core or in the shell) and also microgels with homogeneous comonomer distribution.

Enabling technologies in polymer synthesis: accessing a new design space for advanced polymer materials

This review discusses how developments in laboratory technologies can push the boundaries of what is achievable using existing polymer synthesis techniques.

Principal component analysis to enhance enantioselective Raman spectroscopy

Enantioselective Raman (esR) spectroscopy is an innovative technique with a high potential for online process monitoring in chiral media, e.g. in the pharmaceutical industry. A prerequisite for an effective application is to combine the experimental approach with suitable concepts for data analysis. In this work, we present a chemometric approach to analyze the esR spectra recorded in an automatized polarization-resolved Raman set-up. It is demonstrated that the proposed method is capable of distinguishing between the enantiomers of the chiral alcohol 4-methylpentan-2-ol in a fully unsupervised fashion. Furthermore, it is shown that the difficulty of facing only small intensity differences between the esR spectra of the enantiomers can be overcome by feeding difference spectra between the pure enantiomers and the racemate into the principal component analysis (PCA) algorithm. The enantiomers are clearly discriminable along the first principal component.

Functional Microgels: Recent Advances in Their Biomedical Applications

Here, a spotlight is shown on aqueous microgel particles which exhibit a great potential for various biomedical applications such as drug delivery, cell imaging, and tissue engineering. Herein, different synthetic methods to develop microgels with desirable functionality and properties along with degradable strategies to ensure their renal clearance are briefly presented. A special focus is given on the ability of microgels to respond to various stimuli such as temperature, pH, redox potential, magnetic field, light, etc., which helps not only to adjust their physical and chemical properties, and degradability on demand, but also the release of encapsulated bioactive molecules and thus making them suitable for drug delivery. Furthermore, recent developments in using the functional microgels for cell imaging and tissue regeneration are reviewed. The results reviewed here encourage the development of a new class of microgels which are able to intelligently perform in a complex biological environment. Finally, various challenges and possibilities are discussed in order to achieve their successful clinical use in future.

From Batch to Continuous Precipitation Polymerization of Thermoresponsive Microgels

Microgels are commonly synthesized in batch experiments, yielding quantities sufficient to perform characterization experiments for physical property studies. With increasing attention on the application potential of microgels, little attention is yet paid to the questions (a) whether they can be produced continuously on a larger scale, (b) whether synthesis routes can be easily transferred from batch to continuous synthesis, and (c) whether their properties can be precisely controlled as a function of synthesis parameters under continuous flow reaction conditions. We present a new continuous synthesis process of two typical but different microgel systems. Their size, size distribution, and temperature-responsive behavior are compared in depth to those of microgels synthesized using batch processes, and the influence of premixing and surfactant is also investigated. For the surfactant-free poly( N-vinylcaprolactam) and poly( N-isopropylacrylamide) systems, microgels are systematically smaller, while the actual size is depending on the premixing of the reaction solutions. However, by the use of a surfactant, the size difference between batch and continuous preparation diminishes, resulting in equal-sized microgels. Temperature-induced swelling-deswelling of microgels synthesized under continuous flow conditions was similar to that of their analogues synthesized using the batch polymerization process. Additionally, investigation of the internal microgel structure using static light scattering showed no significant changes between microgels prepared under batch and continuous conditions. The work encourages synthesis concepts of sequential chemical conditions in continuous flow reactors to prepare precisely tuned new microgel systems.

Calibration transfer of a Raman spectroscopic quantification method from at-line to in-line assessment of liquid detergent compositions

The industrial production of liquid detergent compositions entails delicate balance of ingredients and process steps. In order to assure high quality and productivity in the manufacturing line, process analytical technology tools such as Raman spectroscopy are to be implemented. Marked chemical specificity, negligible water interference and high robustness are ascribed to this process analytical technique. Previously, at-line calibration models have been developed for determining the concentration levels of the being studied liquid detergents main ingredients from Raman spectra. A strategy is now proposed to transfer such at-line developed regression models to an in-line set-up, allowing real-time dosing control of the liquid detergent composition under production. To mimic in-line manufacturing conditions, liquid detergent compositions are created in a five-liter vessel with an overhead mixer. Raman spectra are continuously acquired by pumping the detergent under production via plastic tubing towards a Raman superhead probe, which is incorporated into a metal frame with a sapphire window facing the detergent fluid. Two at-line developed partial least squares (PLS) models are aimed at transferring, predicting the concentration of surfactant 1 and polymer 2 in the examined liquid detergent composition. A univariate slope/bias correction (SBC) is investigated, next to three well-acknowledged multivariate transformation methods: direct, piecewise and double-window piecewise direct standardization. Transfer is considered successful when the magnitude of the validation sets root mean square error of prediction (RMSEP) is similar to or smaller than the corresponding at-line prediction error. The transferred model offering the most promising outcome is further subjected to an exhaustive statistical evaluation, in order to appraise the applicability of the suggested calibration transfer method. Interval hypothesis tests are thereby performed for method comparison. It is illustrated that the investigated transfer approach yields satisfactory results, provided that the original at-line calibration model is thoroughly validated. Both SBC transfer models return lower RMSEP values than their corresponding original models. The surfactant 1 assay met all relevant evaluation criteria, demonstrating successful transfer to the in-line set-up. The in-line quantification of polymer 2 levels in the liquid detergent composition could not be statistically validated, due to the poorer performance of the at-line model.