In-Line Multipoint Near-Infrared Spectroscopy for Moisture Content Quantification during Freeze-Drying

Noninvasive Moisture Detection in Lyophilized Drug Product Using NIR Spectrometer and Headspace Moisture Analyzer

Utilization of laser headspace and near-infrared (NIR) methods provides rapid and non-destructive approaches for moisture detection of lyophilized drug products to facilitate lyophilization formulation characterization and process development. In the present study, the NIR method was developed based on a partial least square regression (PLSR) model calibrated and validated with Karl Fisher (KF) data, whereas the laser headspace method was developed with aid of dynamic vapor sorption (DVS) method so that the water vapor pressure measured from the headspace of a lyophilized drug product vial can be converted directly to water content value through the water vapor sorption isotherm of the lyophilized drug product bypassing KF calibration. The water contents of lyophilized samples obtained from both methods agreed well with KF data, with a root mean squared error of prediction (RMSEP) of less than 0.15%. The pros and cons of NIR and laser headspace method were evaluated. The results suggest that traditional off-line KF method can be potentially replaced by at-line laser headspace method combined with water sorption isotherm data from DVS. Further studies may be needed to evaluate the quantitation limit and generality of this method to a variety of lyophilized formulations.

Comparison of Vibrational Spectroscopic Techniques for Quantification of Water in Natural Deep Eutectic Solvents

Vibrational spectroscopic techniques, i.e., attenuated total reflectance infrared (ATR-IR), near infrared spectroscopy (NIRS) and Raman spectroscopy (RS), coupled with Partial Least Squares Regression (PLSR), were evaluated as cost-effective label-free and reagent-free tools to monitor water content in Levulinic Acid/L-Proline (LALP) (2:1, mol/mol) Natural Deep Eutectic Solvent (NADES). ATR-IR delivered the best outcome of Root Mean Squared Error (RMSE) of Cross-Validation (CV) = 0.27% added water concentration, RMSE of Prediction (P) = 0.27% added water concentration and mean % relative error = 2.59%. Two NIRS instruments (benchtop and handheld) were also compared during the study, respectively yielding RMSECV = 0.35% added water concentration, RMSEP = 0.56% added water concentration and mean % relative error = 5.13% added water concentration, and RMECV = 0.36% added water concentration, RMSEP = 0.68% added water concentration and mean % relative error = 6.23%. RS analysis performed in quartz cuvettes enabled accurate water quantification with RMECV = 0.43% added water concentration, RMSEP = 0.67% added water concentration and mean % relative error = 6.75%. While the vibrational spectroscopic techniques studied have shown high performance in relation to reliable determination of water concentration, their accuracy is most likely related to their sensitivity to detect the LALP compounds in the NADES. For instance, whereas ATR-IR spectra display strong features from water, Levulinic Acid and L-Proline that contribute to the PLSR predictive models constructed, NIRS and RS spectra are respectively dominated by either water or LALP compounds, representing partial molecular information and moderate accuracy compared to ATR-IR. However, while ATR-IR instruments are common in chemistry and physics laboratories, making the technique readily transferable to water quantification in NADES, Raman spectroscopy offers promising potential for future development for in situ, sample withdrawal-free analysis for high throughput and online monitoring.

Near-infrared analysis of nanofibrillated cellulose aerogel manufacturing

Biomaterial aerogel fabrication by freeze-drying must be further improved to reduce the costs of lengthy freeze-drying cycles and to avoid the formation of spongy cryogels and collapse of the aerogel structures. Residual water content is a critical quality attribute of the freeze-dried product, which can be monitored in-line with near-infrared (NIR) spectroscopy. Predictive models of NIR have not been previously applied for biomaterials and the models were mostly focused on the prediction of only one formulation at a time. We recorded NIR spectra of different nanofibrillated cellulose (NFC) hydrogel formulations during the secondary drying and set up a partial least square regression model to predict their residual water contents. The model can be generalized to measure residual water of formulations with different NFC concentrations and the excipients, and the NFC fiber concentrations and excipients can be separated with the principal component analysis. Our results provide valuable information about the freeze-drying of biomaterials and aerogel fabrication, and how NIR spectroscopy can be utilized in the optimization of residual water content.

Evaluation of the Robustness of A Novel NIR-based Technique to Measure the Residual Moisture In Freeze-dried Products

(Bio)pharmaceutical products freeze-dried in vials must meet stringent quality specifications: among these, the residual moisture (RM) is crucial. The most common techniques adopted for measuring the RM are destructive, e.g. Karl Fisher titration, thus few samples from each batch are tested. Being a high intra-batch variability an intrinsic feature of batch freeze-drying, a high number of samples needs to be tested to get a representative measurement. Near-Infrared (NIR) spectroscopy was extensively applied in the past as a non-invasive method to quantify the RM. In this paper, an accurate Partial Least Square (PLS) model was developed and calibrated with a single product, focusing on a small but significative wavelength range of NIR spectra (model SR), characteristic of the water and not of the product. The salient feature of this approach is that the model SR appears to provide fairly accurate estimates with the same product but at a higher concentration, with other excipients and in presence of an amino acid at high concentration, without requiring any additional calibration with KF analysis, as in previous techniques; the irrelevance of the vial shape was also shown. This approach was compared to a simpler one, based on a single-variable linear regression, and to more complex one, using a wider wavelength range or calibrating the PLS model with several products. Model SR definitely ended up as the most accurate, and it appeared to have a great potential as a robust model, suitable also for products that were not involved in the calibration step.

Molecular Insights on Successful Reconstitution of Freeze-Dried Nanofibrillated Cellulose Hydrogel

The diversity and safety of nanofibrillated cellulose (NFC) hydrogels have gained a vast amount of interest at the pharmaceutical site in recent years. Moreover, this biomaterial has a high potential to be utilized as a protective matrix during the freeze-drying of heat-sensitive pharmaceuticals and biologics to increase their properties for long-term storing at room temperature and transportation. Since freeze-drying and subsequent reconstitution have not been optimized for this biomaterial, we must find a wider understanding of the process itself as well as the molecular level interactions between the NFC hydrogel and the most suitable lyoprotectants. Herein we optimized the reconstitution of the freeze-dried NFC hydrogel by considering critical quality attributes required to ensure the success of the process and gained insights of the obtained experimental data by simulating the effects of the used lyoprotectants on water and NFC. We discovered the correlation between the measured characteristics and molecular dynamics simulations and obtained successful freeze-drying and subsequent reconstitution of NFC hydrogel with the presence of 300 mM of sucrose. These findings demonstrated the possibility of using the simulations together with the experimental measurements to obtain a more comprehensive way to design a successful freeze-drying process, which could be utilized in future pharmaceutical applications.

Advanced Process Analytical Technology in Combination with Process Modeling for Endpoint and Model Parameter Determination in Lyophilization Process Design and Optimization

Lyophilization is widely used in the preservation of thermolabile products. The main shortcoming is the long processing time. Lyophilization processes are mostly based on a recipe that is not changed, but, with the Quality by Design (QbD) approach and use of Process Analytical Technology (PAT), the process duration can be optimized for maximum productivity while ensuring product safety. In this work, an advanced PAT approach is used for the endpoint determination of primary drying. Manometric temperature measurement (MTM) and comparative pressure measurement are used to determine the endpoint of the batch while a modeling approach is outlined that is able to calculate the endpoint of every vial in the batch. This approach can be used for process development, control and optimization.

Recent developments in vibrational spectral analyses for dynamically assessing and monitoring food dehydration processes

Dehydration is one of the most widely used food processing techniques, which is sophisticated in nature. Rapid and accurate prediction of dehydration performance and its effects on product quality is still a difficult task. Traditional analytical methods for evaluating food dehydration processes are laborious, time-consuming and destructive, and they are not suitable for online applications. On the other hand, vibrational spectral techniques coupled with chemometrics have emerged as a rapid and noninvasive tool with excellent potential for online evaluation and control of the dehydration process to improve final dried food quality. In the current review, the fundamental of food dehydration and five types of vibrational spectral techniques, and spectral data processing methods are introduced. Critical overtones bands related to dehydration attributes in the near-infrared (NIR) region and the state-of-the-art applications of vibrational spectral analyses in evaluating food quality attributes as affected by dehydration processes are summarized. Research investigations since 2010 on using vibrational spectral technologies combined with chemometrics to continuously monitor food quality attributes during dehydration processes are also covered in this review.

Preservation of biomaterials and cells by freeze-drying: Change of paradigm

Freeze-drying is the most widespread method to preserve protein drugs and vaccines in a dry form facilitating their storage and transportation without the laborious and expensive cold chain. Extending this method for the preservation of natural biomaterials and cells in a dry form would provide similar benefits, but most results in the domain are still below expectations. In this review, rather than consider freeze-drying as a traditional black box we "break it" through a detailed process thinking approach. We discuss freeze-drying from process thinking aspects, introduce the chemical, physical, and mechanical environments important in this process, and present advanced biophotonic process analytical technology. In the end, we review the state of the art in the freeze-drying of the biomaterials, extracellular vesicles, and cells. We suggest that the rational design of the experiment and implementation of advanced biophotonic tools are required to successfully preserve the natural biomaterials and cells by freeze-drying. We discuss this change of paradigm with existing literature and elaborate on our perspective based on our new unpublished results.

Applicability of Raman and near-infrared spectroscopy in the monitoring of freeze-drying injectable ibuprofen

The freeze-drying process is an expensive, time-consuming and rather complex process. Therefore, process analytical technology (PAT) tools have been introduced to develop an optimized process and control critical process parameters, which affect the final product quality. The aim of the present work was to study the applicability of at-line near-infrared (NIR) and Raman spectroscopy approach in the monitoring of the freeze-drying process. Freeze-dried powders, which were developed previously, were manufactured as a multi-component system, containing ibuprofen (IBP). The NIR proved to be a useful tool for the monitoring of the freeze-drying process, since it was able to determine residual moisture content (RMC) and hence predict its values by using the partial least square (PLS) model. In addition, the evaluation of the correlation between the NIR and off-line HPLC IBP content results showed that NIR spectra were consistent with the HPLC measurements, even though overlapping absorption bands in multi-component system were observed. This research also studied the ability of using the at-line Raman measurements for the evaluation of the crystallinity and polymorphic transformations during the process, such as IBP ionization and mannitol polymorphism. The results were in correlation with XRPD results, but parameters of PLS models were not optimal. Nevertheless, this approach still assured better process understanding. To conclude, high applicability of the at-line NIR in the monitoring of the freeze-dried powder production was successfully demonstrated, suggesting that it can be used as a single tool to monitor RMC and IBP content as well as process deviations during the freeze-drying process.

Application of ultraviolet, visible, and infrared light imaging in protein-based biopharmaceutical formulation characterization and development studies

Imaging is increasingly more utilized as analytical technology in biopharmaceutical formulation research, with applications ranging from subvisible particle characterization to thermal stability screening and residual moisture analysis. This review offers a comprehensive overview of analytical imaging for scientists active in biopharmaceutical formulation research and development, where it presents the unique information provided by the ultraviolet (UV), visible (Vis), and infrared (IR) sections in the electromagnetic spectrum. The main body of this review consists of an outline of UV, Vis, and IR imaging techniques for several (bio)physical properties that are commonly determined during protein-based biopharmaceutical formulation characterization and development studies. The review concludes with a future perspective of applied imaging within the field of biopharmaceutical formulation research.

Challenging handheld NIR spectrometers with moisture analysis in plant matrices: Performance of PLSR vs. GPR vs. ANN modelling

The global demand for natural products grows rapidly, intensifying the request for the development of high-throughput, fast, non-invasive tools for quality control applicable on-site. Moisture content is one of the most important quality parameters of natural products. It determines their market suitability, stability and shelf life and should preferably be constantly monitored. Miniaturized near-infrared (NIR) spectroscopy is a powerful method for on-site analysis, potentially fulfilling this requirement. Here, a feasibility study for applicability and analytical performance of three miniaturized NIR spectrometers and two benchtop instruments was evaluated in that scenario. The case study involved 192 dried plant extracts composed of five different plants harvested in different countries at various times within two years. The reference analysis by Karl Fischer titration determined the water content in this sample set between 1.36% and 6.47%. For the spectroscopic analysis half of the samples were laced with a drying agent to comply with the industry standard. The performance of various calibration models for NIR analysis was evaluated on the basis of root-mean square error of prediction (RMSEP) determined for an independent test set. Partial least squares regression (PLSR), Gaussian process regression (GPR) and artificial neural network (ANN) models were constructed for the spectral sets from each instrument. GPR and ANN models performed superior for all samples measured by handheld spectrometers and for native ones analyzed by benchtop instruments. Moreover, the accuracy penalty when analyzing native samples was lower for GPR and ANN prediction as well. With GPR or ANN calibration, miniaturized spectrometers offered the prediction performance at the level of the benchtop instruments. Therefore, in this analytical application miniaturized spectrometers can be used on-site with no penalty to the performance vs. laboratory-based NIR analysis.

Non-invasive detection technologies of solid foreign matter and their applications to lyophilized pharmaceutical products: A review

Good Manufacturing Practice Regulations, under the Food and Drug Administration (FDA), stipulate that all pharmaceutical products must be free of any contaminants, including, namely, any foreign solid objects. Lyophilization is a common manufacturing method that consists of several steps where foreign materials may enter the product. The presence of unintended particles in freeze drying, which will herein be referred to under the term 'Lyophilization', is of great concern to the authorities responsible for drug safety and effectiveness. In the pharmaceutical industry, presently, the inspection of lyophilized products for foreign matter particulates relies on visual inspection where only the outer surface of the lyophilized cake is visible. This review is motivated by the need for new control strategies for foreign matter (FM) detection in lyophilized products; more specifically, it assesses the reliability of non-destructive technologies for FM detection in dried samples. Emerging technologies applied in other industries, such as various types of spectroscopies and imaging (e.g. chemical, X-ray, ultrasound, thermal and terahertz), are evaluated based on compatibility with the intended application, with identification of the possible technical challenges.

Inhomogeneous Distribution of Components in Solid Protein Pharmaceuticals: Origins, Consequences, Analysis, and Resolutions

Successful development of stable solid protein formulations usually requires the addition of one or several excipients to achieve optimal stability. In these products, there is a potential risk of an inhomogeneous distribution of the various ingredients, specifically the ratio of protein and stabilizer may vary. Such inhomogeneity can be detrimental for stability but is mostly neglected in literature. In the past, it was challenging to analyze inhomogeneous component distribution, but recent advances in analytical techniques have revealed new options to investigate this phenomenon. This paper aims to review fundamental aspects of the inhomogeneous distribution of components of freeze-dried and spray-dried protein formulations. Four key topics will be presented and discussed, including the sources of component inhomogeneity, its consequences on protein stability, the analytical methods to reveal component inhomogeneity, and possible solutions to prevent or mitigate inhomogeneity.

Near-Infrared Spectroscopy to Determine Residual Moisture in Freeze-Dried Products: Model Generation by Statistical Design of Experiments

Moisture content (MC) is a critical quality attribute of lyophilized biopharmaceuticals and can be determined by near-infrared (NIR) spectroscopy as nondestructive alternative to Karl-Fischer titration. In this study, we create NIR models to determine MC in mAb lyophilisates by use of statistical design of experiments (DoE) and multivariate data analysis. We varied the composition of the formulation as well as lyophilization parameters covering a large range of representative conditions, which is commonly referred to as "robustness testing" according to quality-by-design concepts. We applied principles of chemometrics with partial least squares and principal component analysis. The NIR model excluded samples with complete collapse and MC > 6%. The 2 main components in the principal component analysis were MC (91%) and protein:sugar ratio (6%). The third component amounted to only 3% and remained unspecified but may include variations in process parameters and cake structure. In contrast to traditional approaches for NIR model creation, the DoE-based model can be used to monitor MC during drug product development work including scale-up, and transfer without the need to update the NIR model if protein:sugar ratio and MC stays within the tested limits and cake structure remains macroscopically intact. The use of the DoE approach and multivariate data analysis ensures product consistency and improves understanding of the manufacturing process.

Measurement of the Water Content in Semi-solid Formulations Used to Treat Pressure Ulcers and Evaluation of Their Water Absorption Characteristics

We investigated the water contents in commercial semi-solid preparations used for pressure ulcer (PU) treatment using near-IR spectroscopy (NIRS) and compared the results with those measured using the Karl Fischer (KF) method. The aim of this study was to determine a standard method and select the appropriate topical preparation with the optimal moisture for PU treatment. The water absorption properties of bases and formulations were evaluated with a time-dependent factor using Transwell as the model membrane. KF and NIRS were applicable as measurement methods of the water content in semi-solid formulations. NIRS was shown to be a useful, simple, nondestructive tool that is more advantageous than the KF method. The water absorption characteristics tested using Transwell revealed that the rate of and capacity for water absorption are determined not only by the absorption ability of the polymer base but also by other factors, such as the osmotic pressure exerted by additives. KF and NIR measurements can be used to choose external skin preparations to control the amount of water in PU treatment.

Note: Plasma optical emission spectroscopy for water vapor quantification and detection during vacuum drying process

A methodology involving plasma optical emission spectroscopy driven by a direct current (dc) plasma source is developed to quantify water vapor concentration in a gaseous stream. The experimental setup consists of a dc driven low-pressure plasma cell in which the emission from the plasma discharge is measured by using an optical emission spectrometer. The emission from H_α at 656.2 nm-the first transition in the Balmer series, was found to be the most sensitive to the water vapor concentration in the gas stream. Consistent linear trends of the emission signals with respect to variation in concentration of water are observed for multiple combinations of operating parameters. This method has been applied to a vacuum drying process of a mock nuclear fuel assembly to quantify the concentration of water vapor during the drying process.

Use of near-infrared spectroscopy and multipoint measurements for quality control of pharmaceutical drug products

Near-infrared (NIR) spectroscopy is a non-destructive analytical technique that enables better-understanding and optimization of pharmaceutical processes and final drug products. The use in line is often limited by acquisition speed and sampling area. This work focuses on performing a multipoint measurement at high acquisition speed at the end of the manufacturing process on a conveyor belt system to control both the distribution and the content of active pharmaceutical ingredient within final drug products, i.e., tablets. A specially designed probe with several collection fibers was developed for this study. By measuring spectral and spatial information, it provides physical and chemical knowledge on the final drug product. The NIR probe was installed on a conveyor belt system that enables the analysis of a lot of tablets. The use of these NIR multipoint measurement probes on a conveyor belt system provided an innovative method that has the potential to be used as a new paradigm to ensure the drug product quality at the end of the manufacturing process and as a new analytical method for the real-time release control strategy. Graphical abstract Use of near-infrared spectroscopy and multipoint measurements for quality control of pharmaceutical drug products.

The Future of Pharmaceutical Manufacturing Sciences

The entire pharmaceutical sector is in an urgent need of both innovative technological solutions and fundamental scientific work, enabling the production of highly engineered drug products. Commercial-scale manufacturing of complex drug delivery systems (DDSs) using the existing technologies is challenging. This review covers important elements of manufacturing sciences, beginning with risk management strategies and design of experiments (DoE) techniques. Experimental techniques should, where possible, be supported by computational approaches. With that regard, state-of-art mechanistic process modeling techniques are described in detail. Implementation of materials science tools paves the way to molecular-based processing of future DDSs. A snapshot of some of the existing tools is presented. Additionally, general engineering principles are discussed covering process measurement and process control solutions. Last part of the review addresses future manufacturing solutions, covering continuous processing and, specifically, hot-melt processing and printing-based technologies. Finally, challenges related to implementing these technologies as a part of future health care systems are discussed.

Multipoint near-infrared spectrometry for real-time monitoring of protein conformational stability in powdered infant formula

Powdered infant formula (PIF) can be the sole source of nutrition for babies and infants. Monitoring conformational changes in protein during manufacture of PIF is critical in order to maintain its nutritional value. This study presents the development of a calibration model for monitoring conformational changes in PIF protein by applying a novel multipoint near-infrared (NIR) spectrometry. NIR spectra were collected for PIF and PIF proteins, casein and whey protein isolate, before and after heat treatment. Results show that principal component analysis showed discrimination between native protein at room temperature and protein conformational changes caused at elevated temperature. Partial least squares regression analysis showed good calibration models with correlation coefficients ranging between 87% and 99% for the prediction of protein quality. This novel multipoint NIR spectrometry could serve as a simple in-line tool to rapidly monitor protein quality during processing stages, contributing to product nutritional value.

On-line quantitative monitoring of liquid-liquid extraction of Lonicera japonica and Artemisia annua using near-infrared spectroscopy and chemometrics

BACKGROUND

Liquid-liquid extraction of Lonicera japonica and Artemisia annua (JQ) plays a significant role in manufacturing Reduning injection. Many process parameters may influence liquid-liquid extraction and cause fluctuations in product quality.

OBJECTIVE

To develop a near-infrared (NIR) spectroscopy method for on-line monitoring of liquid-liquid extraction of JQ.

MATERIALS AND METHODS

Eleven batches of JQ extraction solution were obtained, ten for building quantitative models and one for assessing the predictive accuracy of established models. Neochlorogenic acid (NCA), chlorogenic acid (CA), cryptochlorogenic acid (CCA), isochlorogenic acid B (ICAB), isochlorogenic acid A (ICAA), isochlorogenic acid C (ICAC) and soluble solid content (SSC) were selected as quality control indicators, and measured by reference methods. NIR spectra were collected in transmittance mode. After selecting the spectral sub-ranges, optimizing the spectral pretreatment and neglecting outliers, partial least squares regression models were built to predict the content of indicators. The model performance was evaluated by the coefficients of determination (R (2)), the root mean square errors of prediction (RMSEP) and the relative standard error of prediction (RSEP).

RESULTS

For NCA, CA, CCA, ICAB, ICAA, ICAC and SSC, R (2) was 0.9674, 0.9704, 0.9641, 0.9514, 0.9436, 0.9640, 0.9809, RMSEP was 0.0280, 0.2913, 0.0710, 0.0590, 0.0815, 0.1506, 1.167, and RSEP was 2.32%, 4.14%, 3.86%, 5.65%, 7.29%, 6.95% and 4.18%, respectively.

CONCLUSION

This study demonstrated that NIR spectroscopy could provide good predictive ability in monitoring of the content of quality control indicators in liquid-liquid extraction of JQ.

Evaluation of spin freezing versus conventional freezing as part of a continuous pharmaceutical freeze-drying concept for unit doses

Spin-freezing as alternative freezing approach was evaluated as part of an innovative continuous pharmaceutical freeze-drying concept for unit doses. The aim of this paper was to compare the sublimation rate of spin-frozen vials versus traditionally frozen vials in a batch freeze-dryer, and its impact on total drying time. Five different formulations, each having a different dry cake resistance, were tested. After freezing, the traditionally frozen vials were placed on the shelves while the spin-frozen vials were placed in aluminum vial holders providing radial energy supply during drying. Different primary drying conditions and chamber pressures were evaluated. After 2h of primary drying, the amount of sublimed ice was determined in each vial. Each formulation was monitored in-line using NIR spectroscopy during drying to determine the sublimation endpoint and the influence of drying conditions upon total drying time. For all tested formulations and applied freeze-drying conditions, there was a significant higher sublimation rate in the spin-frozen vials. This can be explained by the larger product surface and the lower importance of product resistance because of the much thinner product layers in the spin frozen vials. The in-line NIR measurements allowed evaluating the influence of applied drying conditions on the drying trajectories.