Application of in-line Raman spectroscopy to monitor crystallization and melting processes in milk fat

Anhydrous milk fat (AMF) and its fractions are used as ingredients in a wide range of food applications. Obtaining the appropriate solid fat content (SFC) is essential to achieve the desired product texture. At present, in-line monitoring techniques to control milk fat crystallization and melting are largely unavailable. The thermal behaviour of milk fat (AMF and four of its fractions) was monitored in a temperature-controlled vessel using an in-line Raman analyser and compared with thermograms generated using differential scanning calorimetry (DSC). The major stages of milk fat crystallization and melting were identified using the in-line Raman analyser. Thermal data from DSC showed excellent linear correlations with Raman spectral data (R2 value of 0.97 for the onset of milk fat crystallisation). Partial least squares regression (PLSR) models were developed using Raman spectra to predict SFC with coefficient of determination (R2Cs) from 0.929 to 0.992 and root mean standard error of calibration (RMSECs) ranging from 3.20 to 10.36%. Results demonstrated Raman spectroscopy has significant potential as a way of monitoring milk fat crystallization and melting processes.

In-situ sequential crystallization of fenofibrate and tristearin - Understanding the distribution of API in particles and stability of solid lipid microparticles from the perspective of crystallization

In-situ API crystallization in carrier matrices has attracted extensive attention in recent years for its advantages over traditional preparation processes. However, due to the lack of systemic research on molecular self-assembly behaviors, the products obtained by in-situ crystallization suffer from the problems of polymorphic transformation and drug expulsion during storage, limiting its industrial application. This paper investigates the in-situ sequential crystallization behavior of tristearin (SSS) and fenofibrate (FEN), utilizing SSS as the carrier and FEN as the API. It was found that the behavior of mixed crystallization significantly differs from single-component crystallization, including direct formation of stable form of SSS and the rapid crystallization of FEN. During the crystallization process, the melting FEN promotes the movement of SSS molecules, while the sliding of SSS lamellae, in turn, provides a mechanical stimulus to enhance the nucleation of FEN. Based on the observed synergistic crystallization behavior, the distribution and stability of the API within FEN solid lipid microparticles (SLMs) during storage were evaluated, while also examining the stability variations in SLMs formulated at different cooling rates and drug loading concentrations. The findings indicate that the initial nucleated FEN results in a decrease in the surrounding molten FEN and the irregularity of the SSS lamellas, thereby preventing the remaining molten FEN from achieving complete crystallization within a brief period. Due to the compatibility between FEN and SSS, some SSS may blend with the molten FEN, potentially resulting in further crystallization during storage and consequently increasing the risk of drug expulsion.

Process analytical technology in Downstream-Processing of Drug Substances- A review

Process Analytical Technology (PAT) has revolutionized pharmaceutical manufacturing by providing real-time monitoring and control capabilities throughout the production process. This review paper comprehensively examines the application of PAT methodologies specifically in the production of solid active pharmaceutical ingredients (APIs). Beginning with an overview of PAT principles and objectives, the paper explores the integration of advanced analytical techniques such as spectroscopy, imaging modalities and others into solid API substance production processes. Novel developments in in-line monitoring at academic level are also discussed. Emphasis is placed on the role of PAT in ensuring product quality, consistency, and compliance with regulatory requirements. Examples from existing literature illustrate the practical implementation of PAT in solid API substance production, including work-up, crystallization, filtration, and drying processes. The review addresses the quality and reliability of the measurement technologies, aspects of process implementation and handling, the integration of data treatment algorithms and current challenges. Overall, this review provides valuable insights into the transformative impact of PAT on enhancing pharmaceutical manufacturing processes for solid API substances.

Spectroscopic insights into multi-phase protein crystallization in complex lysate using Raman spectroscopy and a particle-free bypass

Protein crystallization as opposed to well-established chromatography processes has the benefits to reduce production costs while reaching a comparable high purity. However, monitoring crystallization processes remains a challenge as the produced crystals may interfere with analytical measurements. Especially for capturing proteins from complex feedstock containing various impurities, establishing reliable process analytical technology (PAT) to monitor protein crystallization processes can be complicated. In heterogeneous mixtures, important product characteristics can be found by multivariate analysis and chemometrics, thus contributing to the development of a thorough process understanding. In this project, an analytical set-up is established combining offline analytics, on-line ultraviolet visible light (UV/Vis) spectroscopy, and in-line Raman spectroscopy to monitor a stirred-batch crystallization process with multiple phases and species being present. As an example process, the enzyme Lactobacillus kefir alcohol dehydrogenase (LkADH) was crystallized from clarified Escherichia coli (E. coli) lysate on a 300 mL scale in five distinct experiments, with the experimental conditions changing in terms of the initial lysate solution preparation method and precipitant concentration. Since UV/Vis spectroscopy is sensitive to particles, a cross-flow filtration (cross-flow filtration)-based bypass enabled the on-line analysis of the liquid phase providing information on the lysate composition regarding the nucleic acid to protein ratio. A principal component analysis (PCA) of in situ Raman spectra supported the identification of spectra and wavenumber ranges associated with productspecific information and revealed that the experiments followed a comparable, spectral trend when crystals were present. Based on preprocessed Raman spectra, a partial least squares (PLS) regression model was optimized to monitor the target molecule concentration in real-time. The off-line sample analysis provided information on the crystal number and crystal geometry by automated image analysis as well as the concentration of LkADH and host cell proteins (HCPs) In spite of a complex lysate suspension containing scattering crystals and various impurities, it was possible to monitor the target molecule concentration in a heterogeneous, multi-phase process using spectroscopic methods. With the presented analytical set-up of off-line, particle-sensitive on-line, and in-line analyzers, a crystallization capture process can be characterized better in terms of the geometry, yield, and purity of the crystals.

Real-Time Monitoring of Multistep Batch and Flow Synthesis Processes of a Key Intermediate of Lifitegrast by a Combined Spectrometer System with Both Near-Infrared and Raman Spectroscopies Coupled to Partial Least-Squares

Process analytical technology (PAT) has been successfully applied in numerous chemical synthesis cases and is an important tool in pharmaceutical process research and development. PAT brings new methods and opportunities for the real-time monitoring of chemical processes. In multistep synthesis, real-time monitoring of the complex reaction mixtures is a significant challenge but provides an opportunity to enhance reaction understanding and control. In this study, a combined multichannel spectrometer system with both near-infrared and Raman spectroscopy was built, and calibration models were developed to quantify the desired products, intermediates, and impurities in real-time at multiple points along the synthetic pathway. The capabilities of the system have been demonstrated by operating dynamic experiments in both batch and continuous-flow processes. It represents a significant step forward in data-driven, multistep pharmaceutical ingredient synthesis.

Stability of Rapidly Crystallizing Sulfonamides Glasses by Fast Scanning Calorimetry: Crystallization Kinetics and Glass-Forming Ability

Production and evaluation of the kinetic stability of the amorphous forms of active pharmaceutical ingredients are among the current challenges of modern pharmaceutical science. In the present work, amorphous forms of several sulfonamides were produced for the first time using Fast Scanning calorimetry. The parameters, characterizing the glass-forming ability of the compounds, i.e. the critical cooling rate of the melt and the kinetic fragility, were determined. The cold crystallization kinetics was studied using both isothermal and non-isothermal approaches. The results of the present study will contribute to the development of approaches for producing amorphous forms of rapidly crystallizing active pharmaceutical ingredients.

Quantifying Dense Multicomponent Slurries with In-Line ATR-FTIR and Raman Spectroscopies: A Hanford Case Study

The multiphase nature of slurries can make them difficult to process and monitor in real time. For example, the nuclear waste slurries present at the Hanford site in Washington State are multicomponent, multiphase, and inhomogeneous. Current analytical techniques for analyzing radioactive waste at Hanford rely on laboratory results from an on-site analytical laboratory, which can delay processing speed and create exposure risks for workers. However, in-line probes can provide an alternative route to collect the necessary composition information. In the present work, Raman spectroscopy and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy are tested on simulants of nuclear waste slurries containing up to 23.2 wt % solids. We observe ATR-FTIR spectroscopy to be effective in measuring the solution phase of the studied slurry systems (3.52% mean percent error), while Raman spectroscopy provides information about the suspended solids in the slurry system (18.21% mean percent error). In-line measurement of multicomponent solids typical of nuclear waste processing has been previously unreported. The composition of both the solution and solid phases is vital in ensuring stable glass formulation and effective disposal of nuclear waste at Hanford. Raman and ATR-FTIR spectroscopies can provide a safer and faster alternative for acquiring compositional information on nuclear waste slurries.

Evaluation of a compact composite sensor array for concentration monitoring of solutions and suspensions via multivariate analysis

Compact composite probes were identified as a priority to alleviate space constraints in miniaturized unit operations and pharmaceutical manufacturing platforms. Therefore, in this proof of principle study, a compact composite sensor array (CCSA) combining ultraviolet and near infrared features at four different wavelengths (280, 340, 600, 860 nm) in a 380 × 30 mm housing (length x diameter, 7 mm diameter at the probe head), was evaluated for its capabilities to monitor in situ concentration of solutions and suspensions via multivariate analysis using partial least squares (PLS) regression models. Four model active pharmaceutical ingredients (APIs): warfarin sodium isopropanol solvate (WS), lidocaine hydrochloride monohydrate (LID), 6-mercaptopurine monohydrate (6-MP), and acetaminophen (ACM) in their aqueous solution and suspension formulation were used for the assessment. The results demonstrate that PLS models can be applied for the CCSA prototype to measure the API concentrations with similar accuracy (validation samples within the United States Pharmacopeia (USP) limits), compared to univariate CCSA models and multivariate models for an established Raman spectrometer. Specifically, the multivariate CCSA models applied to the suspensions of 6-MP and ACM demonstrate improved accuracy of 63% and 31%, respectively, compared to the univariate CCSA models [1]. On the other hand, the PLS models for the solutions WS and LID showed a reduced accuracy compared to the univariate models [1].

On the use of Raman spectroscopy to characterize mass-produced graphene nanoplatelets

Raman spectroscopy is one of the most common methods to characterize graphene-related 2D materials, providing information on a wide range of physical and chemical properties. Because of typical sample inhomogeneity, Raman spectra are acquired from several locations across a sample, and analysis is carried out on the averaged spectrum from all locations. This is then used to characterize the "quality" of the graphene produced, in particular the level of exfoliation for top-down manufactured materials. However, these have generally been developed using samples prepared with careful separation of unexfoliated materials. In this work we assess these metrics when applied to non-ideal samples, where unexfoliated graphite has been deliberately added to the exfoliated material. We demonstrate that previously published metrics, when applied to averaged spectra, do not allow the presence of this unexfoliated material to be reliably detected. Furthermore, when a sufficiently large number of spectra are acquired, it is found that by processing and classifying individual spectra, rather than the averaged spectrum, it is possible to identify the presence of this material in the sample, although quantification of the amount remains approximate. We therefore recommend this approach as a robust methodology for reliable characterization of mass-produced graphene-related 2D materials using confocal Raman spectroscopy.

A Review of Pharmaceutical Robot based on Hyperspectral Technology

The quality and safety of medicinal products are related to patients’ lives and health. Therefore, quality inspection takes a key role in the pharmaceutical industry. Most of the previous solutions are based on machine vision, however, their performance is limited by the RGB sensor. The pharmaceutical visual inspection robot combined with hyperspectral imaging technology is becoming a new trend in the high-end medical quality inspection process since the hyperspectral data can provide spectral information with spatial knowledge. Yet, there is no comprehensive review about hyperspectral imaging-based medicinal products inspection. This paper focuses on the pivotal pharmaceutical applications, including counterfeit drugs detection, active component analysis of tables, and quality testing of herbal medicines and other medical materials. We discuss the technology and hardware of Raman spectroscopy and hyperspectral imaging, firstly. Furthermore, we review these technologies in pharmaceutical scenarios. Finally, the development tendency and prospect of hyperspectral imaging technology-based robots in the field of pharmaceutical quality inspection is summarized.

Enantioselective synthesis of (−)-tetrabenazine via continuous crystallization-induced diastereomer transformation

A multi-well continuous CIDT approach with inline racemization of the solution phase is presented. Using two in-house built PATs and a flow reactor, we were able to successfully crystallize an enantiopure salt of TBZ, the active metabolite of the tardive dyskinesia drug valbenazine. Despite discovering an undesired racemic solid phase, inline racemization combined with careful control of crystallization conditions allowed for multigram quantities of enantiopure material to be harvested using our setup. Critically, this control was made possible by the use of PATs to observe and quantify the composition of both the solid and solution phases.

A novel enantioselective route to tetrabenazine has been developed using continuous CIDT in a multiwell crystallization/racemization device outfitted with real-time HPLC to visualize and control the dynamic process.

Polymorph control in batch seeded crystallizers. A case study with paracetamol

We show that seeding is not always sufficient to control cystal polymorphism and illustrate how kinetic modeling can help controlling polymorphism.

Hyperspectral Imaging Using Laser Excitation for Fast Raman and Fluorescence Hyperspectral Imaging for Sorting and Quality Control Applications

A hyperspectral measurement system for the fast and large area measurement of Raman and fluorescence signals was developed, characterized and tested. This laser hyperspectral imaging system (Laser-HSI) can be used for sorting tasks and for continuous quality monitoring. The system uses a 532 nm Nd:YAG laser and a standard pushbroom HSI camera. Depending on the lens selected, it is possible to cover large areas (e.g., field of view (FOV) = 386 mm) or to achieve high spatial resolutions (e.g., 0.02 mm). The developed Laser-HSI was used for four exemplary experiments: (a) the measurement and classification of a mixture of sulphur and naphthalene; (b) the measurement of carotenoid distribution in a carrot slice; (c) the classification of black polymer particles; and, (d) the localization of impurities on a lead zirconate titanate (PZT) piezoelectric actuator. It could be shown that the measurement data obtained were in good agreement with reference measurements taken with a high-resolution Raman microscope. Furthermore, the suitability of the measurements for classification using machine learning algorithms was also demonstrated. The developed Laser-HSI could be used in the future for complex quality control or sorting tasks where conventional HSI systems fail.

Pharmaceutical cocrystals, salts and polymorphs: Advanced characterization techniques

The main goal of a novel drug development is to obtain it with optimal physiochemical, pharmaceutical and biological properties. Pharmaceutical companies and scientists modify active pharmaceutical ingredients (APIs), which often are cocrystals, salts or carefully selected polymorphs, to improve the properties of a parent drug. To find the best form of a drug, various advanced characterization methods should be used. In this review, we have described such analytical methods, dedicated to solid drug forms. Thus, diffraction, spectroscopic, thermal and also pharmaceutical characterization methods are discussed. They all are necessary to study a solid API in its intrinsic complexity from bulk down to the molecular level, gain information on its structure, properties, purity and possible transformations, and make the characterization efficient, comprehensive and complete. Furthermore, these methods can be used to monitor and investigate physical processes, involved in the drug development, in situ and in real time. The main aim of this paper is to gather information on the current advancements in the analytical methods and highlight their pharmaceutical relevance.

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.

In-line ATR-UV and Raman Spectroscopy for Monitoring API Dissolution Process During Liquid-Filled Soft-Gelatin Capsule Manufacturing

Complete dissolution of the active pharmaceutical ingredient (API) is critical in the manufacturing of liquid-filled soft-gelatin capsules (SGC). Attenuated total reflectance UV spectroscopy (ATR-UV) and Raman spectroscopy have been investigated for in-line monitoring of API dissolution during manufacturing of an SGC product. Calibration models have been developed with both techniques for in-line determination of API potency. Performance of both techniques was evaluated and compared. The ATR-UV methodology was found to be able to monitor the dissolution process and determine the endpoint, but was sensitive to temperature variations. The Raman technique was also capable of effectively monitoring the process and was more robust to the temperature variation and process perturbations by using an excipient peak for internal correction. Different data preprocessing methodologies were explored in an attempt to improve method performance.

Applications of Quantum Cascade Laser Spectroscopy in the Analysis of Pharmaceutical Formulations

Quantum cascade laser spectroscopy was used to quantify active pharmaceutical ingredient content in a model formulation. The analyses were conducted in non-contact mode by mid-infrared diffuse reflectance. Measurements were carried out at a distance of 15 cm, covering the spectral range 1000-1600 cm(-1) Calibrations were generated by applying multivariate analysis using partial least squares models. Among the figures of merit of the proposed methodology are the high analytical sensitivity equivalent to 0.05% active pharmaceutical ingredient in the formulation, high repeatability (2.7%), high reproducibility (5.4%), and low limit of detection (1%). The relatively high power of the quantum-cascade-laser-based spectroscopic system resulted in the design of detection and quantification methodologies for pharmaceutical applications with high accuracy and precision that are comparable to those of methodologies based on near-infrared spectroscopy, attenuated total reflection mid-infrared Fourier transform infrared spectroscopy, and Raman spectroscopy.

Analytical technologies for real-time drug dissolution and precipitation testing on a small scale

Objectives

This review focuses on real-time analytics of drug dissolution and precipitation testing on a comparatively small scale.

Key findings

Miniaturisation of test equipment is an important trend in pharmaceutics, and several small-scale experiments have been reported for drug dissolution and precipitation testing. Such tests typically employ analytics in real-time. Fibre optic ultraviolet (UV) analytics has become a well-established method in this field. Novel imaging techniques are emerging that use visible or UV light; also promising is Fourier transform infrared imaging based on attenuated total reflection. More information than just a rate constant is obtained from these methods. The early phase of a dissolution process can be assessed and drug precipitation may eventually be observed. Some real-time techniques are particularly well suited to studying drug precipitation during formulation dispersion; for example, turbidity, focused beam reflectance measurement and Raman spectroscopy.

Summary

Small-scale dissolution tests equipped with real-time analytics have become important to screen drug candidates as well as to study prototype formulations in early development. Future approaches are likely to combine different analytical techniques including imaging. Miniaturisation started with mini-vessels or small vials and future assays of dissolution research will probably more often reach the level of parallel well plates and microfluidic channels.

Characterisation of crystalline-amorphous blends of sucrose with terahertz-pulsed spectroscopy: the development of a prediction technique for estimating the degree of crystallinity with partial least squares regression

The control of the amorphous and crystalline states of drugs and excipients is important in many instances of product formulation, manufacture, and packaging, such as the formulation of certain (freeze-dried) fast melt tablets. This study examines the use of terahertz-pulsed spectroscopy (TPS) coupled with two different data analytical methods as an off-line tool (in the first instance) for assessing the degree of crystallinity in a binary mixture of amorphous and polycrystalline sucrose. The terahertz spectrum of sucrose was recorded in the wave number range between 3 and 100 cm(-1) for both the pure crystalline form and for a mixture of the crystalline and amorphous (freeze-dried) form. The THz spectra of crystalline sucrose showed distinct absorption bands at ∼48, ∼55, and ∼60 cm(-1) while all these features were absent in the amorphous sucrose. Calibration models were constructed based on (1) peak area analysis and (2) partial least square regression analysis, with the latter giving the best LOD and LOQ of 0.76% and 2.3%, respectively. The potential for using THz spectroscopy, as a quantitative in-line tool for percent crystallinity in a range of complex systems such as conventional tablets and freeze-dried formulations, is suggested in this study.

Advances and New Directions in Crystallization Control

The academic literature on and industrial practice of control of solution crystallization processes have seen major advances in the past 15 years that have been enabled by progress in in-situ real-time sensor technologies and driven primarily by needs in the pharmaceutical industry for improved and more consistent quality of drug crystals. These advances include the accurate measurement of solution concentrations and crystal characteristics as well as the first-principles modeling and robust model-based and model-free feedback control of crystal size and polymorphic identity. Research opportunities are described in model-free controller design, new crystallizer designs with enhanced control of crystal size distribution, strategies for the robust control of crystal shape, and interconnected crystallization systems for multicomponent crystallization.

Quantitative analysis of powder mixtures by Raman spectrometry: the influence of particle size and its correction

Particle size distribution and compactness have significant confounding effects on Raman signals of powder mixtures, which cannot be effectively modeled or corrected by traditional multivariate linear calibration methods such as partial least-squares (PLS), and therefore greatly deteriorate the predictive abilities of Raman calibration models for powder mixtures. The ability to obtain directly quantitative information from Raman signals of powder mixtures with varying particle size distribution and compactness is, therefore, of considerable interest. In this study, an advanced quantitative Raman calibration model was developed to explicitly account for the confounding effects of particle size distribution and compactness on Raman signals of powder mixtures. Under the theoretical guidance of the proposed Raman calibration model, an advanced dual calibration strategy was adopted to separate the Raman contributions caused by the changes in mass fractions of the constituents in powder mixtures from those induced by the variations in the physical properties of samples, and hence achieve accurate quantitative determination for powder mixture samples. The proposed Raman calibration model was applied to the quantitative analysis of backscatter Raman measurements of a proof-of-concept model system of powder mixtures consisting of barium nitrate and potassium chromate. The average relative prediction error of prediction obtained by the proposed Raman calibration model was less than one-third of the corresponding value of the best performing PLS model for mass fractions of barium nitrate in powder mixtures with variations in particle size distribution, as well as compactness.