Comparison of sampling techniques for in-line monitoring using Raman spectroscopy

Non-destructive Raman Method Development for Quantifying Active Pharmaceutical Ingredient in an Oral Suspension Through Plastic Dosing Syringes

For liquid drug products, e.g., solutions or suspensions for oral or parenteral dosing, stability needs to be demonstrated in primary packaging during storage and in dosing devices during in-use periods per quality guidelines from the International Conference on Harmonisation (ICH) and the European Agency for the Evaluation of Medicinal Products (EMEA). One aspect of stability testing for liquid drug products is in-use stability, which typically includes transferring the liquid samples into another container for further sample preparation with extraction diluent and necessary agitation. Samples are then analyzed with traditional chromatography methods, which are laborious, prone to human errors, and time-consuming, especially when this process needs to be repeated multiple times during storage and in-use periods. Being able to analyze the liquid samples non-destructively would significantly improve testing efficiency. We investigated different Raman techniques, including transmission Raman (TRS) and back scatter Raman with a non-contact optic (NCO) probe, as alternative non-destructive tools to the UHPLC method for API quantitation in in-use liquid samples pulled into plastic dosing syringes. The linearity of the chemometric methods for these two techniques was demonstrated by cross-validation sample sets at three levels over an API concentration range of 60 to 80 mg/mL. The accuracy of the chemometric models was demonstrated by the accurate prediction of the API concentrations in independent samples from four different pilot plant batches manufactured at different sites. Both techniques were successful in measuring a signal through a plastic oral dosing syringe, and predicting the suspension API concentration to within 4% of the UHPLC-measured value. For future work, there are opportunities to improve the methodology by exploring additional probes or to expand the range of applications by using different sample presentations (such as prefilled syringes) or formulation matrices for solutions and suspensions.

In-line Raman spectroscopy for characterization of an industrial poultry raw material stream

In this work, we evaluated the feasibility of Raman spectroscopy as an in-line raw material characterization tool for industrial process control of the hydrolysis of poultry rest raw material. We established calibrations (N = 59) for fat, protein, ash (proxy for bone) and hydroxyproline (proxy for collagen) in ground poultry rest raw material. Calibrations were established in the laboratory using poultry samples with high compositional variation. Samples were measured using a wide area illumination Raman probe at varying working distance (6 cm, 9 cm, 12 cm) and probe tilt angle (0°, 30°) to mimic expected in-line variations in the measurement situation. These moderate variations did not significantly affect performance for any analytes. The obtained calibrations were tested in-line with continuous measurements of the ground poultry by-product stream at a commercial hydrolysis facility over the course of two days. Measurements were acquired under demanding conditions, e.g. large variations in working distance. Reasonable estimates of compositional trends were obtained. Validation samples (N = 19) were also reasonably well predicted, with RMSEPcorr = [0.14, 1.37, 2.36, 1.51]% for hydroxyproline, protein, fat and ash, respectively. However, there were indications that further calibration development and robustification of pre-processing would be advantageous, particularly with respect to hydroxyproline and protein models. It is the authors' impression that with such efforts, potentially in combination with development of practical measurement setup, the use of Raman spectroscopy as a process control tool for the hydrolysis of poultry rest raw materials is within reach.

The role of biospectroscopy and chemometrics as enabling technologies for upcycling of raw materials from the food industry

It is important to utilize the entire animal in meat and fish production to ensure sustainability. Rest raw materials, such as bones, heads, trimmings, and skin, contain essential nutrients that can be transformed into high-value products. Enzymatic protein hydrolysis (EPH) is a bioprocess that can upcycle these materials to create valuable proteins and fats. This paper focuses on the role of spectroscopy and chemometrics in characterizing the quality of the resulting protein product and understanding how raw material quality and processing affect it. The article presents recent developments in chemical characterisation and process modelling, with a focus on rest raw materials from poultry and salmon production. Even if some of the technology is relatively mature and implemented in many laboratories and industries, there are still open challenges and research questions. The main challenges are related to the transition of technology and insights from laboratory to industrial scale, and the link between peptide composition and critical product quality attributes.

Raman spectroscopy and NIR hyperspectral imaging for in-line estimation of fatty acid features in salmon fillets

Raman spectroscopy was compared with near infrared (NIR) hyperspectral imaging for determination of fat composition (%EPA + DHA) in salmon fillets at short exposure times. Fillets were measured in movement for both methods. Salmon were acquired from several different farming locations in Norway with different feeding regimes, representing a realistic variation of salmon in the market. For Raman, we investigated three manual scanning strategies; i) line scan of loin, ii) line scan of belly and iii) sinusoidal scan of belly at exposure times of 2s and 4s. NIR images were acquired while the fillets moved on a conveyor belt at 40 cm/s, which corresponds to an acquisition time of 1s for a 40 cm long fillet. For NIR images, three different regions of interest (ROI) were investigated including the i) whole fillet, ii) belly segment, and iii) loin segment. For both Raman and NIR measurements, we investigated an untrimmed and trimmed version of the fillets, both relevant for industrial in-line evaluation. For the trimmed fillets, a fat rich deposition layer in the belly was removed. The %EPA + DHA models were validated by cross validation (N = 51) and using an independent test set (N = 20) which was acquired in a different season. Both Raman and NIR showed promising results and high performances in the cross validation, with R2_CV = 0.96 for Raman at 2s exposure and R2_CV = 0.97 for NIR. High performances were obtained also for the test set, but while Raman had low and stable biases for the test set, the biases were high and varied for the NIR measurements. Analysis of variance on the squared test set residuals showed that performance for Raman measurements were significantly higher than NIR at 1% significance level (p = 0.000013) when slope-and-bias errors were not corrected, but not significant when residuals were slope-and-bias corrected (p = 0.28). This indicated that NIR was more sensitive to matrix effects. For Raman, signal-to-noise ratio was the main limitation and there were indications that Raman was close to a critical sample exposure time at the 2s signal accumulation.

Evaluation of a Raman Chemometric Method for Detecting Protein Structural Conformational Changes in Solution

Raman scattering shows promise as a powerful routine tool, to determine both secondary and the smaller tertiary structural changes that precede aggregation in both solutions and solids. A method was developed utilizing principal component analysis (PCA) of Raman spectra for detection of small, but meaningful, pH induced changes in tertiary protein structure linked to aggregate formation using α-lactalbumin solutions as a model. The sample preparation and spectral parameters, were optimized for a bulk Raman probe. Analysis of large regions (600-1850 cm^-1) yielded principal component (PC) scores useful for semi-quantitative comparison of protein conformation between formulations. PC loadings corresponded to specific structural peaks known to change with solution pH. PCA of circular dichroism (CD) spectra of dilute solutions yielded similar results. Sucrose is a common formulation excipient with a Raman spectrum that overlaps many protein peaks. With sucrose in the protein solution, the ability of PCA to discern protein structural changes from the Raman spectra was somewhat reduced. Analysis of a more limited spectral region (1530-1780 cm^-1) with negligible sucrose spectral contribution improved the discrimination of protein conformational states. The new Raman method accurately distinguished differences in protein structure in concentrated solutions. The long-term goal is to explore Raman characterization as a routine monitoring tool of protein stability in both solution and solid states.

Feasibility of In-Line Raman Spectroscopy for Quality Assessment in Food Industry: How Fast Can We Go?

Raman spectroscopy is a viable tool within process analytical technologies due to recent technological advances. In this article, we evaluate the feasibility of Raman spectroscopy for in-line applications in the food industry by estimating the concentration of the fatty acids EPA + DHA in ground salmon samples (n = 63) and residual bone concentration in samples of mechanically recovered ground chicken (n = 66). The samples were measured under industry like conditions: They moved on a conveyor belt through a dark cabinet where they were scanned with a wide area illumination standoff Raman probe. Such a setup should be able to handle relevant industrial conveyor belt speeds, and it was studied how different speeds (i.e., exposure times) influenced the signal-to-noise ratio (SNR) of the Raman spectra as well as the corresponding model performance. For all samples we applied speeds that resulted in 1 s, 2 s, 4 s, and 10 s exposure times. Samples were scanned in both heterogenous and homogenous state. The slowest speed (10 s exposure) yielded prediction errors (RMSECV) of 0.41%EPA + DHA and 0.59% ash for the salmon and chicken data sets, respectively. The more in-line relevant exposure time of 1 s resulted in increased RMSECV values, 0.84% EPA + DHA and 0.84% ash, respectively. The increase in prediction error correlated closely with the decrease in SNR. Further improvements of model performance were possible through different noise reduction strategies. Model performance for homogenous and heterogenous samples was similar, suggesting that the presented Raman scanning approach has the potential to work well also on intact heterogenous foods. The estimation errors obtained at these high speeds are likely acceptable for industrial use, but successful strategies to increase SNR will be key for widespread in-line use in the food industry.

Assessment of Bulk Composition of Heterogeneous Food Matrices Using Raman Spectroscopy

Raman spectroscopy (RS) has for decades been considered a promising tool for food analysis, but widespread adoption has been held back by, e.g., high instrument costs and sampling limitations regarding heterogeneous samples. The aim of the present study was to use wide area RS in conjunction with surface scanning to overcome the obstacle of heterogeneity. Four different food matrices were scanned (intact and homogenized pork and by-products from salmon and poultry processing) and the bulk chemical parameters such as fat and protein content were estimated using partial least squares regression (PLSR). The performance of PLSR models from RS was compared with near-infrared spectroscopy (NIRS). Good to excellent results were obtained with PLSR models from RS for estimation of fat content in all food matrices (coefficient of determination for cross-validation (R²_CV) from 0.73 to 0.96 and root mean square error of cross-validation (RMSECV) from 0.43% to 2.06%). Poor to very good PLSR models were obtained for estimation of protein content in salmon and poultry by-product using RS (R²_CV from 0.56 to 0.92 and RMSECV from 0.85% to 0.94%). The performance of RS was similar to NIRS for all analyses. This work demonstrates the applicability of RS to analyze bulk composition in heterogeneous food matrices and paves way for future applications of RS in routine food analyses.

Spatial Heterodyne Raman Spectrometer (SHRS) for In Situ Chemical Sensing Using Sapphire and Silica Optical Fiber Raman Probes

A spatial heterodyne Raman spectrometer (SHRS), constructed using a modular optical cage and lens tube system, is described for use with a commercial silica and a custom single-crystal (SC) sapphire fiber Raman probe. The utility of these fiber-coupled SHRS chemical sensors is demonstrated using 532 nm laser excitation for acquiring Raman measurements of solid (sulfur) and liquid (cyclohexane) Raman standards as well as real-world, plastic-bonded explosives (PBX) comprising 1,3,5- triamino- 2,4,6- trinitrobenzene (TATB) and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) energetic materials. The SHRS is a fixed grating-based dispersive interferometer equipped with an array detector. Each Raman spectrum was extracted from its corresponding fringe image (i.e., interferogram) using a Fourier transform method. Raman measurements were acquired with the SHRS Littrow wavelength set at the laser excitation wavelength over a spectral range of ∼1750 cm^-1 with a spectral resolution of ∼8 cm^-1 for sapphire and ∼10 cm^-1 for silica fiber probes. The large aperture of the SHRS allows much larger fiber diameters to be used without degrading spectral resolution as demonstrated with the larger sapphire collection fiber diameter (330 μm) compared to the silica fiber (100 μm). Unlike the dual silica fiber Raman probe, the dual sapphire fiber Raman probe did not include filtering at the fiber probe tip nearest the sample. Even so, SC sapphire fiber probe measurements produced less background than silica fibers allowing Raman measurements as close as ∼85 cm^-1 to the excitation laser. Despite the short lengths of sapphire fiber used to construct the sapphire probe, well-defined, sharp sapphire Raman bands at 420, 580, and 750 cm^-1 were observed in the SHRS spectra of cyclohexane and the highly fluorescent HMX-based PBX. SHRS measurements of the latter produced low background interference in the extracted Raman spectrum because the broad band fluorescence (i.e., a direct current, or DC, component) does not contribute to the interferogram intensity (i.e., the alternating current, or AC, component). SHRS spectral resolution, throughput, and signal-to-noise ratio are also discussed along with the merits of using sapphire Raman bands as internal performance references and as internal wavelength calibration standards in Raman measurements.

Raman Spectroscopy for Process Analytical Technologies of Pharmaceutical Secondary Manufacturing

As the process analytical technology (PAT) mindset is progressively introduced and adopted by the pharmaceutical companies, there is an increasing demand for effective and versatile real-time analyzers to address the quality assurance challenges of drug manufacturing. In the last decades, Raman spectroscopy has emerged as one of the most promising tools for non-destructive and fast characterization of the pharmaceutical processes. This review summarizes the achieved results of the real-time application of Raman spectroscopy in the field of the secondary manufacturing of pharmaceutical solid dosage forms, covering the most common secondary process steps of a tablet production line. In addition, the feasibility of Raman spectroscopy for real-time control is critically reviewed, and challenges and possible approaches to moving from real-time monitoring to process analytically controlled technologies (PACT) are discussed.

Discrimination and quantification of sulfathiazole polytypes using low-frequency Raman spectroscopy

Low-frequency Raman spectroscopy has advantage to discriminate and quantify polymorphs where common 2D superstructures are piled up with different mode.

In-line Raman spectroscopic monitoring and feedback control of a continuous twin-screw pharmaceutical powder blending and tableting process

The integration of Process Analytical Technology (PAT) initiative into the continuous production of pharmaceuticals is indispensable for reliable production. The present paper reports the implementation of in-line Raman spectroscopy in a continuous blending and tableting process of a three-component model pharmaceutical system, containing caffeine as model active pharmaceutical ingredient (API), glucose as model excipient and magnesium stearate as lubricant. The real-time analysis of API content, blend homogeneity, and tablet content uniformity was performed using a Partial Least Squares (PLS) quantitative method. The in-line Raman spectroscopic monitoring showed that the continuous blender was capable of producing blends with high homogeneity, and technological malfunctions can be detected by the proposed PAT method. The Raman spectroscopy-based feedback control of the API feeder was also established, creating a 'Process Analytically Controlled Technology' (PACT), which guarantees the required API content in the produced blend. This is, to the best of the authors' knowledge, the first ever application of Raman-spectroscopy in continuous blending and the first Raman-based feedback control in the formulation technology of solid pharmaceuticals.

Continuous flow synthesis of poly(acrylic acid) via free radical polymerisation

The free radical polymerisation of aqueous solutions of acrylic acid (1) has been studied using a continuous flow reactor to quickly screen reaction parameters such as temperature, residence time, monomer- and initiator concentration.

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.

Anhydrate to hydrate solid-state transformations of carbamazepine and nitrofurantoin in biorelevant media studied in situ using time-resolved synchrotron X-ray diffraction

Transformation of the solid-state form of a drug compound in the lumen of the gastrointestinal tract may alter the drug bioavailability and in extreme cases result in patient fatalities. The solution-mediated anhydrate-to-hydrate phase transformation was examined using an in vitro model with different biorelevant media, simulated fasted and fed state intestinal fluids containing bile salt and dioleoylphosphatidylcholine (DOPC) micelles, DOPC/sodium dodecyl sulfate (SDS) mixture, bile salt solution and water. Two anhydrate compounds (carbamazepine, CBZ and nitrofurantoin, NF) with different overall transformation time into hydrate form were used as model compounds. The transformations were monitored using direct structural information from time-resolved synchrotron X-ray diffraction. The kinetics of these transformations were estimated using multivariate data analysis (principal component analysis, PCA) and compared to those for nitrofurantoin (NF). The study showed that the solution-mediated phase transformation of CBZ anhydrate was remarkably faster in the DOPC/SDS medium compared to transformation in all the other aqueous dispersion media. The conversion time for CBZ anhydrate in water was shorter than for DOPC/SDS but still faster than the conversion seen in fed and fasted state micellar media. The conversion of CBZ anhydrate to hydrate was the slowest in the solution containing bile salt alone. In contrast, the solution-mediated phase transformations of NF did only show limited kinetic dependence on the dispersion media used, indicating the complexity of the nucleation process. Furthermore, when the CBZ and NF material was compacted into tablets the transformation times were remarkably slower. Results suggest that variations in the composition of the contents of the stomach/gut may affect the recrystallization kinetics, especially when investigating compounds with relatively fast overall transformation time, such as CBZ.

Feasibility for non-destructive discrimination of natural and beryllium-diffused sapphires using Raman spectroscopy

Raman spectroscopy based non-destructive discrimination between natural and beryllium-diffused (Be-diffused) sapphires has been attempted. The initial examination of Raman image acquired on a sapphire revealed that microscopic structural and compositional heterogeneity was apparent in the sample, so acquisition of spectra able to represent a whole body of sapphire rather than a localized area was necessary for a reliable discrimination. For this purpose, a wide area illumination (WAI) scheme (illumination area: 28.3mm(2)) providing a large sampling volume was employed to collect representative Raman spectra of sapphires. Upon the diffusion of Be into a sapphire, the band shift originated from varied lattice structure by substitution of Be at cation sites was observed and utilized as a valuable spectral signature for the discrimination. In the domain of principal component (PC) scores, the groups of natural and Be-diffused sapphires were identifiable with minor overlapping and the cross-validated discrimination error was 7.3% when k-Nearest Neighbor (k-NN) was used as a classifier.

A novel approach for subsurface through-skin analysis of salmon using spatially offset Raman spectroscopy (SORS)

In the present study, the possibility of employing spatially offset Raman spectroscopy (SORS) in the qualitative and quantitative characterization of quality parameters of salmon through the skin has been explored. A laboratory-based SORS setup comprising an 830 nm laser was employed, and intact samples and model samples made of salmon tissue constituents were used to investigate the penetration of Raman signals through the dark and light part of salmon skin. Intact salmon samples with both dark and light skin were measured at different spatial offsets. When using spatial offsets in the range of 5-6 mm, the results clearly show that information regarding fatty acid composition and carotenoid content could be obtained from both dark and light parts of the skin. Similar information could not be obtained using conventional backscattering Raman spectroscopy. Model samples of ground salmon spiked with either solutions of carotenoids or a range of vegetable oils were also measured, and at a spatial offset of 5 mm, a clear relationship between Raman carotenoid band intensities and carotenoid concentrations in the model samples was revealed. In addition, high correlations for the estimation of iodine values (i.e., fatty acid unsaturation) could be obtained for SORS measurements through light and dark parts of the salmon skin. A crude estimate suggested that information from around 5 mm beneath the surface area of the salmon skin could be obtained. The choice of a laser line in the near-infrared region is a major prerequisite for successful through-skin analysis of salmon. This feasibility study could pave the way for future Raman analysis of intact salmon.

Wide area coverage Raman spectroscopy for reliable quantitative analysis and its applications

This review summarizes recent studies to improve sample representation in Raman measurement by covering a large area of a sample in spectral collection. Three different schemes have been mainly investigated to fulfill the goal: (1) averaging of Raman spectra collected at many different locations on a sample, (2) rotation of a sample during spectral collection and (3) simultaneous wide area illumination (WAI) for spectral collection. The use of a wide area illumination scheme, simultaneously illuminating a laser over a large area for spectral acquisition without any further assistance such as sample rotation, has increased in diverse fields. Applications employing the WAI scheme in pharmaceutical, polymer/chemical/petrochemical and other areas are described in this review.

In situ monitoring of powder blending by non-invasive Raman spectrometry with wide area illumination

A 785nm diode laser and probe with a 6mm spot size were used to obtain spectra of stationary powders and powders mixing at 50rpm in a high shear convective blender. Two methods of assessing the effect of particle characteristics on the Raman sampling depth for microcrystalline cellulose (Avicel), aspirin or sodium nitrate were compared: (i) the information depth, based on the diminishing Raman signal of TiO(2) in a reference plate as the depth of powder prior to the plate was increased, and (ii) the depth at which a sample became infinitely thick, based on the depth of powder at which the Raman signal of the compound became constant. The particle size, shape, density and/or light absorption capability of the compounds were shown to affect the "information" and "infinitely thick" depths of individual compounds. However, when different sized fractions of aspirin were added to Avicel as the main component, the depth values of aspirin were the same and matched that of the Avicel: 1.7mm for the "information" depth and 3.5mm for the "infinitely thick" depth. This latter value was considered to be the minimum Raman sampling depth when monitoring the addition of aspirin to Avicel in the blender. Mixing profiles for aspirin were obtained non-invasively through the glass wall of the vessel and could be used to assess how the aspirin blended into the main component, identify the end point of the mixing process (which varied with the particle size of the aspirin), and determine the concentration of aspirin in real time. The Raman procedure was compared to two other non-invasive monitoring techniques, near infrared (NIR) spectrometry and broadband acoustic emission spectrometry. The features of the mixing profiles generated by the three techniques were similar for addition of aspirin to Avicel. Although Raman was less sensitive than NIR spectrometry, Raman allowed compound specific mixing profiles to be generated by studying the mixing behaviour of an aspirin-aspartame-Avicel mixture.

Measurement of spatial resolution and sensitivity in transmission and backscattering Raman spectroscopy of opaque samples: impact on pharmaceutical quality control and Raman tomography

A practical methodology is described that allows measurement of spatial resolution and sensitivity of Raman spectroscopy in backscatter and transmission modes under conditions where photon migration dominates, i.e., with turbid or opaque samples. For the first time under such conditions the width and intensity of the point spread function (PSF) has been accurately measured as a function of sample thickness and depth below the surface. In transmission mode, the lateral resolution for objects in the bulk degraded linearly with sample thickness, but the resolution was much better for objects near either surface, being determined by the diameter of the probe beam and collection aperture irrespective of sample thickness. In other words, buried objects appear to be larger than ones near either surface. The absolute transmitted signal decreased significantly with sample thickness, but objects in the bulk yielded higher signals than those at either surface. In transmission, materials are sampled preferentially in the bulk, which has ramifications for quantitative analysis. In backscattering mode, objects near the probed surface were detected much more effectively than in the bulk, and the resolution worsened linearly with depth below the surface. These results are highly relevant in circumstances in which one is trying to detect or image buried objects in opaque media, for example Raman tomography of biological tissues or compositional and structural analysis of pharmaceutical tablets. Finally, the observations were in good agreement with Monte Carlo simulations and, provided one is in the diffusion regime, were insensitive to the choice of transport length, which shows that a simple model can be used to predict instrument performance for a given excitation and collection geometry.

Determination of amorphous content in the pharmaceutical process environment

The amorphous state has different chemical and physical properties compared with a crystalline one. Amorphous regions in an otherwise crystalline material can affect the bioavailability and the processability. On the other hand, crystalline material can function as nuclei and decrease the stability of an amorphous system. The aim of this study was to determine amorphous content in a pharmaceutical process environment using near infrared (NIR) and Raman spectroscopic techniques together with multivariate modelling tools. Milling was used as a model system for process-induced amorphization of a crystalline starting material, α-lactose monohydrate. In addition, the crystallization of amorphous material was studied by storing amorphous material, either amorphous lactose or trehalose, at high relative humidity conditions. The results show that both of the spectroscopic techniques combined with multivariate methods could be applied for quantitation. Preprocessing, as well as the sampling area, was found to affect the performance of the models. Standard normal variate (SNV) transformation was the best preprocessing approach and increasing the sampling area was found to improve the models. The root mean square error of prediction (RMSEP) for quantitation of amorphous lactose using NIR spectroscopy was 2.7%, when a measuring setup with a larger sampling area was used. When the sampling area was smaller, the RMSEPs for lactose and trehalose were 4.3% and 4.2%, respectively. For Raman spectroscopy, the RMSEPs were 2.3% and 2.5% for lactose and trehalose, respectively. However, for the optimal performance of a multivariate model, all the physical forms present, as well as the process environment itself, have to be taken into consideration.

Drug product characterization by Macropixel Analysis of chemical images

Traditional monitoring of pharmaceutical manufacturing combines physical sampling and analytical methodologies (e.g. HPLC). Process analytical technology (PAT) can be implemented to collect real-time measurements, although successful monitoring requires that sampling be representative. The maximum spot size for a spectroscopic tool (e.g. near-infrared; Raman) should be equivalent to a single dosage size. A smaller spot size may provide a PAT tool that is sensitive to monitoring process changes, but if too small, produces non-reproducible data. The current study uses chemical imaging to determine appropriate spot size. A chemical image is an array of pixels which maps the chemical composition of the sample. "Macropixel Analysis" is introduced as a measure of image heterogeneity based on clusters of pixels (macropixels) within near-infrared chemical images. Analyses were conducted using non-overlapping tiles of macropixels (Discrete-Level Tiling) and all possible macropixels of the image (Continuous-Level Moving Block). Both methods minimize the variance between macropixel intensities by varying the size of the macropixels. Spot size is then chosen as the minimum macropixel size for which the range of macropixel intensities falls within an acceptable criterion. Both imaging-based algorithms provide useful quantitative information about the heterogeneity of pharmaceutical products.

Process analytical applications of Raman spectroscopy

There is an increasing demand for new approaches to understand the chemical and physical phenomena that occur during pharmaceutical unit operations. Obtaining real-time information from processes opens new perspectives for safer and more efficient manufacture of pharmaceuticals. Raman spectroscopy provides a molecular level insight into processing, and therefore it is a future process analytical tool. In this review, different applications of Raman spectroscopy in the field of process analysis of pharmaceutical solid dosage forms are summarized. In addition, pitfalls associated with interfacing to the process environment and challenges within data management are discussed.

Influence of sample characteristics on quantification of carbamazepine hydrate formation by X-ray powder diffraction and Raman spectroscopy

This study aimed to assess the suitability of two widely utilized solid state characterization techniques namely powder X-ray diffraction (XRPD) and Raman spectroscopy, in polymorph detection and quantification for carbamazepine anhydrate and dihydrate mixtures. The influences of particle size, particle morphology, mixing, and in particular, surface bias on quantitation were investigated. Binary mixtures of carbamazepine anhydrate (form III) and dihydrate were prepared and analyzed using both XRPD and Raman spectroscopy in combination with partial least squares analysis. It was found that in principle both XRPD and Raman spectroscopy could be used to build calibration models for quantitative analysis, and a satisfactory correlation between the two techniques could be achieved. However, Raman spectroscopy appeared to be a more reliable quantification method because problems such as different particle size, morphology, and special distribution of the two solid state forms of the drug seemed to have no significant influence on Raman scattering in this study. The robust nature of Raman analysis greatly facilitates the whole quantification process from the preparation of calibration models to the quantification of in situ CBZ-DH conversion.

Drug characterization in low dosage pharmaceutical tablets using Raman microscopic mapping

Raman micro-spectroscopic mapping is utilized to analyze pharmaceutical tablets containing a low concentration (0.5% w/w) of active pharmaceutical ingredient (API). The domain sizes and spatial distributions of the API and the major excipients are obtained. Domain size of the API is found to be dependent upon the particle size distribution of the ingoing API material, making the Raman maps good indicators of the source of API used in tablet manufacturing. Multivariate classification was performed to simultaneously check for the presence of two undesired API polymorphs within tablets. Raman mapping was demonstrated capable of detecting in the tablet matrix as little as 10% form conversion of the low-dosage (0.5% w/w) API, which is equivalent to detection of a 0.05% w/w polymorphic impurity. Overall, the information provided by Raman micro-spectroscopic mapping was found to have potential utility for manufacturing process optimization or predictive stability assessments.

Analysis of the effect of particle size on polymorphic quantitation by Raman spectroscopy

Raman spectroscopy has been widely used to monitor various aspects of the crystallization process. Although it has long been known that particle size can influence Raman signal, relatively little research has been conducted in this area, in particular for mixtures of organic materials. The aim of this study was to investigate the effect of particle size on quantification of polymorphic mixtures. Several sets of calibration samples containing different particle size fractions were prepared and Raman spectra were collected with different probes. Calibration models were built using both univariate and multivariate analysis. It was found that, for a single component system, Raman intensity decreased with increasing particle size. For mixtures, calibration models generated from the same particle size distribution as the sample yielded relatively good predictions of the actual sample composition. However, if the particle sizes of the calibration and unknown samples were different, prediction errors resulted. For extreme differences in particle sizes, prediction errors of up to 20% were observed. Prediction errors could be minimized by changing the sampling optics employed.

On-line content uniformity determination of tablets using low-resolution Raman spectroscopy

Analytical techniques for rapid and nondestructive content uniformity determination of pharmaceutical solid dosage forms have been studied for several years in an effort to replace the traditional wet chemistry procedures, which are labor intensive and time consuming. Both Raman spectroscopy and near-infrared spectroscopy have been used for this purpose, and predictability errors are approaching those of the traditional techniques. In this study, a low-resolution Raman spectrometer was utilized to demonstrate the feasibility of both rapid at-line and on-line determination of tablet content uniformity. Additionally, sampling statistics were reviewed in an effort to determine how many tablets should be assayed for specific batch sizes. A good correlation was observed between assay values determined by high-performance liquid chromatography and Raman analysis. Due to rapid acquisition times for the Raman data, it was possible to analyze far more samples than with wet chemistry methods, leading to a better statistical description of variation within the batch. For at-line experiments, the sampling volume was increased by rotating the laser beam during the acquisition period. For the on-line experiments, the sampling volume was increased by sampling from a stream of tablets moving underneath the Raman probe on a conveyor system. Finally, an approach is proposed for monitoring content uniformity immediately following the compaction process. In conclusion, Raman spectroscopy has potential as a rapid, nondestructive technique for at- or on-line determination of tablet content uniformity.

Subsurface Raman spectroscopy and mapping using a globally illuminated non-confocal fiber-optic array probe in the presence of Raman photon migration

We report the use of a fiber-optic probe with global illumination and an array of 50 collection fibers (PhAT probe, Kaiser Optical Systems, Inc.) to obtain Raman spectra and 50 spatial element maps of polymers through overlayers of other polymers that are highly scattering. Band target entropy minimization (BTEM) is used to recover the spectra of the subsurface components and generate maps of their distributions. This approach to subsurface mapping is tested with model systems consisting of two or three layers of polyethylene, polytetrafluoroethylene (Teflon), and polyoxymethylene (Delrin) arranged in different geometries. Raman spectra and maps were obtained through overlayer thicknesses of up to 13 mm. Subsurface spatial resolution is achieved because each fiber views an asymmetric distribution of Raman scattered light from surface and subsurface components that depends on the position of the fiber relative to the depth and position of a component and the extent of photon diffusion through the system.

Improved understanding of factors contributing to quantification of anhydrate/hydrate powder mixtures

Different spectroscopic approaches have proved to be excellent analytical tools for monitoring process-induced transformations of active pharmaceutical ingredients during pharmaceutical unit operations. In order to use these tools effectively, it is necessary to build calibration models that describe the relationship between the amount of each solid-state form of interest and the spectroscopic signal. In this study, near-infrared (NIR) and Raman spectroscopic methods have been evaluated for the quantification of hydrate and anhydrate forms in pharmaceutical powders. Process type spectrometers were used to collect the data and the role of the sampling procedure was examined. Multivariate regression models were compared with traditional univariate calibrations and special emphasis was placed on data treatment prior to multivariate modeling by partial least squares (PLS). It was found that the measured sample volume greatly affected the performance of the model whereby the calibrations were significantly improved by utilizing a larger sampling area. In addition, multivariate regression did not always improve the predictability of the data compared to univariate analysis. The data treatment prior to multivariate modeling had a significant influence on the quality of predictions with standard normal variate transformation generally proving to be the best preprocessing method. When the appropriate sampling techniques and data analysis methods were utilized, both NIR and Raman spectroscopy were found to be suitable methods for the quantification of anhydrate/hydrate in powder systems, and thus the method of choice will depend on the conditions in the process under investigation.