Application of quantitative Raman spectroscopy for the monitoring of polymorphic transformation in crystallization processes using a good calibration practice procedure

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.

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.

Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy

Raman spectroscopy is a well-established technique for the molecular characterisation of samples and does not require extensive pre-analytical processing for complex cosmetic products. As an illustration of its potential, this study investigates the quantitative performance of Raman spectroscopy coupled with partial least squares regression (PLSR) for the analysis of Alginate nanoencapsulated Piperonyl Esters (ANC-PE) incorporated into a hydrogel. A total of 96 ANC-PE samples covering a 0.4% w/w-8.3% w/w PE concentration range have been prepared and analysed. Despite the complex formulation of the sample, the spectral features of the PE can be detected and used to quantify the concentrations. Using a leave-K-out cross-validation approach, samples were divided into a training set (n = 64) and a test set, samples that were previously unknown to the PLSR model (n = 32). The root mean square error of cross-validation (RMSECV) and prediction (RMSEP) was evaluated to be 0.142% (w/w PE) and 0.148% (w/w PE), respectively. The accuracy of the prediction model was further evaluated by the percent relative error calculated from the predicted concentration compared to the true value, yielding values of 3.58% for the training set and 3.67% for the test set. The outcome of the analysis demonstrated the analytical power of Raman to obtain label-free, non-destructive quantification of the active cosmetic ingredient, presently PE, in complex formulations, holding promise for future analytical quality control (AQC) applications in the cosmetics industry with rapid and consumable-free analysis.

Developing In Situ Chemometric Models with Raman Spectroscopy for Monitoring an API Disproportionation with a Complex Polymorphic Landscape

An in situ Raman method was developed to characterize the disproportionation of two salts involving a complex polymorphic landscape comprising up to two metastable and one stable freebase forms. Few precedents exist for Raman calibration procedures for solid form quantitation involving more than two polymorphs, while no literature examples were found for cases with multiple metastable forms. Therefore, a new Raman calibration procedure was proposed by directly using disproportionation experiments to generate multiple calibration samples encompassing a range of polymorph ratios through in-line Raman measurements complemented by off-line reference X-ray diffraction measurements. The developed Raman methods were capable of accurately quantitating each solid form in situ when solid concentration variation was incorporated into the calibration dataset. The kinetic understanding of the thermodynamically driven polymorphic conversions gained from this Raman method guided the selection of the salt best suited for the delivery of the active ingredient in the drug product. This work provided a spectroscopic and mathematical approach for simultaneously quantitating multiple polymorphs from a complex mixture of solids with the objective of real-time monitoring.

Multicomponent Chiral Quantification with Ultraviolet Circular Dichroism Spectroscopy: Ternary and Quaternary Phase Diagrams of Levetiracetam

Chiral molecules are challenging for the pharmaceutical industry because although physical properties of the enantiomers are the same in achiral systems, they exhibit different effects in chiral systems, such as the human body. The separation of enantiomers is desired but complex, as enantiomers crystallize most often as racemic compounds. A technique to enable the chiral separation of racemic compounds is to create an asymmetry in the thermodynamic system by generating chiral cocrystal(s) using a chiral coformer and using the solubility differences to enable separation through crystallization from solution. However, such quaternary systems are complex and require analytical methods to quantify different chiral molecules in solution. Here, we develop a new chiral quantification method using ultraviolet-circular dichroism spectroscopy and multivariate partial least squares calibration models, to build multicomponent chiral phase diagrams. Working on the quaternary system of (R)- and (S)-2-(2-oxopyrrolidin-1-yl)butanamide enantiomers with (S)-mandelic acid in acetonitrile, we measure accurately the full quaternary phase diagram for the first time. By understanding the phase stabilities of the racemic compound and the enantiospecific cocrystal, the chiral resolution of levetiracetam could be designed due to a large asymmetry in overall solubility between both sides of the racemic composition. This new method offers improvements for chiral molecule quantification in complex multicomponent chiral systems and can be applied to other chiral spectroscopy techniques.

Calibration-free PAT: Locating selective crystallization or precipitation sweet spot in screenings with multi-way PARAFAC models

When developping selective crystallization or precipitation processes, biopharmaceutical modalities require empirical screenings and analytics tailored to the specific needs of the target molecule. The multi-way chemometric approach called parallel factor analysis (PARAFAC) coupled with ultraviolet visible light (UV/Vis) spectroscopy is able to predict specific concentrations and spectra from highly structured data sets without the need for calibration samples and reference analytics. These calculated models can provide exploratory information on pure species spectra and concentrations in all analyzed samples by representing one model component with one species. In this work, protein mixtures, monoclonal antibodies, and virus-like particles in chemically defined and complex solutions were investigated in three high-throughput crystallization or precipitation screenings with the aim to construct one PARAFAC model per case. Spectroscopic data sets of samples after the selective crystallization or precipitation, washing, and redissolution were recorded and arranged into a four-dimensional data set per case study. Different reference analytics and pure species spectra served as validation. Appropriate spectral preprocessing parameters were found for all case studies allowing even the application of this approach to the third case study in which quantitative concentration analytics are missing. Regardless of the modality or the number of species present in complex solutions, all models were able to estimate the specific concentration and find the optimal process condition regarding yield and product purity. It was shown that in complex solutions, species demonstrating similar phase behavior can be clustered as one component and described in the model. PARAFAC as a calibration-free approach coupled with UV/Vis spectroscopy provides a fast overview of species present in complex solution and of their concentration during selective crystallization or precipitation, washing, and redissolution.

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.

Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization

Artificial intelligence and specifically machine learning applications are nowadays used in a variety of scientific applications and cutting-edge technologies, where they have a transformative impact. Such an assembly of statistical and linear algebra methods making use of large data sets is becoming more and more integrated into chemistry and crystallization research workflows. This review aims to present, for the first time, a holistic overview of machine learning and cheminformatics applications as a novel, powerful means to accelerate the discovery of new crystal structures, predict key properties of organic crystalline materials, simulate, understand, and control the dynamics of complex crystallization process systems, as well as contribute to high throughput automation of chemical process development involving crystalline materials. We critically review the advances in these new, rapidly emerging research areas, raising awareness in issues such as the bridging of machine learning models with first-principles mechanistic models, data set size, structure, and quality, as well as the selection of appropriate descriptors. At the same time, we propose future research at the interface of applied mathematics, chemistry, and crystallography. Overall, this review aims to increase the adoption of such methods and tools by chemists and scientists across industry and academia.

An Ultrasound Tomography Method for Monitoring CO2 Capture Process Involving Stirring and CaCO3 Precipitation

In this work, an ultrasound computed tomography (USCT) system was employed to investigate the fast-kinetic reactive crystallization process of calcium carbonate. USCT measurements and reconstruction provided key insights into the bulk particle distribution inside the stirred tank reactor and could be used to estimate the settling rate and settling time of the particles. To establish the utility of the USCT system for dynamical crystallization processes, first, the experimental imaging tasks were carried out with the stirred solid beads, as well as the feeding and stirring of the CaCO₃ crystals. The feeding region, the mixing process, and the particles settling time could be detected from USCT data. Reactive crystallization experiments for CO₂ capture were then conducted. Moreover, there was further potential for quantitative characterization of the suspension density in this process. USCT-based reconstructions were investigated for several experimental scenarios and operating conditions. This study demonstrates a real-time monitoring and fault detection application of USCT for reactive crystallization processes. As a robust noninvasive and nonintrusive tool, real-time signal analysis and reconstruction can be beneficial in the development of monitoring and control systems with real-world applications for crystallization processes. A diverse range of experimental studies shown here demonstrate the versatility of the USCT system in process application, hoping to unlock the commercial and industrial utility of the USCT devices.

In Situ Water Quantification in Natural Deep Eutectic Solvents Using Portable Raman Spectroscopy

Raman spectroscopy is a label-free, non-destructive, non-invasive analytical tool that provides insight into the molecular composition of samples with minimum or no sample preparation. The increased availability of commercial portable Raman devices presents a potentially easy and convenient analytical solution for day-to-day analysis in laboratories and production lines. However, their performance for highly specific and sensitive analysis applications has not been extensively evaluated. This study performs a direct comparison of such a commercially available, portable Raman system, with a research grade Raman microscope system for the analysis of water content of Natural Deep Eutectic Solvents (NADES). NADES are renewable, biodegradable and easily tunable “green” solvents, outcompeting existing organic solvents for applications in extraction from biomass, biocatalysis, and nanoparticle synthesis. Water content in NADES is, however, a critical parameter, affecting their properties, optimal use and extraction efficiency. In the present study, portable Raman spectroscopy coupled with Partial Least Squares Regression (PLSR) is investigated for rapid determination of water content in NADES samples in situ, i.e., directly in glassware. Three NADES systems, namely Betaine Glycerol (BG), Choline Chloride Glycerol (CCG) and Glucose Glycerol (GG), containing a range of water concentrations between 0% (w/w) and 28.5% (w/w), were studied. The results are directly compared with previously published studies of the same systems, using a research grade Raman microscope. PLSR results demonstrate the reliability of the analysis, surrendering R² values above 0.99. Root Mean Square Errors Prediction (RMSEP) of 0.6805%, 0.9859% and 1.2907% w/w were found for respectively unknown CCG, BG and GG samples using the portable device compared to 0.4715%, 0.3437% and 0.7409% w/w previously obtained by analysis in quartz cuvettes with a Raman confocal microscope. Despite the relatively higher values of RMSEP observed, the comparison of the percentage of relative errors in the predicted concentration highlights that, overall, the portable device delivers accuracy below 5%. Ultimately, it has been demonstrated that portable Raman spectroscopy enables accurate quantification of water in NADES directly through glass vials without the requirement for sample withdrawal. Such compact instruments provide solvent and consumable free analysis for rapid analysis directly in laboratories and for non-expert users. Portable Raman is a promising approach for high throughput monitoring of water content in NADES that can support the development of new analytical protocols in the field of green chemistry in research and development laboratories but also in the industry as a routine quality control tool.

The development of analytical methods for the purity determination of fucoidan extracted from brown seaweed species

To determine the purity of extracted fucoidan from brown seaweeds, analytical methods were developed, including spectroscopy (i.e., Attenuate total reflectance (ATR) - Fourier-transform infrared (FT-IR) and Raman) combined with chemometrics; and the results were compared with those of high performance liquid chromatography (HPLC) and other two chemistry methods (i.e., fucoidan estimation based on fucose content and a cationic dye method based on sulphated polysaccharide estimation). Quantitative models (i.e., partial least squares regression (PLSR)) were developed and cross-validated using FT-IR spectroscopic methods (R2CV ~ 0.998, RMSECV ~1.7%). The models were also validated using other four commercial fucoidan products. On the other hand, the same commercial samples were used to validate the two chemistry methods and the HPLC method. Estimation results of these analytical methods were discussed based on the potential of these analytical methods for fucoidan purity determination. The results demonstrated FT-IR spectroscopy with chemometrics potentially could be used for non-destructive and real time determination.

Application of PAT-Based Feedback Control Approaches in Pharmaceutical Crystallization

Crystallization is one of the important unit operations for the separation and purification of solid products in the chemical, pharmaceutical, and pesticide industries, especially for realizing high-end, high-value solid products. The precise control of the solution crystallization process determines the polymorph, crystal shape, size, and size distribution of the crystal product, which is of great significance to improve product quality and production efficiency. In order to develop the crystallization process in a scientific method that is based on process parameters and data, process analysis technology (PAT) has become an important enabling platform. In this paper, we review the development of PAT in the field of crystallization in recent years. Based on the current research status of drug crystallization process control, the monitoring methods and control strategies of feedback control in the crystallization process were systematically summarized. The focus is on the application of model-free feedback control strategies based on the solution and solid information collected by various online monitoring equipment in product engineering, including improving particle size distribution, achieving polymorphic control, and improving purity. In this paper, the challenges of feedback control strategy in the crystallization process are also discussed, and the development trend of the feedback control strategy has been prospected.

Optimizing the morphology of calcium d-pantothenate by controlling phase transformation processes

A process for preparing calcium d-pantothenate tetramethanol monohydrate (d-PC·4MeOH·H₂O) with a block-like morphology was developed, the solvent-free D-PC with a block-like morphology was obtained by controlling the de-solvation of d-PC·4MeOH·H₂O.

Evaluation of focused beam reflectance measurement (FBRM) for monitoring and predicting the crystal size of carbamazepine in crystallization processes

Pharmaceutical crystallization affects the properties of APIs as it determines the purity and crystal size distribution, among other attributes. This work presents two CLD–CSD models, theoretical and empirical, for a model compound.

Olanzapine crystal symmetry originates in preformed centrosymmetric solute dimers

The symmetries of a crystal are notoriously uncorrelated to those of its constituent molecules. This symmetry breaking is typically thought to occur during crystallization. Here we demonstrate that one of the two symmetry elements of olanzapine crystals, an inversion centre, emerges in solute dimers extant in solution prior to crystallization. We combine time-resolved in situ scanning probe microscopy to monitor the crystal growth processes with all-atom molecular dynamics simulations. We show that crystals grow non-classically, predominantly by incorporation of centrosymmetric dimers. The growth rate of crystal layers exhibits a quadratic dependence on the solute concentration, characteristic of the second-order kinetics of the incorporation of dimers, which exist in equilibrium with a majority of monomers. We show that growth by dimers is preferred due to overwhelming accumulation of adsorbed dimers on the crystal surface, where it is complemented by dimerization and expedites dimer incorporation into growth sites.

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.

Vibrational Spectroscopy for Cocrystals Screening. A Comparative Study

A recurrent problem faced by the pharmaceutical industry when formulating drug products concerns poorly soluble drugs, which, despite having desirable pharmacological activity, present limited bioavailability. Cocrystallization is growing up as a possible approach to tackle this problem. Cocrystals are crystalline materials comprising at least two components, solid at room temperature, and held together by non-covalent bonds. The increasing interest in these compounds is steadily demanding faster, simpler, and more reliable methods for the task of screening new cocrystals. This work aims at comparing the performance of three vibrational spectroscopy techniques (mid infrared, near infrared, and Raman spectroscopy) for cocrystals screening. Presented results are based on hydrochlorothiazide, a poorly soluble drug belonging to class IV of the Biopharmaceutical Classification System. The implemented cocrystal screening procedure tested six coformers (all considered safe for human administration) added according to a drug:coformer ratio of 1:1 and 1:2 and seven solvents with different polarity. The screening method chosen was based on slurry cocrystallization performed by sonication (ultrasound assisted) in a 96-well plate. Results show that all evaluated vibrational spectroscopy techniques provided important information regarding cocrystal formation, including information on the groups involved in the cocrystallization and purity, and can be used for the screening task.

Raman spectroscopy in pharmaceutical research and industry

In the fast-developing fields of pharmaceutical research and industry, the implementation of Raman spectroscopy and related technologies has been very well received due to the combination of chemical selectivity and the option for non-invasive analysis of samples. This chapter explores established and potential applications of Raman spectroscopy, confocal Raman microscopy and related techniques from the early stages of drug development research up to the implementation of these techniques in process analytical technology (PAT) concepts for large-scale production in the pharmaceutical industry. Within this chapter, the implementation of Raman spectroscopy in the process of selection and optimisation of active pharmaceutical ingredients (APIs) and investigation of the interaction with excipients is described. Going beyond the scope of early drug development, the reader is introduced to the use of Raman techniques for the characterization of complex drug delivery systems, highlighting the technical requirements and describing the analysis of qualitative and quantitative composition as well as spatial component distribution within these pharmaceutical systems. Further, the reader is introduced to the application of Raman techniques for performance testing of drug delivery systems addressing drug release kinetics and interactions with biological systems ranging from single cells up to complex tissues. In the last part of this chapter, the advantages and recent developments of integrating Raman technologies into PAT processes for solid drug delivery systems and biologically derived pharmaceutics are discussed, demonstrating the impact of the technique on current quality control standards in industrial production and providing good prospects for future developments in the field of quality control at the terminal part of the supply chain and various other fields like individualized medicine.

On the way from the active drug molecule (API) in the research laboratory to the marketed medicine in the pharmacy, therapeutic efficacy of the active molecule and safety of the final medicine for the patient are of utmost importance. For each step, strict regulatory requirements apply which demand for suitable analytical techniques to acquire robust data to understand and control design, manufacturing and industrial large-scale production of medicines. In this context, Raman spectroscopy has come to the fore due to the combination of chemical selectivity and the option for non-invasive analysis of samples. Following the technical advancements in Raman equipment and analysis software, Raman spectroscopy and microscopy proofed to be valuable methods with versatile applications in pharmaceutical research and industry, starting from the analysis of single drug molecules as well as complex multi-component formulations up to automatized quality control during industrial production.

Nucleation in food colloids

Nucleation in food colloids has been studied in detail using ultrasound spectroscopy. Our data show that classical nucleation theory (CNT) remains a sound basis from which to understand nucleation in food colloids and analogous model systems using n-alkanes. Various interpretations and modifications of CNT are discussed with regard to their relevance to food colloids. Much of the evidence presented is based on the ultrasound velocity spectrometry measurements which has many advantages for the study of nucleating systems compared to light scattering and NMR due to its sensitivity at low solid contents and its ability to measure true solid contents in the nucleation and early crystal growth stages. Ultrasound attenuation spectroscopy also responds to critical fluctuations in the induction region. We show, however, that a periodic pressure fluctuation such as a quasi-continuous (as opposed to a pulse comprising only a few pressure cycles) ultrasound field can alter the nucleation process, even at very low acoustic intensity. Thus care must be taken when using ultrasound techniques that the measurements do not alter the studied processes. Quasi-continuous ultrasound fields may enhance or suppress nucleation and the criteria to determine such effects are derived. The conclusions of this paper are relevant to colloidal systems in foods, pharmaceuticals, agro-chemicals, cosmetics, and personal products.

Soft Sensors: Chemoinformatic Model for Efficient Control and Operation in Chemical Plants

Soft sensor is statistical model as an essential tool for controlling pharmaceutical, chemical and industrial plants. I introduce soft sensor, the roles, the applications, the problems and the research examples such as adaptive soft sensor, database monitoring and efficient process control. The use of soft sensor enables chemical industrial plants to be operated more effectively and stably.

Nondestructive detection of lead chrome green in tea by Raman spectroscopy

Raman spectroscopy was first adopted for rapid detecting a hazardous substance of lead chrome green in tea, which was illegally added to tea to disguise as high-quality. 160 samples of tea infusion with different concentrations of lead chrome green were prepared for Raman spectra acquirement in the range of 2804 cm(-1)-230 cm(-1) and the spectral intensities were calibrated with relative intensity standards. Then wavelet transformation (WT) was adopted to extract information in different time and frequency domains from Raman spectra, and the low-frequency approximation signal (ca4) was proved as the most important information for establishment of lead chrome green measurement model, and the corresponding partial least squares (PLS) regression model obtained good performance in prediction with Rp and RMSEP of 0.936 and 0.803, respectively. To further explore the important wavenumbers closely related to lead chrome green, successive projections algorithm (SPA) was proposed. Finally, 8 characteristic wavenumbers closely related to lead chrome green were obtained and a more convenient and fast model was also developed. These results proved the feasibility of Raman spectroscopy for nondestructive detection of lead chrome green in tea quality control.

Raman spectroscopy in pharmaceutical product design

Almost 100 years after the discovery of the Raman scattering phenomenon, related analytical techniques have emerged as important tools in biomedical sciences. Raman spectroscopy and microscopy are frontier, non-invasive analytical techniques amenable for diverse biomedical areas, ranging from molecular-based drug discovery, design of innovative drug delivery systems and quality control of finished products. This review presents concise accounts of various conventional and emerging Raman instrumentations including associated hyphenated tools of pharmaceutical interest. Moreover, relevant application cases of Raman spectroscopy in early and late phase pharmaceutical development, process analysis and micro-structural analysis of drug delivery systems are introduced. Finally, potential areas of future advancement and application of Raman spectroscopic techniques are discussed.

Vibrational spectroscopy and microspectroscopy analyzing qualitatively and quantitatively pharmaceutical hot melt extrudates

Since the last decade, more and more Active Pharmaceutical Ingredient (API) candidates have poor water solubility inducing low bioavailability. These molecules belong to the Biopharmaceutical Classification System (BCS) classes II and IV. Thanks to Hot-Melt Extrusion (HME), it is possible to incorporate these candidates in pharmaceutical solid forms. Indeed, HME increases the solubility and the bioavailability of these drugs by encompassing them in a polymeric carrier and by forming solid dispersions. Moreover, in 2004, the FDA's guidance initiative promoted the usefulness of Process Analytical Technology (PAT) tools when developing a manufacturing process. Indeed, the main objective when developing a new pharmaceutical process is the product quality throughout the production chain. The trend is to follow this parameter in real-time in order to react immediately when there is a bias. Vibrational spectroscopic techniques, NIR and Raman, are useful to analyze processes in-line. Moreover, off-line Raman microspectroscopy is more and more used when developing new pharmaceutical processes or when analyzing optimized ones by combining the advantages of Raman spectroscopy and imaging. It is an interesting tool for homogeneity and spatial distribution studies. This review treats about spectroscopic techniques analyzing a HME process, as well off-line as in-line, presenting their advantages and their complementarities.