Analysis and inorganic composition of microplastics in commercial Malaysian fish meals.

Presence of microplastics (MPs) in a broad range of wild and cultured marine organisms is well-documented, but transfer mechanisms by which cultured organisms are contaminated with MPs is poorly understood. MP loads in three Malaysian commercial brands of fish meal were investigated. Chemical composition of extracted MP-like particles was confirmed using micro-Raman spectroscopy. Inorganic composition of MPs and pigment particles were assessed through energy-dispersive X-ray spectroscopy (EDX). Out of 336 extracted particles, 64.3% were plastic polymers, 25% pigment particles, 4.2% non-plastic items, and 6.5% were unidentified. Fragments were the dominant form of MPs (78.2%) followed by filaments (13.4%) and films (8.4%). This study demonstrates that cultured organisms could be exposed to high levels of MPs via MP contaminated fish/shellfish used in fish meal production. Fish meal replacement with other sources of protein including meat meals and plant-based meals may mitigate MP exposure to cultured or farmed organisms.

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

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

An iterative approach for compound detection in an unknown pharmaceutical drug product: Application on Raman microscopy.

Raman chemical imaging provides both spectral and spatial information on a pharmaceutical drug product. Even if the main objective of chemical imaging is to obtain distribution maps of each formulation compound, identification of pure signals in a mixture dataset remains of huge interest. In this work, an iterative approach is proposed to identify the compounds in a pharmaceutical drug product, assuming that the chemical composition of the product is not known by the analyst and that a low dose compound can be present in the studied medicine. The proposed approach uses a spectral library, spectral distances and orthogonal projections to iteratively detect pure compounds of a tablet. Since the proposed method is not based on variance decomposition, it should be well adapted for a drug product which contains a low dose product, interpreted as a compound located in few pixels and with low spectral contributions. The method is tested on a tablet specifically manufactured for this study with one active pharmaceutical ingredient and five excipients. A spectral library, constituted of 24 pure pharmaceutical compounds, is used as a reference spectral database. Pure spectra of active and excipients, including a modification of the crystalline form and a low dose compound, are iteratively detected. Once the pure spectra are identified, multivariate curve resolution-alternating least squares process is performed on the data to provide distribution maps of each compound in the studied sample. Distributions of the two crystalline forms of active and the five excipients were in accordance with the theoretical formulation.

Setting local rank constraints by orthogonal projections for image resolution analysis: application to the determination of a low dose pharmaceutical compound.

Raman chemical imaging provides chemical and spatial information about pharmaceutical drug product. By using resolution methods on acquired spectra, the objective is to calculate pure spectra and distribution maps of image compounds. With multivariate curve resolution-alternating least squares, constraints are used to improve the performance of the resolution and to decrease the ambiguity linked to the final solution. Non negativity and spatial local rank constraints have been identified as the most powerful constraints to be used. In this work, an alternative method to set local rank constraints is proposed. The method is based on orthogonal projections pretreatment. For each drug product compound, raw Raman spectra are orthogonally projected to a basis including all the variability from the formulation compounds other than the product of interest. Presence or absence of the compound of interest is obtained by observing the correlations between the orthogonal projected spectra and a pure spectrum orthogonally projected to the same basis. By selecting an appropriate threshold, maps of presence/absence of compounds can be set up for all the product compounds. This method appears as a powerful approach to identify a low dose compound within a pharmaceutical drug product. The maps of presence/absence of compounds can be used as local rank constraints in resolution methods, such as multivariate curve resolution-alternating least squares process in order to improve the resolution of the system. The method proposed is particularly suited for pharmaceutical systems, where the identity of all compounds in the formulations is known and, therefore, the space of interferences can be well defined.

Distribution of a low dose compound within pharmaceutical tablet by using multivariate curve resolution on Raman hyperspectral images.

In this work, Raman hyperspectral images and multivariate curve resolution-alternating least squares (MCR-ALS) are used to study the distribution of actives and excipients within a pharmaceutical drug product. This article is mainly focused on the distribution of a low dose constituent. Different approaches are compared, using initially filtered or non-filtered data, or using a column-wise augmented dataset before starting the MCR-ALS iterative process including appended information on the low dose component. In the studied formulation, magnesium stearate is used as a lubricant to improve powder flowability. With a theoretical concentration of 0.5% (w/w) in the drug product, the spectral variance contained in the data is weak. By using a principal component analysis (PCA) filtered dataset as a first step of the MCR-ALS approach, the lubricant information is lost in the non-explained variance and its associated distribution in the tablet cannot be highlighted. A sufficient number of components to generate the PCA noise-filtered matrix has to be used in order to keep the lubricant variability within the data set analyzed or, otherwise, work with the raw non-filtered data. Different models are built using an increasing number of components to perform the PCA reduction. It is shown that the magnesium stearate information can be extracted from a PCA model using a minimum of 20 components. In the last part, a column-wise augmented matrix, including a reference spectrum of the lubricant, is used before starting MCR-ALS process. PCA reduction is performed on the augmented matrix, so the magnesium stearate contribution is included within the MCR-ALS calculations. By using an appropriate PCA reduction, with a sufficient number of components, or by using an augmented dataset including appended information on the low dose component, the distribution of the two actives, the two main excipients and the low dose lubricant are correctly recovered.

Application of chemometric algorithms to MALDI mass spectrometry imaging of pharmaceutical tablets.

During drug product development, the nature and distribution of the active substance have to be controlled to ensure the correct activity and the safety of the final medication. Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), due to its structural and spatial specificities, provides an excellent way to analyze these two critical parameters in the same acquisition. The aim of this work is to demonstrate that MALDI-MSI, coupled with four well known multivariate statistical analysis algorithms (PCA, ICA, MCR-ALS and NMF), is a powerful technique to extract spatial and spectral information about chemical compounds from known or unknown solid drug product formulations. To test this methodology, an in-house manufactured tablet and a commercialized Coversyl(®) tablet were studied. The statistical analysis was decomposed into three steps: preprocessing, estimation of the number of statistical components (manually or using singular value decomposition), and multivariate statistical analysis. The results obtained showed that while principal component analysis (PCA) was efficient in searching for sources of variation in the matrix, it was not the best technique to estimate an unmixing model of a tablet. Independent component analysis (ICA) was able to extract appropriate contributions of chemical information in homogeneous and heterogeneous datasets. Non-negative matrix factorization (NMF) and multivariate curve resolution-alternating least squares (MCR-ALS) were less accurate in obtaining the right contribution in a homogeneous sample but they were better at distinguishing the semi-quantitative information in a heterogeneous MALDI dataset.

Application of independent component analysis on Raman images of a pharmaceutical drug product: pure spectra determination and spatial distribution of constituents.

Independent component analysis (ICA) was used as a blind source separation method on a Raman image of a pharmaceutical tablet. Calculations were performed without a priori knowledge concerning the formulation. The aim was to extract the pure signals from the initial data set in order to examine the distribution of actives and major excipients within the tablet. As a method based on the decomposition of a matrix of mixtures of several components, the number of independent component to choose is a critical step of the analysis. The ICA_by_blocks method, based on the calculation of several models using an increasing number of independent components on initial matrix blocks, was used. The calculated ICA signals were compared with the pure spectra of the formulation compounds. High correlations between the two active principal ingredient spectra and their corresponding calculated signals were observed giving a good overview of the distributions of these compounds within the tablet. Information from the major excipients (lactose and avicel) was found in several independent components but the ICA approach provides high level of information concerning their distribution within the tablet. However, the results could vary considerably by changing the number of independent components or the preprocessing method. Indeed, it was shown that under-decomposition of the matrix could lead to better signal quality (compared to the pure spectra) but in that case the contributions due to minor components or effects were not correctly identified and extracted. On the contrary, over-decomposition of the original dataset could provide information about low concentration compounds at the expense of some loss of signal interpretability for the other compounds.

Comparative static curing versus dynamic curing on tablet coating structures.

Curing is generally required to stabilize film coating from aqueous polymer dispersion. This post-coating drying step is traditionally carried out in static conditions, requiring the transfer of solid dosage forms to an oven. But, curing operation performed directly inside the coating equipment stands for an attractive industrial application. Recently, the use of various advanced physico-chemical characterization techniques i.e., X-ray micro-computed tomography, vibrational spectroscopies (near infrared and Raman) and X-ray microdiffraction, allowed new insights into the film-coating structures of dynamically cured tablets. Dynamic curing end-point was efficiently determined after 4h. The aim of the present work was to elucidate the influence of curing conditions on film-coating structures. Results demonstrated that 24h of static curing and 4h of dynamic curing, both performed at 60°C and ambient relative humidity, led to similar coating layers in terms of drug release properties, porosity, water content, structural rearrangement of polymer chains and crystalline distribution. Furthermore, X-ray microdiffraction measurements pointed out different crystalline coating compositions depending on sample storage time. An aging mechanism might have occur during storage, resulting in the crystallization and the upward migration of cetyl alcohol, coupled to the downward migration of crystalline sodium lauryl sulfate within the coating layer. Interestingly, this new study clearly provided further knowledge into film-coating structures after a curing step and confirmed that curing operation could be performed in dynamic conditions.

Comprehensive study of dynamic curing effect on tablet coating structure.

The dissolution method is still widely used to determine curing end-points to ensure long-term stability of film coatings. Nevertheless, the process of curing has not yet been fully investigated. For the first time, joint techniques were used to elucidate the mechanisms of dynamic curing over time from ethylcellulose (Aquacoat)-based coated tablets. X-ray micro-computed tomography (XµCT), Near Infrared (NIR), and Raman spectroscopies as well as X-ray microdiffraction were employed as non-destructive techniques to perform direct measurements on tablets. All techniques indicated that after a dynamic curing period of 4h, reproducible drug release can be achieved and no changes in the microstructure of the coating were any longer detected. XµCT analysis highlighted the reduced internal porosity, while both NIR and Raman measurements showed that spectral information remained unaltered after further curing. X-ray microdiffraction revealed densification of the coating layer with a decrease in the overall coating thickness of about 10 µm as a result of curing. In addition, coating heterogeneity attributed to cetyl alcohol was observed from microscopic images and Raman analysis. This observation was confirmed by X-ray microdiffraction that showed that crystalline cetyl alcohol melted and spread over the coating surface with curing. Prior to curing, X-ray microdiffraction also revealed the existence of two coating zones differing in crystalline cetyl alcohol and sodium lauryl sulfate concentrations which could be explained by migration of these constituents within the coating layer. Therefore, the use of non-destructive techniques allowed new insights into tablet coating structures and provided precise determination of the curing end-point compared to traditional dissolution testing. This thorough study may open up new possibilities for process and formulation control.

Real-time predictions of drug release and end point detection of a coating operation by in-line near infrared measurements.

The aim of this work was to carry out real-time near infrared (NIR) predictions of drug release from sustained release coated tablets and to determine end point of coating operation. In-line measurements were ensured by implementation of a NIR probe inside a pan coater. Tablets were coated using a functional aqueous dispersion of ethylcellulose blended with PVA-PEG graft copolymer to obtain a controlled drug release dosage form over 16h. Samples were collected at regular intervals and subjected to a standardized curing step. Percentages of released drug at 4h, 8h and 12h were selected to describe the controlled drug release of cured tablets. These dissolution criteria were used as reference values to calibrate NIR spectral information and to develop three partial least squares regressions. Low predictive errors of 1.7%, 1.9% and 1.5%, respectively, were obtained. The coating operation was stopped while desired dissolution criteria were achieved, corresponding to a coating level around 10%. The present study demonstrated that real-time NIR measurements could be performed on non-finished drug products to predict dissolution properties of cured coated tablets. This novel and innovative approach fulfils the expectations of ICH Q8 guideline on pharmaceutical development, in terms of process understanding and process analytical technology (PAT) control strategy. This approach should be however adapted to curing operation to allow a real-time release testing.

Development of a Process Analytical Technology (PAT) for in-line monitoring of film thickness and mass of coating materials during a pan coating operation.

The aim of this study was to perform in-line Near Infrared (NIR) measurements inside a pan coater to monitor a coating operation in real-time, by predicting the increases in mass of coating materials and coating thickness. A polymer combination of ethylcellulose/poly(vinyl-alcohol)-poly(ethylene-glycol) graft copolymer was used as functional aqueous coating. Coated tablets were sampled at regular intervals during the coating operation, then subjected to either simple and fast weighing (n=50) or accurate and non-destructive Terahertz Pulsed Imaging (TPI) measurements (n=3). Off-line NIR spectra analysis revealed that the coating operation could efficiently be controlled by focusing on two distinct NIR regions, related to absorption bands of ethylcellulose. Principal component analysis of in-line NIR spectra gave a clear classification of the collected coated tablets. Real-time quantitative monitoring of the coating operation was successfully performed from partial least square calibration models built using either TPI or weighing as reference method. Coating thicknesses as well as mass of coating materials used as primary values provided accurate NIR predictions. A comparison study demonstrated that both reference methods led to reliable and accurate real-time monitoring of the coating operation. This work demonstrated that in-line NIR measurements associated with multivariate analyses can be implemented to monitor in real-time a pan coating operation in order to fulfil the expectations of ICH Q8 guideline on pharmaceutical development, especially in terms of PAT control strategy and reduced end-product testing.

Tablet potency of Tianeptine in coated tablets by near infrared spectroscopy: model optimisation, calibration transfer and confidence intervals.

A near infrared (NIR) method was developed for determination of tablet potency of active pharmaceutical ingredient (API) in a complex coated tablet matrix. The calibration set contained samples from laboratory and production scale batches. The reference values were obtained by high performance liquid chromatography (HPLC) and partial least squares (PLS) regression was used to establish a model. The model was challenged by calculating tablet potency of two external test sets. Root mean square errors of prediction were respectively equal to 2.0% and 2.7%. To use this model with a second spectrometer from the production field, a calibration transfer method called piecewise direct standardisation (PDS) was used. After the transfer, the root mean square error of prediction of the first test set was 2.4% compared to 4.0% without transferring the spectra. A statistical technique using bootstrap of PLS residuals was used to estimate confidence intervals of tablet potency calculations. This method requires an optimised PLS model, selection of the bootstrap number and determination of the risk. In the case of a chemical analysis, the tablet potency value will be included within the confidence interval calculated by the bootstrap method. An easy to use graphical interface was developed to easily determine if the predictions, surrounded by minimum and maximum values, are within the specifications defined by the regulatory organisation.