Visualization and prediction of porosity in roller compacted ribbons with near-infrared chemical imaging (NIR-CI)

Laser Triangulation Based In-Line Elastic Recovery Measurement for the Determination of Ribbon Solid Fraction in Roll Compaction

Process Analytical Technology (PAT) plays a crucial role in the design of today's manufacturing lines as continuous manufacturing becomes more important. Until now PAT tools to measure the ribbon solid fraction (SFribbon) in-line are not commonly used in roll compaction. The aim of this study was therefore to establish a new approach as PAT for in-line ribbon solid fraction determination. Different placebo formulations with different binders and one formulation containing active pharmaceutical ingredient were investigated using in-line laser triangulation measurement to detect the ribbon thickness after compaction. With this the ribbon elastic recovery was determined in-line (ERin-line) while the ribbons are attached to the roll surface. It was found that the ratio (ERratio) between the total elastic recovery and ERin-line is formulation specific and not influenced by any process parameters. This enables ERratio as prediction tool for SFribbon, if the solid fraction at gap (SFgap) width is known. SFgap was determined with ribbon mass flow measurement or based on the Midoux model, a simplified Johanson model, gaining two prediction models for SFribbon. Both models showed good agreement of the predicted SFribbon and the measured one.

Development of an Image-based Method for Tablet Microstructure Description and Its Correlation with API Release Rate

The performance of a pharmaceutical formulation, such as the drug (API) release rate, is significantly influenced by the properties of the materials used, the composition of the final product and the tablet compression process parameters. However, in some cases, the knowledge of these input parameters does not necessarily provide a reliable description or prediction of tablet performance. Therefore, the knowledge of tablet microstructure is desirable to understand such formulations. Commonly used analytical techniques, such as X-ray tomography and intrusion mercury porosimetry, are not widely used in pharmaceutical companies due to their price and/or toxicity, and therefore, efforts are made to develop a tool for fast and easy microstructure description. In this work, we have developed an image-based method for microstructure description and applied it to a model system consisting of ibuprofen and CaHPO4∙2H2O (API and excipient with different deformability). The obtained parameter, the quadratic mean of the equivalent diameter of the non-deformable, brittle excipient CaHPO4∙2H2O, was correlated with tablet composition, compression pressure and API release rate. The obtained results demonstrate the possibility of describing the tablet dissolution performance in the presented model system based on the microstructural parameter, providing a possible model system for compressed solid dosage forms in which a plastic component is present and specific API release is required.

Laser triangulation as a fast and reliable method for determining ribbon solid fraction; focus on accuracy, precision, and measurement time

Roller compaction and dry granulation represent well-established unit operations in the pharmaceutical industry. The ribbon solid fraction is classified as a critical quality attribute, that directly impacts final product quality and performance. The development and evaluation of novel methods measuring ribbon solid fraction represent a subject of current research, since novel analyses strategies need to be established for at-, on-, or in-line process monitoring to overcome limitations of end product testing and to set the course for continuous manufacturing. In this study, a novel analytical device, using the principle of laser triangulation, was investigated to asses its potential being used as at-line process analytical technology tool during a roller compaction process. To this end, the laser triangulation device was compared with X-ray micro-computed tomography and powder based volume displacement measurement techniques using different statistical evaluation methods. Special focus was given to accuracy, precision, and total measurement time. The laser triangulation device was confirmed as highly accurate and precise, enabling the shortest total measurement time compared to the other methods. The findings of this study support the idea of implementing the laser triangulation device as a novel at-line process analytical technology tool into a roller compaction process.

Process Analytical Technology Tools for Monitoring Pharmaceutical Unit Operations: A Control Strategy for Continuous Process Verification

Various frameworks and methods, such as quality by design (QbD), real time release test (RTRT), and continuous process verification (CPV), have been introduced to improve drug product quality in the pharmaceutical industry. The methods recognize that an appropriate combination of process controls and predefined material attributes and intermediate quality attributes (IQAs) during processing may provide greater assurance of product quality than end-product testing. The efficient analysis method to monitor the relationship between process and quality should be used. Process analytical technology (PAT) was introduced to analyze IQAs during the process of establishing regulatory specifications and facilitating continuous manufacturing improvement. Although PAT was introduced in the pharmaceutical industry in the early 21st century, new PAT tools have been introduced during the last 20 years. In this review, we present the recent pharmaceutical PAT tools and their application in pharmaceutical unit operations. Based on unit operations, the significant IQAs monitored by PAT are presented to establish a control strategy for CPV and real time release testing (RTRT). In addition, the equipment type used in unit operation, PAT tools, multivariate statistical tools, and mathematical preprocessing are introduced, along with relevant literature. This review suggests that various PAT tools are rapidly advancing, and various IQAs are efficiently and precisely monitored in the pharmaceutical industry. Therefore, PAT could be a fundamental tool for the present QbD and CPV to improve drug product quality.

An Investigation into Mechanical Properties and Printability of Potential Substrates for Inkjet Printing of Orodispersible Films

Inkjet printing is novel approach in drug manufacturing that enables dispensing precise volumes of ink onto substrates. Optimal substrate properties including suitable mechanical characteristic are recognized as crucial to achieve desired dosage form performance upon administration. Identification of relevant quality attributes and their quantification is subject of intensive scientific research. The aim of this work was to explore applicability of different materials as printing substrates and explore contribution of the investigated substrate properties to its printability. Substrates were characterized with regards to uniformity, porosity, disintegration time, mechanical properties and drug dissolution. Experimentally obtained values were mathematically transformed and the obtained results were presented as relevant radar charts. It was shown that structurally different substrates may be employed for orodispersible films inkjet printing. Main disadvantage of single-polymer films was low drug load, and their printability was dependent on film flexibility and mechanical strength. Structured orodispersible film templates exhibited favorable mechanical properties and drug load capacity. Wafer edible sheets were characterized with high mechanical resistance and brittleness which somewhat diminished printability, but did not hinder high drug load. Obtained results provide insight into application of different materials as printing substrates and contribute to understanding of substrate properties which can affect printability.

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.

The relevance of granule fragmentation on reduced tabletability of granules from ductile or brittle materials produced by roll compaction/dry granulation

Roll compaction/dry granulation often results in loss of tabletability. The two main hypotheses for this are granule hardening and granule size enlargement. The aim of this study was to investigate the effect of granule size, roll compaction force, and granule fragmentation upon tableting and its effect on tabletability of granules constituting a ductile or brittle material. Plastically deforming microcrystalline cellulose (MCC) and fragmenting lactose monohydrate (lactose) were roll compacted at five roll compaction forces ranging from 2 to 16 kN/cm. Granule size fractions of 250-355 and 500-710 µm were blended with 10% magnesium stearate (MgSt), compressed into tablets and ground to obtain compressed granules. The predominant deformation behaviour of the particles constituting the granules directly impacted granule deformation upon tableting, as lactose granules fractured extensively upon tableting, whereas MCC granules predominantly deformed by plastic deformation. Increased roll compaction force resulted in more granule hardening of both materials and thereby granules less susceptible to fragmentation upon tableting. Granule hardening accounted for the largest loss of tabletability of MCC granules upon roll compaction. Roll compaction force and granule size had no or negligible effect on tabletability of lactose tablets without MgSt, whereas increased roll compaction force and larger granules decreased tensile strength of tablets containing lactose granules blended with MgSt. This was explained by inter-particle and inter-granular bonds contributing equally to the tensile strength of lactose tablets without MgSt. However, after addition of MgSt, the decreased fragmentation tendency of larger granules compacted at higher roll compaction forces resulted in greater MgSt coverage of the granules upon tableting, thereby decreasing tabletability.

Process analytical technology tools for process control of roller compaction in solid pharmaceuticals manufacturing

This article presents an overview of using process analytical technology in monitoring the roller compaction process. In the past two decades, near-infrared spectroscopy, near-infrared spectroscopy coupled with chemical imaging, microwave resonance technology, thermal effusivity and various particle imaging techniques have been used for developing at-, off-, on- and in-line models for predicting critical quality attributes of ribbons and subsequent granules and tablets. The common goal of all these methods is improved process understanding and process control, and thus improved production of high-quality products. This article reviews the work of several researchers in this field, comparing and critically evaluating their achievements.

Investigation of the effects of particle size on fragmentation during tableting

Particle size is a critical parameter during tablet production as it can impact tabletability, flowability, and dissolution rate of the final product. The purpose of this study was to investigate the effect of initial particle size on fragmentation of pharmaceutical materials during tableting. Initial particle size fractions ranging from 0-125 to 355-500 µm of dibasic calcium phosphate (DCP), lactose monohydrate, and agglomerated and non-agglomerated microcrystalline cellulose (MCC) were blended with magnesium stearate and compressed into tablets. Larger initial particle sizes were found to fragment more extensively than smaller initial particle sizes for all materials based on the particle size distributions determined by laser diffraction. DCP was found to fragment most extensively followed by lactose and both MCCs. The fragmentation degrees of DCP, lactose, agglomerated and non-agglomerated MCC reached 95, 81, 32, and 29%, respectively. These findings were further supported by an increase in specific surface area with increasing compression pressure of compressed particles. The NIR spectral baseline offset from tablets was found to increase with increasing compression pressure up to 50 MPa for all materials, which was the same compression pressure range where fragmentation was observed. The NIR spectral slope from tablets as a function of compression pressure furthermore showed a similar trend as the tabletability profiles. NIR spectroscopy can thereby potentially be used as a surrogate control strategy for assessing compression related particle size changes and possibly tablet density and deformation behavior during tablet production.

Quantification of Inkjet-Printed Pharmaceuticals on Porous Substrates Using Raman Spectroscopy and Near-Infrared Spectroscopy

The use of inkjet printing for pharmaceutical manufacturing is gaining interest for production of personalized dosage forms tailored to specific patients. As part of the manufacturing, it is imperative to ensure that the correct dose is printed. The aim of this study was to use inkjet printing for manufacturing of personalized dosage forms combined with the use of near-infrared (NIR) and Raman spectroscopy as complementary analytical techniques for active pharmaceutical ingredient (API) quantification of the inkjet-printed dosage forms. Three APIs, propranolol (0.5-4.1 mg), montelukast (2.1-12.1 mg), and haloperidol (0.6-4.1 mg) were inkjet printed in 1 cm² areas on a porous substrate. The printed doses were non-destructively analyzed by transmission NIR and Raman spectroscopy (both transmission and backscatter). X-ray computed microtomography (μ-CT) analysis was undertaken for porosity measurements of the substrate. The API content was confirmed using high-performance liquid chromatography (HPLC), and the content in the dosage forms was modeled from the NIR and Raman spectra using partial least squares regression (PLS). HPLC analysis revealed a linear correlation of the number of layers printed to the API content. The resulting PLS models for both NIR and Raman had R² values between 0.95 and 0.99. The best predictive model was obtained using NIR, followed by Raman spectroscopy. μ-CT revealed the substrate to be highly porous and optimal for inkjet printing. In conclusion, NIR and Raman spectroscopic techniques could be used complementary as fast API quantification tools for inkjet-printed medicines.

Characterisation of pore structures of pharmaceutical tablets: A review

Traditionally, the development of a new solid dosage form is formulation-driven and less focus is put on the design of a specific microstructure for the drug delivery system. However, the compaction process particularly impacts the microstructure, or more precisely, the pore architecture in a pharmaceutical tablet. Besides the formulation, the pore structure is a major contributor to the overall performance of oral solid dosage forms as it directly affects the liquid uptake rate, which is the very first step of the dissolution process. In future, additive manufacturing is a potential game changer to design the inner structures and realise a tailor-made pore structure. In pharmaceutical development the pore structure is most commonly only described by the total porosity of the tablet matrix. Yet it is of great importance to consider other parameters to fully resolve the interplay between microstructure and dosage form performance. Specifically, tortuosity, connectivity, as well as pore shape, size and orientation all impact the flow paths and play an important role in describing the fluid flow in a pharmaceutical tablet. This review presents the key properties of the pore structures in solid dosage forms and it discusses how to measure these properties. In particular, the principles, advantages and limitations of helium pycnometry, mercury porosimetry, terahertz time-domain spectroscopy, nuclear magnetic resonance and X-ray computed microtomography are discussed.

Determination of Spatially Resolved Tablet Density and Hardness Using Near-Infrared Chemical Imaging (NIR-CI)

Near-infrared chemical imaging (NIR-CI) combines spectroscopy with digital imaging, enabling spatially resolved analysis and characterization of pharmaceutical samples. Hardness and relative density are critical quality attributes (CQA) that affect tablet performance. Intra-sample density or hardness variability can reveal deficiencies in formulation design or the tableting process. This study was designed to develop NIR-CI methods to predict spatially resolved tablet density and hardness. The method was implemented using a two-step procedure. First, NIR-CI was used to develop a relative density/solid fraction (SF) prediction method for pure microcrystalline cellulose (MCC) compacts only. A partial least squares (PLS) model for predicting SF was generated by regressing the spectra of certain representative pixels selected from each image against the compact SF. Pixel selection was accomplished with a threshold based on the Euclidean distance from the median tablet spectrum. Second, micro-indentation was performed on the calibration compacts to obtain hardness values. A univariate model was developed by relating the empirical hardness values to the NIR-CI predicted SF at the micro-indented pixel locations: this model generated spatially resolved hardness predictions for the entire tablet surface.

NIR hyperspectral imaging to evaluate degradation in captopril commercial tablets

Pharmaceutical quality control is important for improving the effectiveness, purity and safety of drugs, as well as for the prevention or control of drug degradation. In the present work, near infrared hyperspectral images (HSI-NIR) of tablets with different expiration dates were employed to evaluate the degradation of captopril into captopril disulfide in different layers, on the top and on the bottom surfaces of the tablets. Multivariate curve resolution (MCR) models were used to extract the concentration distribution maps from the hyperspectral images. Afterward, multivariate image techniques were applied to the concentration distribution maps (CDMs), to extract features and build models relating the main characteristics of the images to their corresponding manufacturing dates. Resolution methods followed by extracting features were able to estimate the tablet manufacture date with a prediction error of 120days. The model developed could be useful to evaluate whether a sample shows a degradation pattern consistent with the date of manufacturing or to detect abnormal behaviors in the natural degradation process of the sample. The information provided by the HIS-NIR is important for the development of the process (QbD), looking inside the formulation, revealing the behavior of the active pharmaceutical ingredient (API) during the product's shelf life.

Hyperspectral image analysis. A tutorial

This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case.