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Tablet sticking is a continuous accumulation of pharmaceutical powder onto tooling surfaces during compression. Its occurrence greatly impacts tablet productivity, quality attributes, and tooling age. In a previous study1, the authors proposed a multivariate data analysis approach to gain insights into tablet sticking directly on the industrial stage (Dembélé et al. 2022). The objective was to determine the combination of factors that could help distinguish between batches affected and unaffected by sticking. The present study aims to generalize this approach by extending it to quantitative predictions of punch sticking intensity. A total of 345 variables was gathered on 28 industrial batches of an ibuprofen and methocarbamol-based formulation. Using PLS regression models, it was shown that the association of granulation duration and compression force allows to significantly explain ∼60% of sticking variations of studied formulation. In addition, unlike the classification models developed in the earlier work, the validation residues in the present study were found to be normally distributed (Shapiro-Wilks p-value = 0.96) and independent from the target variable (R

Sticking is one of the most common and damaging issues that occur during tablet manufacturing. Sticking is the adhesion of powder onto tooling surfaces during compression. Because of the numerous factors involved in its occurrence, understanding tablet sticking requires the simultaneous investigation of these factors to clarify their possible interactions. However, conducting such a study experimentally can present a significant financial and technical burden. In this study, we aimed to leverage the large amount of data that is usually generated during industrial manufacturing to gain insights into sticking. This was achieved by collecting and analyzing a total of 71 historical batches that used an ibuprofen-based formulation. We associate each batch with a hundred parameters, including a qualitative descriptor of sticking, and employ a predefined methodology based primarily on multivariate data analysis. Our results highlight the role of lubrication, water content, and the low melting point of ibuprofen in its sticking tendency. Based on these findings, we propose and discuss an industrial manufacturing data analysis approach to sticking and its associated systematic methodology, consisting of collection, exploration, and data modeling.

Among the factors that influence adherence to medication within the pediatric population, taste/irritation has been identified as a critical barrier to patient compliance. With the goal of improving compliance, microspheres (matrix systems within which the drug is dispersed) can be coated with a reverse enteric polymer that will prevent the release of the drug in the oral cavity while maintaining an immediate release once the drug product reaches the stomach, thereby achieving a taste neutral profile. In this work, the in-line performance of three process analytical technology (PAT) tools is evaluated in order to monitor the microsphere coating process. These tools are Raman spectroscopy, near-infrared spectroscopy and focused beam reflectance measurements, together with process data and raw material attributes. The ability of these different sources of information to predict the coating's barrier performance is evaluated by using a combined-data-approach: multiblock partial least squares (MBPLS). Results show that Raman spectroscopy has a superior predictive performance and that it has the potential to monitor the coating process of the microspheres as well as to detect process discrepancies (such as spray rate changes), demonstrating its usefulness for the monitoring of fluid bed coating processes. It was also demonstrated that Raman can be used to clearly differentiate batches with significantly difference in-vitro dissolution performance. This monitoring is considered critical to ensure consistent coating performance for this thin film barrier membrane that is essential to patient compliance.

Over the last decade, the conical mill has emerged as a potential piece of equipment to use for continuous dry coating pharmaceutical powders. In this work, silicon dioxide was used as a guest particle on two excipients, fast flow lactose (FFL) and grade PH200 microcrystalline cellulose (MCC), for dry coating by a conical mill with a modified screen that permitted batch and continuous mode operation. Samples were pre-processed in a V-blender. SEM images, particle size distribution, and EDS mapping were used to characterise the treated powders. Pre-processed samples showed some discrete coating of the host particle. After batch processing, the samples were covered with a complete coating. When processed at high impeller speed, coating of FFL was a mix of A200P and FFL fines generated by attrition. Continuous mode processed samples, which had a lower processing time, were coated discretely and showed a better coating than the pre-processed samples. Increasing guest/host mass ratio with FFL host particle had a positive impact on the quality of the coating. These results help to build the case that the processing time of the conical mill is a key parameter to the success of the conical mill as dry coating equipment in the pharmaceutical industry.

A dry coating technology has been evaluated as a dry agglomeration technique for a typical pharmaceutical formulation. Its efficiency was compared with that of the more commonly used roller compaction dry granulation. A commercially available system was selected as a representative technology. The selection was based on batch size, processing time, unit size, vendor support, preventive maintenance requirements, development stage, and maturity for pharmaceutical industry requirements. The comparison targets the behavior of the resulting materials in terms of flowability, compressibility, mixing efficiency, and prevention of segregation. Particle size distribution, bulk density, scanning electron microscopy, FT4 powder rheometer, and hardness were used for the characterization of the powders. A design of experiment was used to evaluate the impact of the dry coating equipment operating parameters (rotor speed and processing time) as well as the impact of formulation (grade of microcrystalline cellulose and ratio between dibasic calcium phosphate and lactose). The tested dry coating technology shows (1) an improved compressibility, (2) that the powders are homogenous, and (3) that they do not have a tendency to segregate in downstream process steps and during handling and storage. The impact of the rotor speed is proven statistically not significant, but it seems that a lower rotor speed might lead to less attrition and better flow properties. Processing time does not seem to have an impact for the range of processing times evaluated. Compared to roller compaction, the main advantages of the tested technology are the shape and surface enhancement and the absence of work hardening. This work has shown that the blends produced by the targeted dry coating equipment has equal or better results than the powders processed by roller compaction for all the critical quality attributes that were evaluated.

Continuous manufacturing can greatly benefit the pharmaceutical industry for improving production yields, size flexibility, and transferability among sites. This study investigated the dynamics of pharmaceutical granules dried in a continuous horizontal fluidized bed dryer (FBD) equipped with a screw conveyor to evaluate the feasibility of the process. Pharmaceutical granules are often irregularly shaped and feature a large particle size distribution, thus complicating the operation of traditional continuous FBDs with smooth fluidization regimes. The presence of screw conveyor enhanced plug flow, decreased agglomeration, and improved fluidization stability and homogeneity. The residence time distribution (RTD) of solid flow was evaluated by the pulse-tracer injection method. The dispersion model and the tanks-in-series model were both suitable for describing the particle flow through the dryer. The corresponding Peclet numbers vary between 9.8 and 13.3 while the tank number better fitting the model are between 5.4 and 7.2. The influences of different parameters were studied. The internal screw conveyor rotation was the most critical parameter affecting the solid RTD, followed by air velocity. The air temperature also had a moderate impact. The solid throughput rate had a negligible effect on the solid RTD, but it did have a direct impact on the overall drying rate.

The availability of reliable online moisture content measurements exploiting near-infrared (NIR) spectroscopy and chemometric tools allows the application of online control strategies to a wide range of drying processes in the pharmaceutical industry. In this paper, drying of particles with a pilot-scale batch fluidized bed dryer (FBD) is studied using a in-line NIR probe. A consolidated phenomenological state-space model of an FBD based on mass and energy balances is calibrated applying a nonlinear least-square identification to experimental data (grey-box modeling). Then, relying on the calibrated model, a nonlinear model predictive controller and a moving horizon state estimator are designed. The objective is to reach a specific particle moisture content setpoint at the end of the drying batch while decreasing cycle time and limiting particle temperature. A penalty term on the energy consumption can also be added to the usual tracking control cost function. Compared to a typical FBD operation in industry (mostly open-loop), it is shown that the drying time and the energy consumption can be efficiently managed on the pilot-scale process while limiting various operation problems like under drying, over drying, or particles overheating.

Good Manufacturing Practice Regulations, under the Food and Drug Administration (FDA), stipulate that all pharmaceutical products must be free of any contaminants, including, namely, any foreign solid objects. Lyophilization is a common manufacturing method that consists of several steps where foreign materials may enter the product. The presence of unintended particles in freeze drying, which will herein be referred to under the term 'Lyophilization', is of great concern to the authorities responsible for drug safety and effectiveness. In the pharmaceutical industry, presently, the inspection of lyophilized products for foreign matter particulates relies on visual inspection where only the outer surface of the lyophilized cake is visible. This review is motivated by the need for new control strategies for foreign matter (FM) detection in lyophilized products; more specifically, it assesses the reliability of non-destructive technologies for FM detection in dried samples. Emerging technologies applied in other industries, such as various types of spectroscopies and imaging (e.g. chemical, X-ray, ultrasound, thermal and terahertz), are evaluated based on compatibility with the intended application, with identification of the possible technical challenges.

International audience; This study applied the concept of Quality by Design (QbD) to tablet dissolution. Its goal was to propose a quality control strategy to model dissolution testing of solid oral dose products according to International Conference on Harmonization guidelines. The methodology involved the following three steps: (1) a risk analysis to identify the material- and process-related parameters impacting the critical quality attributes of dissolution testing, (2) an experimental design to evaluate the influence of design factors (attributes and parameters selected by risk analysis) on dissolution testing, and (3) an investigation of the relationship between design factors and dissolution profiles. Results show that (a) in the case studied, the two parameters impacting dissolution kinetics are active pharmaceutical ingredient particle size distributions and tablet hardness and (b) these two parameters could be monitored with PAT tools to predict dissolution profiles. Moreover, based on the results obtained, modeling dissolution is possible. The practicality and effectiveness of the QbD approach were demonstrated through this industrial case study. Implementing such an approach systematically in industrial pharmaceutical production would reduce the need for tablet dissolution testing.

Near infrared chemical imaging (NIRCI) is a common analytical non-destructive technique for the analysis of pharmaceutical tablets. This powerful process analytical technology provides opportunity to chemically understand the sample, and also to determine spatial distribution and size of ingredients in a tablet. NIRCI has been used to link disintegrant, excipients and active pharmaceutical ingredient (API) to tablet dissolution, as disintegrants play an important role in tablet disintegration, resulting in API dissolution. This article describes a specific methodology to predict API dissolution based on disintegrant chemical information obtained with NIRCI. First, several tablet batches with different disintegrant characteristics were produced. Then, NIRCI was successfully used to provide chemical images of pharmaceutical tablets. A PLS regression model successfully predicted dissolution profiles. These results show that NIRCI is a robust and versatile technique for measuring disintegrant properties in tablet formulations and predicting their effects on dissolution profiles. Thus, NIRCI could routinely complement and eventually replace dissolution testing by monitoring a critical material attribute: disintegrant content.

This work proposes a novel chemometric methodology for in-line near infrared spectroscopy (NIRS) monitoring of pharmaceutical powder moisture in a fluidised-bed dryer. The collected spectra are analysed by multivariate chemometrics involving the preparation of numerous laboratory samples. A different methodology, using only plant samples, was tested in real-time. A specially designed probe tip, allowing for robust in-situ spectral acquisition, was designed. The results prove that NIRS can be as efficient as traditional quality analyses, e.g. loss-on-drying, in measuring powder moisture content in a fluidised bed dryer with a calibration model based only on plant samples. © 2011 Canadian Society for Chemical Engineering

The purpose of this study was to develop a robust and versatile near infrared (NIR) analysis protocol for the quality control of intact tablets containing two active pharmaceutical ingredients, acetylsalicylic acid (ASA) and caffeine, as well as three excipients. Reference samples were prepared and a calibration model built for each apparatus. All components of the formulation were characterized by transmission measurements with NIR spectroscopy (NIRS). The study was performed with three different Fourier transform NIR apparatuses and chemometric models. Calibration was carried out by the partial least squares regression method and a pre-processing technique to optimize the efficiency of the models. High performance liquid chromatography was the reference method for obtaining active pharmaceutical ingredient concentration values used in model building. It also served as a reference for chemometric model validation. Eighteen samples were analyzed by chemometric modeling to predict each component's concentration. Four out of five ingredients were quantified precisely with the three chemometric models developed. ASA quantification uncertainty ranges were between 1.0 and 1.1%, and the average error was less than 5% for caffeine. More than 99.9% of tablet content were analyzed and quantified. The results show that a versatile in-line or at-line NIRS method, with three different chemometric models built from three different acquisition apparatuses, can be developed without sample preparation for pharmaceutical tablet quality control of existing products.

The agglomeration tendency of dry pharmaceutical mixtures containing various concentrations of Xylitab®100 (Xylitol), calcium carbonate precipitated (CCP) and magnesium stearate (MgSt) was evaluated statistically as a function of mixing time. A Ro-Tap tester was employed to mix the three pharmaceutical components, and the agglomerates formed were measured with respect to their weight and size. An experimental design was devised and applied to structure and then statistically analyze the results. Xylitab was found not to be influential in the formation of agglomerates, but aided in deagglomeration when mixed with other components. CCP and MgSt formed agglomerates over time and showed positive interactions favouring agglomeration. The agglomerates started to fracture when they reached a critical size, at which stage the particles’ attraction forces (cohesion forces) were weaker than both gravity and inertia. It has been shown and quantitatively demonstrated that the mixing time and ingredient concentrations of a three-component pharmaceutical mixture can affect agglomeration tendency.

Segregation phenomena are of importance in nearly all processes involving dry granular and powder mixtures. The extent of segregation directly influences the eventual rejection of a considerable percentage of the final product in the majority of pharmaceutical processes; among these are those mixtures destined for powder compression processing for the production of tablets. Although the parameters influencing segregation are relatively well-known qualitatively, there are, so far, no widely accepted quantitative prediction tools that permit process improvement and optimization of production as a function of the mixture's composition and the particulars of individual processes (e.g., geometry of the vessels). Thus, within present practice, only general design considerations and the technical expertise of engineers and operators are relied upon to optimize these processes on a case-by-case basis. It is in these circumstances that a study of the tendency towards segregation in free flowing granular materials was conducted, using a simple tool previously developed for the study of the behavior of continuous chemical reactors with classical fluid flows. The measurement of average residence times and their variance is used to calculate the deviation of chemical reactors from the ideal behavior of a perfectly mixed vessel or a plug flow pattern. In this work, these measurements are adapted to evaluate the tendency of a granular mixture to segregate. The method consists of introducing a pulse perturbation (of another material) to the established regular flow of a single granular material or a granular mixture and to then calculate the response of the system in terms of the concentration of the pulsed material at the process outlet. The average granular particle residence time and its standard deviation are then related to the segregation tendency.

Process analytical technologies (PAT) enable process insight, process control and real-time testing. Light-induced fluorescence (LIF) spectroscopy is especially well suited for low-concentration ingredients as, in many cases, it is the most sensitive probe of the in-line PAT toolbox. This study is aimed at verifying the applicability of a multivariate LIF analyzer to monitor granulated powder blends in industrial settings. Its targets are to: (1) evaluate the critical parameters of powders to obtain robust, precise and accurate concentration predictions and (2) assess technology performance for in-line monitoring of blending operations. Varying dye properties, moisture levels and particle sizes have been shown to have the most significant impact on fluorescence emission. Reliable quantitative models can be obtained by controlling and/or mitigating these factors.

Non-aerated powder flows are frequently encountered in downstream pharmaceutical processes. Such flows occur at the entrance of powder compression units, and their characteristics are of great interest because any powder agglomeration or segregation can be detrimental to the quality of the final solid oral dosage form. This work was aimed at developing a process analytical technology (PAT) method, based on near-infrared spectroscopy (NIR) for the in-line powder flow characterization of pharmaceutical formulations. An Ibuprofen drug formulation was selected for study. A bench-scale hopper system was assembled to monitor powder flow behaviour. An in-line commercial NIR Axsun spectrometer and probe were chosen to collect in-line spectral data on dense, multicomponent, non-aerated powder flow prior to compression. Spectra were collected on flowing mannitol and pharmaceutical product blends. A specially designed, non-contact sampling interface allowed the collection of representative process powder flow spectra without affecting blend uniformity. A partial least squares chemometric model was developed for laboratory-prepared samples, to quantitatively determine the flowing powder's active pharmaceutical ingredient (API) level. Static sample spectra and flowing pure mannitol spectra proved to have a high degree of reproducibility. The model's standard error of calibration was 2.95% of the API level with a R2 of 0.991. Flowing blend powder spectra and API estimates showed variations consistent with those seen in model samples. The average values for flowing pharmaceutical blends were close to the API concentration, indicating that the proposed procedure was statistically acceptable. The model is considered very promising, and some improvements would lead to its final acceptance at production scale as a PAT tool.

Under different charging conditions, particles can be either attracted or repulsed by each other, causing powder agglomeration or segregation. Such behavior can be detrimental in many processes aimed at achieving particulate mixture homogeneity. Consequently, the effects of electrostatic charges on mixing kinetics must be well understood to insure a high level of process control, product quality, and reproducibility. In Part 1, an electrostatic charger is used to evaluate the ability of the studied particles to develop and retain an induced charge at the surface for a fixed period of time. Part 2 assesses the natural electrostatic charge developed by powders sliding across a stainless steel, plastic, or Tyvek chute. In Part 3, 2 binary systems were formed according to an experimental design under different charging conditions, and their behavior was quantified by measuring the degree of agglomeration attained. This work has shown that each raw material develops a different charge according to its physico-chemical properties and the type of contact surface. Electrostatic charges influence the creation of agglomerates under certain conditions. The presence of electrostatic charges must be accounted for in any effort to maximize mixing efficiency.

The measurement of average residence times and their variance, used to calculate the deviation of chemical reactors from the ideal behaviour of a perfectly-mixed vessel, or a plug flow pattern, has already been proposed in the literature to evaluate the segregation tendency of granular mixtures. The method consists of introducing pulse perturbation (of another material) to the established regular flow of a single granular material or a granular mixture and to assess the response of the system in terms of pulsed material concentration at the process outlet. The particles' average residence time and its standard deviation are then related to segregation tendency. Results from the application of this new method are useful when compared to those obtained from a reference mixture to be chosen according to a particular formulation development or process understanding need. This work applies the proposed method for various mixtures, both cohesive and non-cohesive, and derives phenomenological mathematical models expressing segregation tendency as a function of the parameters shown to be critical (i.e. statistically significant) to component segregation. The models were shown to be statistically and experimentally robust in the case of non-cohesive to slightly cohesive mixtures. Although the mathematical models are phenomenological, the findings allow for deriving mechanistic explanations on segregation tendency.