Spectroscopic characterization of tablet properties in a continuous powder blending and tableting process

UV/VIS-imaging of white caffeine tablets for prediction of CQAs: API content, crushing strength, friability, disintegration time and dissolution profile

The paper provides a demonstration of how UV/VIS imaging can be employed to evaluate the crushing strength, friability, disintegration time and dissolution profile of tablets comprised of solely white components. The samples were produced using different levels of compression force and API content of anhydrous caffeine. Images were acquired from both sides of the samples using UV illumination for the API content prediction, while the other parameters were assessed using VIS illumination. Based on the color histograms of the UV images, API content was predicted with 5.6 % relative error. Textural analysis of the VIS images yielded crushing strength predictions under 10 % relative error. Regarding friability, three groups were established according to the weight loss of the samples. Likewise, the evaluation of disintegration time led to the identification of three groups: less than 10 s, 11-35 s, and over 36 s. Successful classification of the samples was achieved with machine learning algorithms. Finally, immediate release dissolution profiles were accurately predicted under 5 % of RMSE with an artificial neural network. The 50 ms exposition time during image acquisition and the resulting outcomes underscore the practicality of machine vision for real-time quality control in solid dosage forms, regardless of the color of the API.

Terahertz time-domain spectroscopy for the investigation of tablets prepared from roller compacted granules

Roller compaction before tableting is a common unit operation to increase the processability of powders. Terahertz time-domain spectroscopy (THz-TDS) has recently been introduced as a potential process analytical technology (PAT) for measuring tablet porosity based on the refractive index of the tablet. Tablet porosity is a governing parameter for tablet disintegration and dissolution. The first aim of this study was to investigate tablets prepared from roller-compacted materials with THz-TDS to explore its usefulness for particle size evaluation of granules in tablets. Secondly, the impact of roller compaction and granule size before tablet compression on the established THz-TDS based measurement of tablet porosity was investigated. Microcrystalline cellulose and α-lactose monohydrate were roller compacted separately at five specific compaction forces (2, 4, 8, 12, and 16 kN cm-1) and fractionated into three size fractions. Tablets were prepared from the fractionated and unfractionated granules at twelve tableting pressures and subjected to THz-TDS transmission measurements. It was possible to use the scattering behaviour of the tablets at terahertz frequencies to describe the granulated materials' particle size changes during tableting. At the same time, prediction of porosity was impaired due to the deviation of the refractive index in strongly scattering samples. A correction method was introduced in which the porosity error was corrected based on the tablet's scattering behaviour, resulting in an improved prediction of tablet porosity. In conclusion, THz-TDS is considered a promising technique for the process monitoring of tableting based on its sensitivity to porosity and particle size changes within the tablet non-destructively, with a possible application as part of an in-process control strategy of the tableting of granulated or non-granulated materials.

Application of chemometrics using direct spectroscopic methods as a QC tool in pharmaceutical industry and their validation

This present review described the application of chemometrics using direct spectroscopic methods at the quality control (QC) laboratory of Pharmaceutical Industries. Using chemometrics methods, all QC assessments during the fabrication processes of the drug preparations can be well performed. Chemometrics methods have some advantages compared to the conventional methods, i.e., non-destructive, can be performed directly to intake samples without any extractions, unnecessary performing stability studies, and cost-effective. To achieve reliable results of analyses, all methods must be validated first prior to routine applications. According to the current Pharmacopeia, the validation parameters are specificity/selectivity, accuracy, repeatability, intermediate precision, range, detection limit, quantification limit and robustness. These validation data must meet the acceptance criteria, that have been described by the analytical target profile (ATP) of the drug preparations.

Non-destructive quantitative analysis of pharmaceutical ointment by transmission Raman spectroscopy

Transmission Raman spectroscopy was used to develop a non-destructive quantitative analytical model for the assay of a crystal dispersion-type ointment containing acyclovir as a model drug with a concentration of 3% w/w. The obtained Raman spectra were pre-processed by applying multiplicative scatter correction, standard normal variate, and first or second derivative by the Savitzky-Golay method to optimize the partial least squares (PLS) regression model. The optimized PLS model showed good prediction performance for 85%, 100%, and 115% label claims, with average recovery values of 100.7%, 99.3%, and 99.8%, respectively. Although the material properties and manufacturing method of acyclovir and white petrolatum were expected to be different from those of the calibration set, the mean recovery value of the commercial product was 104.2%. These results indicate that transmission Raman spectroscopy is a useful process analytical technology tool for product development and quality control of a crystal dispersion-type ointment with low drug concentration.

Industrial application of QbD and NIR chemometric models in quality improvement of immediate release tablets

Quality by Design (QbD) and chemometric models are different sides of the same coin. While QbD models utilize experimentally designed settings for optimization of some quality attributes, these settings can also be utilized for chemometric prediction of the same attributes. We aimed to synchronize optimization of comparative dissolution results of carvedilol immediate release tablets with chemometric prediction of dissolution profile and content uniformity of the product. As an industrial application, selection of variables for optimization was done by performing risk assessment utilizing the archived product records at the pharmaceutical site. Experimental tablets were produced with 20 different settings with the variables being contents of sucrose, sodium starch glycolate, lactose monohydrate, and avicel Ph 101. Contents of the excipients were modelled with F1 dissimilarity factor and F2 similarity factor in HCL, acetate, and USP dissolution media to determine the design space. We initiatively utilized Partial Least Square based Structural Equation Modelling (PLS-SEM) to explore how the excipients and their NIR records explained dissolution of the product. Finally, the optimized formula was utilized with varied content of carvedilol for chemometric prediction of the content uniformity.

Spectrophotometry and pharmaceutical PAT/RTRT: Practical challenges and regulatory landscape from development to product lifecycle

European Pharmacopoeia includes dedicated chapters for Raman, NIR and Chemometrics, as well as there is a lot of Academia research on the matter. Despite that, the word innovation is often associated to such tools and there is a still slow implementation at industry. The paper is the outcome of the Associazione Farmaceutici dell'Industria (AFI) Study Group on Process Innovation and Product Lifecycle; the aim is to describe some case studies referring to practical approaches in pharmaceutical industry, in order to depict challenges and opportunities for the implementation of spectroscopic techniques. Case studies include: feasibility and pre-screening evaluations, chemometric model development approaches, way for the method maintenance during commercial manufacturing, challenges for implementation on existing equipment and on sterile processes. Case studies refer to oral solid products, liquid products and sterile Active Pharmaceutical Ingradient (API) manufacturing. There are already successful and robust spectroscopic applications in pharmaceutical industry and the technology is mature: this is the outcome of a strong applied research performed at pharmaceutical production departments. It is necessary to acknowledge efforts done by industry as Research for strengthening the cooperation with Academia, so that advantage of process innovation might reach the patients in a fastest way.

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.

Fast, Spectroscopy-Based Prediction of In Vitro Dissolution Profile of Extended Release Tablets Using Artificial Neural Networks

The pharmaceutical industry has never seen such a vast development in process analytical methods as in the last decade. The application of near-infrared (NIR) and Raman spectroscopy in monitoring production lines has also become widespread. This work aims to utilize the large amount of information collected by these methods by building an artificial neural network (ANN) model that can predict the dissolution profile of the scanned tablets. An extended release formulation containing drotaverine (DR) as a model drug was developed and tablets were produced with 37 different settings, with the variables being the DR content, the hydroxypropyl methylcellulose (HPMC) content and compression force. NIR and Raman spectra of the tablets were recorded in both the transmission and reflection method. The spectra were used to build a partial least squares prediction model for the DR and HPMC content. The ANN model used these predicted values, along with the measured compression force, as input data. It was found that models based on both NIR and Raman spectra were capable of predicting the dissolution profile of the test tablets within the acceptance limit of the f2 difference factor. The performance of these ANN models was compared to PLS models using the same data as input, and the prediction of the ANN models was found to be more accurate. The proposed method accomplishes the prediction of the dissolution profile of extended release tablets using either NIR or Raman spectra.

Integrated continuous manufacturing in pharmaceutical industry: current evolutionary steps toward revolutionary future

Continuous manufacturing (CM) has the potential to provide pharmaceutical products with better quality, improved yield and with reduced cost and time. Moreover, ease of scale-up, small manufacturing footprint and on-line/in-line monitoring and control of the process are other merits for CM. Regulating authorities are supporting the adoption of CM by pharmaceutical manufacturers through issuing proper guidelines. However, implementation of this technology in pharmaceutical industry is encountered by a number of challenges regarding the process development and quality assurance. This article provides a background on the implementation of CM in pharmaceutical industry, literature survey of the most recent state-of-the-art technologies and critically discussing the encountered challenges and its future prospective in pharmaceutical industry.

Data fusion strategies for performance improvement of a Process Analytical Technology platform consisting of four instruments: An electrospinning case study

The aim of this work was to develop a PAT platform consisting of four complementary instruments for the characterization of electrospun amorphous solid dispersions with meloxicam. The investigated methods, namely NIR spectroscopy, Raman spectroscopy, Colorimetry and Image analysis were tested and compared considering the ability to quantify the active pharmaceutical ingredient and to detect production errors reflected in inhomogeneous deposition of fibers. Based on individual performance the calculated RMSEP values ranged between 0.654% and 2.292%. Mid-level data fusion consisting of data compression through latent variables and application of ANN for regression purposes proved efficient, yielding an RMSEP value of 0.153%. Under these conditions the model could be validated accordingly on the full calibration range. The complementarity of the PAT tools, demonstrated from the perspective of captured variability and outlier detection ability, contributed to model performance enhancement through data fusion. To the best of the author's knowledge, this is the first application of data fusion in the field of PAT for efficient handling of big-analytical-data provided by high-throughput instruments.

Assessment of blend uniformity in a continuous tablet manufacturing process

Blend uniformity was monitored throughout a continuous manufacturing (CM) process by near infrared (NIR) spectroscopic measurements of flowing blends and compared to the drug concentration in the tablets. The NIR spectra were obtained through the chute after the blender and within the feed frame, while transmission spectra were obtained for the tablets. The CM process was performed with semi-fine acetaminophen blends at 10.0% (w/w). The blender was operated at 250 RPM, for best performance, and 106 and 495 rpm where a lower mixing efficiency was expected. The variation in blender RPM increased the variation in drug concentration at the chute but not at the feed frame. Statistical results show that the drug concentration of tablets can be predicted, with great accuracy, from blends within the feed frame. This study demonstrated a mixing effect within the feed frame, which contribute to a 60% decrease in the relative standard deviation of the drug concentration, when compared to the chute. Variographic analysis showed that the minimum sampling and analytical error was five times less in the feed frame than the chute. This study demonstrates that the feed frame is an ideal location for monitoring the drug concentration of powder blends for CM processes.

Raman Spectroscopy for Process Analytical Technologies of Pharmaceutical Secondary Manufacturing

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

In-Line UV-Vis Spectroscopy as a Fast-Working Process Analytical Technology (PAT) during Early Phase Product Development Using Hot Melt Extrusion (HME)

This paper displays the potential of an in-line PAT system for early phase product development during pharmaceutical continuous manufacturing following a Quality by Design (QbD) framework. Hot melt extrusion (HME) is used as continuous manufacturing process and UV⁻Vis spectroscopy as an in-line monitoring system. A sequential design of experiments (DoE) (screening, optimisation and verification) was used to gain process understanding for the manufacture of piroxicam (PRX)/Kollidon® VA64 amorphous solid dispersions. The influence of die temperature, screw speed, solid feed rate and PRX concentration on the critical quality attributes (CQAs) absorbance and lightness of color (L*) of the extrudates was investigated using multivariate tools. Statistical analysis results show interaction effects between concentration and temperature on absorbance and L* values. Solid feed rate has a significant effect on absorbance only and screw speed showed least impact on both responses for the screening design. The optimum HME process conditions were confirmed by 4 independent studies to be 20% w/w of PRX, temperature 140 °C, screw speed 200 rpm and feed rate 6 g/min. The in-line UV-Vis system was used to assess the solubility of PRX in Kollidon® VA64 by measuring absorbance and L* values from 230 to 700 nm. Oversaturation was observed for PRX concentrations higher than 20% w/w. Oversaturation can be readily identified as it causes scattering in the visible range. This is observed by a shift of the baseline in the visible part of the spectrum. Extrudate samples were analyzed for degradation using off-line High-Performance Liquid Chromatography (HPLC) standard methods. Results from off-line experiments using differential scanning calorimetry (DSC), and X-ray diffraction (XRD) are also presented.