In-line monitoring of Ibuprofen during and after tablet compression using near-infrared spectroscopy

Real-time monitoring of small changes in powder blends and ejected tablets in a low-dose formulation with 1 %w/w of active pharmaceutical ingredient using Raman and near-infrared spatially resolved spectroscopy within a tablet press

This study used Raman and near-infrared (NIR) spectroscopy to monitor small real-time changes in powder blends and tablets in low-dose pharmaceutical formulations. The research aims to enhance process analytical technology (PAT) in pharmaceutical manufacturing, ensuring high-quality and uniform products with applications to produce drugs with narrow therapeutic indices (NTI). The study utilizes Raman and NIR spatially resolved spectroscopy (SRS) techniques to monitor a moderate cohesive material's active pharmaceutical ingredient (API) concentrations during manufacturing. The sampling locations were a bin blender for the batch blending procedure where the powder heterogeneity plays a significant role in product homogeneity, a feed frame of a tablet press where powder blend dynamics is critical to final product quality, and the outlet port of the tablet press where tablets immediately after ejection can be monitored in real-time. The study used semifine acetaminophen (APAP) as the API. Results indicated that Raman and NIR SRS could detect small API concentration changes as low as 0.50 %w/w, demonstrating their sensitivity and utility in real-time monitoring. The findings support the feasibility of these techniques in ensuring tight process control and highlight the performance of reducing waste and optimizing manufacturing processes in line with quality by design principles. The results highlight the importance of residence time distribution (RTD) in understanding the flow of the materials and powder behavior within the tablet press feed frame. RTD analyses showed that both Raman and NIR SRS techniques could effectively track concentration changes and ensure uniformity in the powder blends and tablets with signal-to-noise ratios higher than 3, demonstrating the sensitivity of the methods to small API changes. The %RSD during a steady state of 250 s (corresponding to 1.04 kg of material at 15 kg/h) for the step changes presented values of 6.74 % at 0.50 %w/w, 5.39 % at 1.00 %w/w, and 2.99 % at 1.50 %w/w for Raman predictions in powder blends within the feed frame and 15.46 % at 0.50 %w/w, 9.64 % at 1.00 %w/w, and 5.68 % at 1.50 %w/w for NIR SRS predictions of tablets ejected at the outlet port of the tablet press. In conclusion, this research demonstrates the potential of advanced spectroscopic techniques and data analysis in pharmaceutical manufacturing. By enabling precise real-time monitoring and control, these techniques contribute to higher-quality drug products, particularly NTI drugs, aligning with modern regulatory expectations and advancing pharmaceutical production technology.

Development of novel portable NIR spectroscopy process analytical technology (PAT) tool for monitoring the transition of ibuprofen to ibuprofen sodium during wet granulation process

The aim of this research was to develop a process analytical technology (PAT) tool for monitoring the transformation of the active ingredient ibuprofen into the fast-dissolving salt ibuprofen sodium during the wet granulation process. Two near-infrared (NIR) spectrophotometers, portable and benchtop spectrophotometer, were compared. During the analysis with the built models, both demonstrated comparable accuracy and precision (R2X = 0.995, R2Y = 0.927, Q2 = 0.995, and R2X = 0.990, R2Y = 0.948, Q2 = 0.992, respectively). Considering the applicability, a model based on the portable NIR spectroscopic data was chosen for further development and application as a PAT tool for monitoring different steps during the wet granulation process. The evaluation of the model's predictive capability involved analyzing laboratory trial batches with varying amounts of sodium carbonate, resulting in different concentrations of ibuprofen sodium at the end of the wet granulation process. Subsequently, tablets were manufactured from each trial batch, followed by dissolution analysis. The dissolution rate assays were in good agreement with the NIR-predicted concentrations of ibuprofen sodium at the end of the wet granulation process. Based on the results, the proposed model provides an excellent tool to monitor the ibuprofen acid-salt transformation, to determine the end-point of the reaction, and to efficiently control the wet granulation process.

Analytical comparison between batch and continuous direct compression processes for pharmaceutical manufacturing using an innovative UV-Vis reflectance method and chemometrics

Advancements in industrial technologies and the application of quality by design (QbD) guidelines are shifting the attention of manufacturers towards innovative production techniques. In the pharmaceutical field, there is a significant focus on the implementation of continuous processes, in which the production stages are carried out continuously, without the need to interrupt the process and store the production intermediates, as in traditional batch production. Such innovative production techniques also require the development of proper analytical methods able to analyze the products in-line, while still being processed. The present study aims to compare a traditional batch manufacturing process with an alternative continuous one. To this end, a real pharmaceutical formulation was used, substituting the active pharmaceutical ingredient (API) with riboflavin, at the concentration of 2 %w/w. Moreover, a direct and non-destructive analytical method based on UV-Vis reflectance spectroscopy was applied for the quantification of riboflavin in the final tablets, and compared with a traditional absorbance analysis. Good results were obtained in the comparison of both the two manufacturing processes and the two analytical methods, with R2 higher than 0.9 for all the calculated calibration models and predicted riboflavin concentrations that never significantly overcame the 15 % limits recommended by the pharmacopeia. The continuous production method demonstrated to be as reliable as the batch one, allowing to save time and money in the production step. Moreover, UV-Vis reflectance was proved to be an interesting alternative to absorption spectroscopy, which, with the proper technology, could be implemented for in-line process control.

Effect of process parameters and formulation properties on the lead-lag between in-line NIR tablet press feed frame and off-line NIR tablet measurements

The use of in-line near-infrared (NIR) measurements for tablet potency monitoring and diversion was studied. First, the optimal sample size for in-line NIR measurements inside the feed chute and the dosing and filling chamber of the tablet press feed frame was determined to allow proper comparison between these different measurement positions. Because of the considerably longer measurement time needed to obtain the same sample size inside the feed chute compared to the feed frame, the possibility of powder segregation inside the feed chute and the additional powder mixing inside the feed frame, the latter is preferred over the feed chute for in-line blend potency monitoring. Next, a design of experiments (DoE) was performed to evaluate the effect of paddle speed, turret speed, overfill level and formulation properties upon the lead-lag and the time it takes before the powder blend that is expelled at the dosing station is measured by the NIR inside the dosing chamber. Lead-lag is defined as the difference in time and API concentration between the measured in-line NIR response inside the filling chamber of the feed frame and the off-line NIR tablet response. Paddle speed and turret speed were the only compression parameters affecting lead-lag. Lead-lag decreased with increasing paddle speed for the first formulation. For the second formulation, lead-lag decreased with decreasing paddle speed and/or increasing turret speed. Formulation properties did not have an effect on the lead-lag. The in-line NIR response inside the dosing chamber of the feed frame was found to be closely following the tablet NIR response. Therefore, the dosing chamber could be used as an additional in-line NIR position for tablet potency monitoring and diversion. It can provide an extra layer of confidence about the final tablet quality. To demonstrate this potential benefit of simultaneous in-line NIR measurements inside the filling and dosing chamber of the feed frame, a tableting experiment was performed where a surrogate API spike was introduced into the product stream to mimic a potential process disturbance. The in-line NIR measurements inside the filling chamber allow diverting tablets in-time when the blend potency crosses the predefined control limits. And because the NIR response inside the dosing chamber closely follows the tablet NIR response, tablet diversion can discontinue when the blend potency inside the dosing chamber is again within the control limits. This could increase the yield of the tableting process by avoiding a longer than needed wash-out period and rejecting tablets that meet the release limits.

The application of Near-Infrared Spatially Resolved Spectroscopy in scope of achieving continuous real-time quality monitoring and control of tablets with challenging dimensions

In scope of achieving real-time release of tablets, quality attributes need to be monitored and controlled through Process Analytical Technology tools such as near-infrared spectroscopy (NIRS). The authors evaluated the suitability of NIR-Spatially Resolved Spectroscopy (NIR-SRS) for continuous real-time monitoring and control of content uniformity, hardness and homogeneity of tablets with challenging dimensions. A novel user-friendly research and development inspection unit was used as standalone equipment for the analysis of small oblong tablets with deep-cut break lines. A total of 66 tablets varying in hardness and Active Pharmaceutical Ingredient (API) content were inspected, with each tablet being analysed five times and measurements repeated on three different days. Partial Least Squares (PLS) models were developed to assess content uniformity and hardness, of which the former showed higher accuracy. The authors attempted to visualize tablet homogeneity through NIR-SRS spectra by regressing all spectra obtained during a single measurement using a content uniformity PLS model. The NIR-SRS probe demonstrated its potential towards real-time release testing through its ability to quickly monitor content uniformity, hardness and visualize homogeneity, even for tablets with challenging dimensions.

Discrimination of Substandard and Falsified Formulations from Genuine Pharmaceuticals Using NIR Spectra and Machine Learning

Near-infrared (NIR) spectroscopy is a promising technique for field identification of substandard and falsified drugs because it is portable, rapid, nondestructive, and can differentiate many formulated pharmaceutical products. Portable NIR spectrometers rely heavily on chemometric analyses based on libraries of NIR spectra from authentic pharmaceutical samples. However, it is difficult to build comprehensive product libraries in many low- and middle-income countries due to the large numbers of manufacturers who supply these markets, frequent unreported changes in materials sourcing and product formulation by the manufacturers, and general lack of cooperation in providing authentic samples. In this work, we show that a simple library of lab-formulated binary mixtures of an active pharmaceutical ingredient (API) with two diluents gave good performance on field screening tasks, such as discriminating substandard and falsified formulations of the API. Six data analysis models, including principal component analysis and support-vector machine classification and regression methods and convolutional neural networks, were trained on binary mixtures of acetaminophen with either lactose or ascorbic acid. While the models all performed strongly in cross-validation (on formulations similar to their training set), they individually showed poor robustness for formulations outside the training set. However, a predictive algorithm based on the six models, trained only on binary samples, accurately predicts whether the correct amount of acetaminophen is present in ternary mixtures, genuine acetaminophen formulations, adulterated acetaminophen formulations, and falsified formulations containing substitute APIs. This data analytics approach may extend the utility of NIR spectrometers for analysis of pharmaceuticals in low-resource settings.

Pharmaceutical tablet compression: measuring temporal and radial concentration profiles to better assess segregation

Concentration monitoring inside a tablet press feed frame is important not only to assess the composition of the powder blend being compressed into tablets but also to detect quality affecting phenomena such as powder segregation. Near infrared spectroscopy has been successfully used to monitor powder concentration inside feed frame; however, so far, this methodology does not provide information on local spatial variability, since it probes a very small area of powder sample. Near infrared chemical imaging (NIR CI) has the potential to improve process monitoring because it can simultaneously acquire a plurality of spectra covering nearly the entire width of feed frame, thereby making it possible to detect local variations in powder concentration.The present work uses both NIRS and NIR CI to monitor the concentration of Ibuprofen and Ascorbic acid in multi-component mock pharmaceutical blends flowing through the feed frame of an industrial tablet press. The concentrations of Ibuprofen and Ascorbic acid were successfully monitored in multi-component powder blends. NIR spectral wavelength ranges and pre-treatments were simultaneously optimized via a genetic algorithm. N-way PLS approach for concentration monitoring was found to be more suitable than regular PLS when analyzing spectral images and provided the ability to visualize spatial segregation.

Development of a tablet press feed frame lead lag determination model using in-line and off-line NIR measurements

For continuous pharmaceutical manufacturing of oral solid dosages, it is essential that product quality is measured inline. In this application, a continuous rotary tablet press is used. The goal is a model-based assessment of the quality of the blend in the feed frame to determine whether the concentration of the active pharmaceutical ingredient (API) will be within the prescribed limits. This is to achieve a better quality assurance than by offline testing of a small sample of tablets. In this way, product quality for real-time release (RTR) could be implemented. With a near-infrared (NIR) probe, the concentration of the API in the feed chute and the feed-frame were measured, as well as the API concentration of the tablets by an offline NIR measurement. These different data sets are connected and used for the residence time distribution characterization of the mixing dynamic of the tablet press. A residence time distribution model is fitted to the data, and is further used to compute the lead-lag time. This yields information on how long it takes for a quantity of product to go from being measured in the feed frame until ending up in tablets. Further, it gives information on the occurrence of mixing in the feed-frame itself. These models allow making accurate predictions of whether tablets fall within specified concentration range in real-time. The real-time prediction can be used in combination with a control system both to maintain the quality of the blend as well as to know which tablets to discard. This real-time quality assurance will lead to less material waste and fewer declined batches of tablets.

Determination and understanding of lead-lag between in-line NIR tablet press feed frame and off-line NIR tablet measurements

The influence of different tableting process parameters on lead-lag was studied by collecting in-line near-infrared (NIR) spectra in the filling chamber of the tablet press feed frame and off-line NIR tablet data. Lead-lag is defined as the difference in time and API concentration between the measured in-line feed frame NIR response and the off-line NIR tablet data. Lead-lag results from the product formulation blend undergoing additional mixing after passing the NIR probe inside the feed frame, before being filled into the dies of the tablet press. A design of experiments (DoE) was performed to evaluate the effect of the tableting process factors paddle speed, turret speed, overfill level, paddle speed ratio and feed frame type upon lead-lag. Paddle speed and turret speed were identified as the only tableting parameters affecting lead-lag. Lead-lag decreased with increasing paddle speed or turret speed and became negligible at high paddle speed and high turret speed. Overfill level, paddle speed ratio and feed frame type did not affect lead-lag, suggesting that the amount and the trajectory of the recirculating powder in the feed frame did not significantly vary and hence influence the lead-lag within the examined process factor ranges. Finally, a methodology was developed using the in-line feed frame NIR measurements for the continuous monitoring and control of blend potency and tablet content uniformity. Tablet diversion should start when the in-line feed frame monitored blend potency exceeds the predefined control limits and can discontinue when this blend potency is again within the control limits for a duration equal to the lead-lag time. A combination of continuous blend potency monitoring inside the feed frame and in-process tablet weight control allows real-time tablet content uniformity assurance. Although the findings of this study are restricted to the specific equipment, tableting parameter ranges and product formulation used, the suggested approach for lead-lag determination and continuous tablet content uniformity monitoring can be applied to any rotary tablet press and product formulation.

Evaluating the impact of NIR pre-processing methods via multiblock partial least-squares

Near-infrared (NIR) spectral data are used in many applications to predict physical and chemical properties. However, it can result in poor predictive models when untreated spectra are directly used to estimate these properties. Many pre-preprocessing techniques are available to reduce noise and variance unrelated to the studied property but choosing which one to apply can be tricky. Existing methods to select a pre-processing are time-consuming or do not allow for a meaningful comparison of the different techniques. Even though new methods focus on extracting complementary information from each pre-processing, an optimal combination is still required to obtain efficient predictive models and avoid extensive computational costs. Here, we propose an approach using multiblock partial least squares (MBPLS) to simultaneously compare the impact of the pre-processing techniques on spectral data and as a result on the regression models. Superloadings provide qualitative and quantitative information on pre-processed data. This tool helps compare and determine which pre-processing technique, or combinations thereof, that may be appropriate for a dataset, not just a single "best" one. Using this, the analyst is then better equipped to make a final choice when selecting which ones to include. This method is tested on artificial signals and NIR spectra from corn samples.

Real-time monitoring of the column chromatographic process of Phellodendri Chinensis Cortex part I: end-point determination based on near-infrared spectroscopy combined with machine learning

A novel and rapid approach for end-point determination of berberine hydrochloride, phellodendrine chloride and total alkaloids in a column chromatographic process.

Real-time monitoring of the column chromatographic process of Phellodendri Chinensis Cortex part II: multivariate statistical process control based on near-infrared spectroscopy

Multivariate statistical process control has been successfully used for the real-time monitoring of the column chromatographic process of Phellodendri Chinensis Cortex.

PAT implementation for advanced process control in solid dosage manufacturing - A practical guide

The implementation of continuous pharmaceutical manufacturing requires advanced control strategies rather than traditional end product testing or an operation within a small range of controlled parameters. A high level of automation based on process models and hierarchical control concepts is desired. The relevant tools that have been developed and successfully tested in academic and industrial environments in recent years are now ready for utilization on the commercial scale. To date, the focus in Process Analytical Technology (PAT) has mainly been on achieving process understanding and quality control with the ultimate goal of real-time release testing (RTRT). This work describes the workflow for the development of an in-line monitoring strategy to support PAT-based real-time control actions and its integration into solid dosage manufacturing. All stages are discussed in this paper, from process analysis and definition of the monitoring task to technology assessment and selection, its process integration and the development of data acquisition.

A review of emerging technologies enabling improved solid oral dosage form manufacturing and processing

Tablets are the most widely utilized solid oral dosage forms because of the advantages of self-administration, stability, ease of handling, transportation, and good patient compliance. Over time, extensive advances have been made in tableting technology. This review aims to provide an insight about the advances in tablet excipients, manufacturing, analytical techniques and deployment of Quality by Design (QbD). Various excipients offering novel functionalities such as solubility enhancement, super-disintegration, taste masking and drug release modifications have been developed. Furthermore, co-processed multifunctional ready-to-use excipients, particularly for tablet dosage forms, have benefitted manufacturing with shorter processing times. Advances in granulation methods, including moist, thermal adhesion, steam, melt, freeze, foam, reverse wet and pneumatic dry granulation, have been proposed to improve product and process performance. Furthermore, methods for particle engineering including hot melt extrusion, extrusion-spheronization, injection molding, spray drying / congealing, co-precipitation and nanotechnology-based approaches have been employed to produce robust tablet formulations. A wide range of tableting technologies including rapidly disintegrating, matrix, tablet-in-tablet, tablet-in-capsule, multilayer tablets and multiparticulate systems have been developed to achieve customized formulation performance. In addition to conventional invasive characterization methods, novel techniques based on laser, tomography, fluorescence, spectroscopy and acoustic approaches have been developed to assess the physical-mechanical attributes of tablet formulations in a non- or minimally invasive manner. Conventional UV-Visible spectroscopy method has been improved (e.g. fiber-optic probes and UV imaging-based approaches) to efficiently record the dissolution profile of tablet formulations. Numerous modifications in tableting presses have also been made to aid machine product changeover, cleaning, and enhance efficiency and productivity. Various process analytical technologies have been employed to track the formulation properties and critical process parameters. These advances will contribute to a strategy for robust tablet dosage forms with excellent performance attributes.

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.

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.

Sample Mass Estimate for the Use of Near-Infrared and Raman Spectroscopy to Monitor Content Uniformity in a Tablet Press Feed Frame of a Drug Product Continuous Manufacturing Process

Recently, feed frame-based process analytical technology measurements used to assure product quality during continuous manufacturing processes have received significant attention. These measurements are able to accurately determine uniformity of the powder blend before compression, and in these applications, it is necessary to understand the interrogated sample volume per measurement. This understanding ensures that the blend measurement can be indicative of the uniformity of the final dosage form. A scientifically sound approach is proposed here to estimate sample mass for a continuous manufacturing process that utilizes either near infrared or Raman spectroscopy. A wide range of commercially available probes with varying spot diameters are considered. By comparing near infrared and Raman spectroscopy, an optimal range of probe spot diameters was identified in order to reach an estimated sample mass between 50 and 500 mg for pharmaceutical blends per measurement, which is equivalent to common tablet weight ranges for solid oral dosage forms currently on the market.

Feed frame: The last processing step before the tablet compaction in pharmaceutical manufacturing

The feed frame is a force-feeding device used in the die filling process. The die filling process is crucial within pharmaceutical manufacturing to guarantee the critical quality attributes of the tablets. In recent years, interest in this unit has increased because it can affect the properties of the powder blend and tablets, and because of the success in real time monitoring of powder blend uniformity potential for Process Analytical Technology as described in this review. The review focuses on the recent advances in understanding the powder flow behavior inside the feed frame and how the residence time distribution of the powder within the feed frame is affected by the operating conditions and design parameters. Furthermore, this review also highlights the effect of the paddle wheel design and feed frame process parameters on the tablet weight, the principal variable for measuring die filling performance.

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.