Assessment of blend uniformity in a continuous tablet manufacturing process

Real-time release testing of in vitro dissolution and blend uniformity in a continuous powder blending process by NIR spectroscopy and machine vision

Continuous manufacturing is gaining increasing interest in the pharmaceutical industry, also requiring real-time and non-destructive quality monitoring. Multiple studies have already addressed the possibility of surrogate in vitro dissolution testing, but the utilization has rarely been demonstrated in real-time. Therefore, in this work, the in-line applicability of an artificial intelligence-based dissolution surrogate model is developed the first time. NIR spectroscopy-based partial least squares regression and artificial neural networks were developed and tested in-line and at-line to assess the blend uniformity and dissolution of encapsulated acetylsalicylic acid (ASA) - microcrystalline cellulose (MCC) powder blends in a continuous blending process. The studied blend is related to a previously published end-to-end manufacturing line, where the varying size of the ASA crystals obtained from a continuous crystallization significantly affected the dissolution of the final product. The in-line monitoring was suitable for detecting the variations in the ASA content and dissolution caused by the feeding of ASA with different particle sizes, and the at-line predictions agreed well with the measured validation dissolution curves (f2 = 80.5). The results were further validated using machine vision-based particle size analysis. Consequently, this work could contribute to the advancement of RTRT in continuous end-to-end processes.

Blend uniformity monitoring in a continuous manufacturing mixing process for a low-dosage formulation using a stream sampler and near infrared spectroscopy

Continuous manufacturing has the potential to offer several benefits for the production of oral solid dosage forms, including reduced costs, low-scale equipment, and the application of process analytical technology (PAT) for real-time process control. This study focuses on the implementation of a stream sampler to develop a near infrared (NIR) calibration model for blend uniformity monitoring in a continuous manufacturing mixing process. Feeding and mixing characterizations were performed for three loss-in-weight feeders and a commercial continuous mixer to prepare powder blends of 2.5-7.5 % w/w ibuprofen DC 85 W with a total throughput of 33 kg/h. The NIR spectral acquisition was performed after the mixing stage using a stream sampler for flowing powders. A continuous mixer shaft speed of 250 RPM was selected to operate the mixing process based on a variability analysis developed with in-line spectral data acquired using the stream sampler at 6 RPM. A partial least squares regression (PLS-R) model was performed and evaluated, yielding a root-mean-square error of prediction (RMSEP) of 0.39 % w/w and a bias of 0.05 % w/w. An independent experimental run conducted two days later revealed that the continuous mixing process and the NIR calibration model presented low day-to-day variation. The minimum practical error (MPE) and sill values through variographic analysis showed low variance associated with the sampling process using the stream sampler. Results demonstrated the promising capacity of the stream sampler coupled to an NIR probe to be implemented within continuous manufacturing processes for the real-time determination of API concentration.

Characterizing a design space for a twin-screw wet granulation process: A case study of extended-release tablets

Twin-screw wet granulation is an emerging continuous manufacturing technology for solid oral dosage forms. This technology has been successfully employed for the commercial manufacture of immediate-released tablets. However, the higher polymer content in extended-release (ER) formulations may present challenges in developing and operating within a desired design space. The work described here used a systematic approach for defining the optimum design space by understanding the effects of the screw design, operating parameters, and their interactions on the critical characteristics of granules and ER tablets. The impacts of screw speed, powder feeding rate, and the number of kneading (KEs) and sizing elements on granules and tablets characteristics were investigated by employing a definitive screening design. A semi-mechanistic model was used to calculate the residence time distribution parameters and validated using the tracers. The results showed that an increase in screw speed decreased the mean residence time of the material within the barrel, while an increase in the powder feeding rate or number of KEs did the opposite and increased the barrel residence time. Screw design and operating parameters affected the flow and bulk characteristics of granules. The screw speed was the most significant factor impacting the tablet's breaking strength. The dissolution profiles revealed that granule characteristics mainly influenced the early phase of drug release. This study demonstrated that a simultaneous optimization of both operating and screw design parameters was beneficial in producing ER granules and tablets of desired performance characteristics while mitigating any failure risks, such as swelling during processing.

The Use of a Closed Feed Frame for the Development of Near-Infrared Spectroscopic Calibration Model to Determine Drug Concentration

PURPOSE

This study evaluates the use of the closed feed frame as a material sparing approach to develop near-infrared (NIR) spectroscopic calibration models for monitoring blend uniformity. The effect of shear induced by recirculation on NIR spectra was also studied.

METHODS

Calibration models were developed using NIR spectra obtained in the closed feed frame for two cases. For case 2, blends that flowed through the open feed frame were predicted with the model. The shear effect of the feed frame on the blends was assessed through the characterization of powder properties before and after recirculation.

RESULTS

The physical characterization of the blends confirmed that the powder properties were not altered after recirculation within the closed feed frame. Both calibration models provided highly accurate predictions of the test sets with low bias (0.03% w/w and -0.06% w/w) and relative standard error of prediction (1.9% and 3.7%), respectively. The predictive performance of the calibration models was not affected by the shear effect.

CONCLUSION

Recirculation within the closed feed frame did not change the physical properties of the blends studied. The prediction of blends flowing through the open feed frame was possible with a calibration model developed in the closed feed frame. The closed feed frame could reduce the materials needed to develop calibration models by more than 90%.

Image-based simultaneous particle size distribution and concentration measurement of powder blend components with deep learning and machine vision

This work presents a system, where deep learning was used on images captured with a digital camera to simultaneously determine the API concentration and the particle size distribution (PSD) of two components of a powder blend. The blend consisted of acetylsalicylic acid (ASA) and calcium hydrogen phosphate (CHP), and the predicted API concentration was found corresponding with the HPLC measurements. The PSDs determined with the method corresponded with those measured with laser diffraction particle size analysis. This novel method provides fast and simple measurements and could be suitable for detecting segregation in the powder. By examining the powders discharged from a batch blender, the API concentrations at the top and bottom of the container could be measured, yielding information about the adequacy of the blending and improving the quality control of the manufacturing process.

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.

Impact of Silica Dry Coprocessing with API and Blend Mixing Time on Blend Flowability and Drug Content Uniformity

This paper considers two fine-sized (d50 ∼10 µm) model drugs, acetaminophen (mAPAP) and ibuprofen (Ibu), to examine the effect of API dry coprocessing on their multi-component medium DL (30 wt%) blends with fine excipients. The impact of blend mixing time on the bulk properties such as flowability, bulk density, and agglomeration was studied. The hypothesis tested is that blends with fine APIs at medium DL require good blend flowability to have good blend uniformity (BU). Moreover, the good flowability could be achieved through dry coating with hydrophobic (R972P) silica, which reduces agglomeration of not only fine API, but also of its blends while using fine excipients. For uncoated APIs, the blend flowability was poor, i.e. cohesive regime at all mixing times, and the blends failed to achieve acceptable BU. In contrast, for dry coated APIs, their blend flowability improved to easy-flow regime or better, improving with mixing time, and as hypothesized, all blends consequently achieved desired BU. All dry coated API blends exhibited improved bulk density and reduced agglomeration, attributed to mixing induced synergistic property enhancements, likely due to silica transfer. Despite coating with hydrophobic silica, tablet dissolution was improved, attributed to the reduced agglomeration of fine API.

Assessment of blend uniformity in a stream sampler device using Raman spectroscopy

This study describes the first implementation of Raman spectrometer in a stream sampler for the in-line monitoring of low drug concentration in poor flowability powder blends. Raman spectra were continuously acquired as the powder blends flowed through the stream sampler operating with a paddle wheel speed of 10 RPM and used to develop the calibration models. A calibration model was developed to quantify caffeine concentration from 1.50 to 4.50% w/w using Partial Least Squares Regression (PLS-R). Three test set blends were used to assess the prediction errors of the calibration model. Caffeine concentration was predicted for the test set blends with a root mean square error of prediction of 0.21% w/w and a low bias of -0.03% w/w. The calibration model showed good prediction performance with an estimated sample mass of 83 mg. Variographic analysis demonstrated the low process variance of the real-time spectral acquisition through minimum practical error and sill values. The results showed the ability of the Raman spectrometer coupled with the stream sampler to monitor low drug concentration for poor flowability blends.

Enhanced blend uniformity and flowability of low drug loaded fine API blends via dry coating: The effect of mixing time and excipient size

Although previous research demonstrated improved flowability, packing, fluidization, etc. of individual powders via nanoparticle dry coating, none considered its impact on very low drug loaded blends. Here, fine ibuprofen at 1, 3, and 5 wt% drug loadings (DL) was used in multi-component blends to examine the impact of the excipients size, dry coating with hydrophilic or hydrophobic silica, and mixing times on the blend uniformity, flowability and drug release rates. For uncoated active pharmaceutical ingredients (API), the blend uniformity (BU) was poor for all blends regardless of the excipient size and mixing time. In contrast, for dry coated API having low agglomerate ratio (AR), BU was dramatically improved, more so for the fine excipient blends, at lesser mixing times. For dry coated API, the fine excipient blends mixed for 30 min had enhanced flowability and lower AR; better for the lowest DL having lesser silica, likely due to mixing induced synergy of silica redistribution. For the fine excipient tablets, dry coating led to fast API release rates even with hydrophobic silica coating. Remarkably, the low AR of the dry coated API even at very low DL and amounts of silica in the blend led to the enhanced blend uniformity, flow, and API release rate.

Implementation of a fully integrated CM direct compression and coating process at a commercial pharmaceutical facility - Part 2: PAT and RTD results for normal operational conditions batches

This is the second of two articles detailing the continuous manufacturing (CM) development and implementation activities for an marketed product which have been realized in novel, qualified equipment, using validated control strategy elements to enable manufacture of batches under current good manufacturing practices (cGMP) and compliant with data integrity principles. Here, the application of process analytical technologies (PAT) and automation tools on batches produced under normal operational conditions is reviewed. The results from residence time distribution (RTD) models for predicting API concentration, in-line near infrared (NIR) testing of blend uniformity (BU) and at-line NIR spectroscopy analysis of core tablet concentration and tablet identity for real-time release testing (RTRT) are discussed. The influences of process equipment and design choices on NIR and RTD model variability, as well as the use of the PAT tools for monitoring the evolving properties understanding of CM process development, such as overcoming flow instabilities, is described. Results demonstrate that the RTD and NIR models developed and validated are robust to operating conditions and are critical for assuring steady state control of the continuous manufacturing process. Finally, the NIR and RTD model lifecycle, including procedures for necessary and normal model upgrades in a cGMP production environment, are presented.

Bilayer fixed-dose combination tablet for curcumin microparticles and piroxicam and in vitro evaluation

Aim: In the present work, fixed-dose combination of bilayer tablets for piroxicam as and curcumin as immediate-release and sustained-release layer (SRL) respectively for management of inflammatory response. Materials & methods: The SRL include Curcumin polycaprolactone microparticles from spray drying. The tablet layers include Pearlitol 200SD, Microcrystalline cellulose PH101, Aerosil 200, talc each layer. Results: SEM studies confirm spherical microparticles. PXRD and DSC studies confirm the amorphous microparticles. In vitro studies exhibit, an immediate release and sustained release for Piroxicam and Curcumin after 2 h. Cellular uptake studies on RAW 264.7 cells confirm the complete internalization of microparticles. Conclusion: Therefore, it was concluded that microparticles can be formulated into a unit dosage form for the management of inflammation.

Batch versus continuous blending of binary and ternary pharmaceutical powder mixtures

The material properties of excipients and active pharmaceutical ingredients (API's) are important parameters that affect blend uniformity of pharmaceutical powder formulations. With the current shift from batch to continuous manufacturing in the pharmaceutical industry, blending of excipients and API is converted to a continuous process. The relation between material properties and blend homogeneity, however, is generally based on batch-wise blending trials. Limited information is available on how material properties affect blending performance in a continuous process. Here, blending of API and excipients is studied in both a batch and a continuous process. Homogeneity of the resulting mixtures is analyzed, which reveals that the impact of material properties is very different in a continuous process. Where parameters such as particle size, density and flowability have significant impact on blending performance in a traditional batch process, continuous blending is more robust resulting in uniform blends for a large variety of blend compositions.

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Continuous mixing improves blend uniformity of pharmaceutical powder mixtures.

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Blend uniformity is highly dependent on excipient properties in a batch process.

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Continuous mixing is more robust, with little impact of material properties.

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Powder bulk density strongly affects blend homogeneity in a batch process.

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Blending of low API dosages is more challenging in a continuous process.

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.

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.

Challenges, opportunities and recent advances in near infrared spectroscopy applications for monitoring blend uniformity in the continuous manufacturing of solid oral dosage forms

Near infrared (NIR) spectroscopy has been widely recognized as a powerful PAT tool for monitoring blend uniformity in continuous manufacturing (CM) processes. However, the dynamic nature of the powder stream and the fast rate at which it moves, compared to batch processes, introduces challenges to NIR quantitative methods for monitoring blend uniformity. For instance, defining the effective sample size interrogated by NIR, selecting the best sampling location for blend monitoring, and ensuring NIR model robustness against influential sources of variability are challenges commonly reported for NIR applications in CM. This article reviews the NIR applications for powder blend monitoring in the continuous manufacturing of solid oral dosage forms, with a particular focus on the challenges, opportunities for method optimization and recent advances with respect three main aspects: effective sample size measured by NIR, probe location and method robustness.

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.

Quantitative analysis of blend uniformity within a Three-Chamber feed frame using simultaneously Raman and Near-Infrared spectroscopy

This study reports the use of Raman and Near-infrared (NIR) spectroscopy to simultaneously monitor the drug concentration in flowing powder blends within a three-chamber feed frame. The Raman probe was located at the top of the dosing chamber, while the NIR probe was located at the top of the filling chamber. The Raman and NIR spectra were continuously acquired while the powder blends flowed through the feed frame. Calibration models were developed with spectra from a total of five calibration blends ranging in caffeine concentration among 3.50 and 6.50% w/w. These models were optimized to predict three test set blends of 4.00, 5.00, and 6.00% w/w caffeine. The results showed a high predictive ability of the models based on root mean square error of predictions of 0.174 and 0.235% w/w for NIR and Raman spectroscopic models, respectively. Concentration profiles with higher variability were observed for the Raman spectroscopy predictions. An estimate of the mass analyzed by each spectrum showed that a NIR spectrum analyzes approximately 4.5 times the mass analyzed by a Raman spectrum; despite these differences in the mass analyzed, blend uniformity results are equivalent between techniques. Variographic analysis demonstrated that both techniques have significantly low sampling errors for the real-time monitoring process of drug concentration within the feed frame.

Blend Segregation in Tablets Manufacturing and Its Effect on Drug Content Uniformity-A Review

Content uniformity (CU) of the active pharmaceutical ingredient is a critical quality attribute of tablets as a dosage form, ensuring reproducible drug potency. Failure to meet the accepted uniformity in the final product may be caused either by suboptimal mixing and insufficient initial blend homogeneity, or may result from further particle segregation during storage, transfer or the compression process itself. This review presents the most relevant powder segregation mechanisms in tablet manufacturing and summarizes the currently available, up-to-date research on segregation and uniformity loss at the various stages of production process—the blend transfer from the bulk container to the tablet press, filling and discharge from the feeding hopper, as well as die filling. Formulation and processing factors affecting the occurrence of segregation and tablets’ CU are reviewed and recommendations for minimizing the risk of content uniformity failure in tablets are considered herein, including the perspective of continuous manufacturing.

Dry Powder Mixing Is Feasible in Continuous Twin Screw Extruder: Towards Lean Extrusion Process for Oral Solid Dosage Manufacturing

Using discrete element method (DEM) modeling and near-infrared (NIR) spectroscopy, the feasibility of powder mixing in the initial pre-melting zones of a twin screw extruder using two independent feeders was studied. Previous work in the pharmaceutical and food industry has focused on mixing when materials are melted or on material homogeneity at the extruder's output. Depending on the formulation, ensuring a fully blended formulation prior to melting may be desired. Experiments were conducted using a Coperion ZSK-18 extruder to evaluate if blend uniformity can be achieved by exploring screw configuration, screw speed, and powder feed rate. As powder exited the extruder and deposited on a conveyor belt, an in-line NIR spectrophotometer measured spectra of material. Chemometric-based models predicted unknown concentrations to evaluate if blend uniformity was achieved. Using the EDEM software, Hertz-Mindlin contact model, and dimensions of the extruder, DEM simulations complemented the experimental work. The DEM computational models provided understanding of mixing patterns inside the extruder at particle scale and helped select the screw configuration before doing experimentation. The simulations showed good axial mixing for all the screw configurations studied, while good cross (radial) mixing was only observed for the screw configuration with 90-degree kneading elements. Therefore, the screw configuration with two 90-degree kneading elements was chosen for the experimental study. The RTD profiles when using a screw configuration with only conveying screw elements are comparable to a plug flow reactor (PFR), while the profiles when using kneading elements are more comparable to an ideal continuous stirred tank reactor (CSTR). For the screw configuration with 90 degrees kneading elements, the mean residence time (MRT) decreases with an increase in the screw speed. Experimental NIR spectra showed that concentrations can be predicted with an error of 2%. It was demonstrated that the twin screw extruder can provide proper dry powder mixing of two powder feed streams based on a unit dose scale, enabling continuous powder mixing prior to the melting zone in the extruder for the formulation studied with a cohesive API. This setup may also work for other types of formulations. These studies can help in developing lean hot melt as well as wet extrusion/granulation processes using twin screw extruders for the continuous manufacturing of oral solid dosage products.

Performance assessment of linear iterative optimization technology (IOT) for Raman chemical mapping of pharmaceutical tablets

Raman chemical mapping is an inherently slow analysis tool. Accurate and robust multivariate analysis algorithms, which require least amount of time and effort in method development are desirable. Calibration-free regression and resolution approaches such as classical least squares (CLS) and multivariate curve resolution using alternating least squares (MCR-ALS), respectively, help in reducing the resources required for method development. However, conventional CLS does not consider appropriate constraints, which may result in negative and/or greater than 100 % Raman concentration scores, while MCR-ALS may not always be as accurate as regression-based algorithms. Linear iterative optimization technology (IOT) is another calibration-free algorithm, which with appropriate constraints has previously shown promise in online and offline pharmaceutical mixture composition determination. This paper aims to evaluate the performance of the linear IOT algorithm for Raman chemical mapping of the active pharmaceutical ingredient (API), diluent, and lubricant in pharmaceutical tablets. Two pre-processing strategies were applied to the raw Raman mapping spectra. The results were compared with CLS (current reference method) and MCR-ALS. Special emphasis was given to mapping at low Raman exposure times to enable feasible total acquisition times (< 5 h). The quality of IOT/CLS/MCR-ALS estimated Raman concentration predictions were assessed by calculating a correlation factor between the spectrum corresponding to the maximum predicted concentration (or resolved spectra) of a component for IOT/CLS (or MCR-ALS) and the pure powder component spectrum. The Raman chemical maps were visualized, and the average Raman concentrations scores were compared. The results demonstrated the utility of IOT in Raman chemical mapping of pharmaceutical tablets. The diluent (lactose) and API (semi-fine APAP) used in this study were reliably estimated by IOT at relatively short Raman exposure times. On the other hand, as expected, the lubricant (magnesium stearate) could not be detected in any of the cases investigated here, irrespective of the algorithm used. Overall, for the API and diluent used in this formulation as well as the chemical mapping conditions, linear IOT seemed to better estimate the pure spectrum intensities and the average Raman scores (closer to CLS) in comparison to MCR-ALS. Moreover, application of appropriate constraints in linear IOT avoided the presence of negative and/or greater than 100 % Raman concentration scores, as observed in CLS-based Raman chemical maps.

Streamlining of the Powder Mixing Process based on a Segregation Test

In direct compression of tablets, it is crucial to maintain content uniformity within acceptable margins, especially in formulations with low drug loading. To assure it, complex and multistep mixing processes are utilized in the industry. In this study, we suggest the use of a simple segregation test to evaluate mixing process performance and mixture segregation to produce tablets having satisfying content uniformity while keeping the process as simple and low cost as possible. Eventually, the formulation propensity to segregation can be evaluated using process analytical technology (PAT) to adjust the mixing process parameters to changing source drug properties. In this study, that approach was examined on a model drug with a broad batch-to-batch variability in particle size and shape. Excipients were chosen so that the resulting blend composition mimicked some marketed formulations. For each drug batch, two formulation blends were prepared through different preparation processes (one simple and one complex) and subsequently subjected to segregation tests. From those, segregation coefficients were obtained to compare segregation tendencies and homogeneity robustness between the drug batches and the blend preparation methods. The inter-particulate interactions were substantially influenced by the drug particle morphology and size and resulted in different segregation behavior. Based on these findings, a simple segregation test proved to be a useful tool for determining the suitability of different batches of the model drug to be used in a certain formulation. Moreover, for a particular batch A, the test revealed a potential for mixing process simplification and therefore process intensification and cost reduction.

Sampling optimization for blend monitoring of a low dose formulation in a tablet press feed frame using spatially resolved near-infrared spectroscopy

In-line measurements of low dose blends in the feed frame of a tablet press were performed for API concentration levels as low as 0.10% w/w. The proposed methodology utilizes the advanced sampling capabilities of a Spatially Resolved Near-Infrared (SR-NIR) probe to develop Partial Least-Squares calibration models. The fast acquisition speed of multipoint spectra allowed the evaluation of different numbers of co-adds and feed frame paddle speeds to establish the optimum conditions of data collection to predict low potency blends. The interaction of the feed frame paddles with the SR-NIR probe was captured with high resolution and allowed the implementation of a spectral data selection criterion to remove the effect of the paddles from the calibration and testing process. The method demonstrated accuracy and robustness when predicting drug concentrations across different feed frame paddle speeds.

Modular solid dosage form design - Application to pH-independent release of a weak-base API

A novel approach to solid dosage form design is investigated, whereby instead of blending the ingredients and subsequently compacting the mixture, the dosage form is made by assembling prefabricated components, each with a specific function. The approach was used to formulate a weak-base API (active pharmaceutical ingredient), such that the modular dosage forms exhibited pH-independent drug release. Tablet-like dosage forms of ciprofloxacin (CPR), used as model weak-base drug, were prepared in order to generate dosage forms exhibiting pH-independent drug release. The dosage forms were made by assembling two types of prefabricated modules onto 3D stacks. The modules were hydroxypropyl methylcellulose circular film wafers, loaded with either CPR or citric acid (CA). CA-wafers served the function of pH-modifier modules in the microenvironment of the dosage form during the dissolution process. In vitro drug release from dosage forms consisting of CA- and CPR-wafers stacked in alternate sequence was compared with the release from assemblies containing CPR-wafers only, under pH = 1.2 and pH = 6.8 conditions. In the absence of CA-wafers, CPR release was ~25-fold slower at pH = 6.8 compared to pH = 1.2. Inclusion of CA-wafers in the dosage form assembly accelerated and decelerated drug release at pH = 6.8 and pH = 1.2, respectively, which resulted in overlapping drug release profiles under the two pH conditions. The two drug release profiles met the criteria for sameness as assessed by the f₁ (difference) and f₂ (similarity) factors. Modeling of drug release kinetics pointed toward polymer erosion as the primary mechanism of drug release for the overlapping pH = 1.2 and pH = 6.8 profiles. In terms of their drug release properties, the multi-modular dosage form assemblies exhibited the attributes and behavior of single bodies, rather than the combined contributions from multiple individually-operating modules. The initial geometry of the dosage form, characterized by the surface area (SA), volume (V) and SA/V ratio accounted for drug release kinetics in the same fashion as for traditional tablet compacts.

Testing the Limits of a Portable NIR Spectrometer: Content Uniformity of Complex Powder Mixtures Followed by Calibration Transfer for In-Line Blend Monitoring

(1) Background: Portable NIR spectrometers gain more and more ground in the field of Process Analytical Technology due to the easy on-site flexibility and interfacing versatility. These advantages that originate from the instrument miniaturization, also come with a downside with respect to performance compared to benchtop devices. The objective of this work was to evaluate the performance of MicroNIR in a pharmaceutical powder blend application, having three active ingredients and 5 excipients. (2) Methods: Spectral data was recorded in reflectance mode using static and dynamic acquisition, on calibration set samples developed using an experimental design. (3) Results: The developed method accurately predicted the content uniformity of these complex mixtures, moreover it was validated in the entire calibration range using ±10% acceptance limits. With respect to at-line prediction, the method presented lower performance compared to a previously studied benchtop spectrometer. Regarding the in-line monitoring of the blending process, it was shown that the spectral variability-induced by dynamic acquisition could be efficiently managed using spectral pre-processing. (4) Conclusions: The in-line process monitoring resulted in accurate concentration profiles, highlighting differences in the mixing behaviour of the investigated ingredients. For the low dose component homogeneity was not reached due to an inefficient dispersive mixing.

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.

An innovative sampling interface for monitoring flowing pharmaceutical powder mixtures

A chute was designed following the principles of the Theory of Sampling to minimize the variations in powder flow and provide all particles in the flowing blends with the same opportunity of being selected as a sample. The design also reduces the thickness of the chute to allow the analysis of a higher portion of the flowing blends by a near infrared spectrometer. The blends that flowed through the chute had Carr's index values that fluctuated between 23 and 25 percent, indicating passable flowability. A powder fowling evaluation demonstrated that there was no powder accumulation at the inspection window of the chute. The mass flow rate profiles indicated that the system achieves mass steady-state in approximately 30 s and a throughput of 30 kg/h which makes it suitable for continuous manufacturing operations. An in-line NIR calibration model was developed to quantify caffeine concentrations between 1.51 and 4.52 % w/w. The spectra obtained from each experiment had minimal baseline variation. The developed NIR method was robust to throughput changes up to approximately ±7 %. The test blends in the caffeine concentration range between 2.02 % w/w and 4.02 % w/w met the dose uniformity requirements of the Ph.Eur. 9.0, chapter 2.9.47. Variographic analysis was done to estimate the analytical and sampling errors which yielded values below 0.01 (%w/w)². The obtained results showed that this chute could also be used in a continuous manufacturing line or other applications with flowing powders.

A near-infrared spectroscopy-based end-point determination method for the blending process of Dahuang soda tablets

OBJECTIVES

This study is aimed to explore the blending process of Dahuang soda tablets. These are composed of two active pharmaceutical ingredients (APIs, emodin and emodin methyl ether) and four kinds of excipients (sodium bicarbonate, starch, sucrose, and magnesium stearate). Also, the objective is to develop a more robust model to determine the blending end-point.

METHODS

Qualitative and quantitative methods based on near-infrared (NIR) spectroscopy were established to monitor the homogeneity of the powder during the blending process. A calibration set consisting of samples from 15 batches was used to develop two types of calibration models with the partial least squares regression (PLSR) method to explore the influence of density on the model robustness. The principal component analysis-moving block standard deviation (PCA-MBSD) method was used for the end-point determination of the blending with the process spectra.

RESULTS

The model with different densities showed better prediction performance and robustness than the model with fixed powder density. In addition, the blending end-points of APIs and excipients were inconsistent because of the differences in the physical properties and chemical contents among the materials of the design batches. For the complex systems of multi-components, using the PCA-MBSD method to determine the blending end-point of each component is difficult. In these conditions, a quantitative method is a more suitable alternative.

CONCLUSIONS

Our results demonstrated that the effect of density plays an important role in improving the performance of the model, and a robust modeling method has been developed.

Residence time distribution modelling and in line monitoring of drug concentration in a tablet press feed frame containing dead zones

The presence of a 'significant dead zone' in any continuous manufacturing equipment may affect the product quality and need to be investigated systematically. Dead zone will affect the residence time distribution (RTD) of continuous manufacturing and thus the mixing and product quality. Tablet press (feed frame) is one of unit operations that directly influence the critical quality attributes (CQA's). However, currently no systematic methods and tools are available to characterize and model the feed frame dead zone. In this manuscript, the RTD of the tablet press feed frame containing dead zone is investigated. Step-change experiments revealed that the feed frame could be expressed as a traditional continuous stirred tank model. The volume fractions of the dead zones are determined experimentally as well as using RTD model. In addition, an in-line NIR method for drug concentration monitoring inside the feed frame is also developed. The developed NIR calibration model enables to monitor the drug concentration precisely and detect the variation immediately with the probe positioned right above the left paddle. It is also found that the feed frame paddle speed slightly affects the predictive accuracy of NIR, while the die disc speed has no significant effect.

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current status of DT development and its application in pharmaceutical and biopharmaceutical manufacturing. State-of-the-art Process Analytical Technology (PAT) developments, process modeling approaches, and data integration studies are reviewed. Challenges and opportunities for future research in this field are also discussed.

The Comparison of Two Challenging Low Dose APIs in a Continuous Direct Compression Process

Segregation is a common problem in batch-based direct compression (BDC) processes, especially with low-dose tablet products, as is the preparation of a homogenous mixture. The scope of the current work was to explore if a continuous direct compression (CDC) process could serve as a solution for these challenges. Furthermore, the principle of a platform formulation was demonstrated for low dose tablets. The combination of filler excipients and the API in the formulation used was suitable for direct compression, but also prone to induce segregation in BDC process. The CDC process was found to be very promising; it was shown that tablets with the desired quality parameters could be manufactured successfully with both of the APIs studied. Powder analysis indicated that the APIs display some fundamental differences in their physical properties, which was also reflected in powder mixture properties and, hence, eventually in processing. However, process parameters, especially mixer impeller speed, were not found to have any significant influence on end product quality. The study suggests that a CDC process can be a viable solution to resolve the challenges described. Moreover, manufacturing by using a universal platform formulation seems to be a feasible way for producing low-dose tablets.

A sampling system for flowing powders based on the theory of sampling

An innovative chute and stream sampler system for flowing powders has been developed and tested. The system is designed for representative sampling based on the principles of the Theory of Sampling (TOS). The sampling system was used in combination with near infrared (NIR) spectroscopy to determine the drug concentration of flowing powders. The system is comprised of three parts: a chute, a stream sampler and a sample collection port. The NIR spectra were obtained at the chute, before entering the sampler, and as the powder flowed through the stream sampler. Samples were also collected from the sample collection port to be analyzed using an ultraviolet-visible (UV-Vis) reference method to determine drug content. A total of eight pharmaceutical powder blends, ranging in concentration from 10.5(%w/w) to 19.5(%w/w) of caffeine, were used to test the sampling system. Materials were characterized before blends were made to provide information on flow properties. The throughput of the system was between 30 and 35 kg/h based on the flow properties of the blend. Drug concentration was effectively determined at the chute and stream sampler. The NIR calibration models showed low root mean squared errors of prediction, 0.65(%w/w) and 0.51(%w/w), for the chute and stream sampler respectively. The NIR calibration models also showed low bias values -0.36(%w/w) at the chute and 0.057(%w/w) at the stream sampler. Significant agreement was obtained between the results from the nondestructive NIR versus the destructive UV-Vis method. Variographic analysis was performed to estimate the analytical and sampling errors when determining the drug concentration at the chute and stream sampler respectively. The variographic analysis showed low analytical errors, 0.103(%w/w)² and 0.181(%w/w)² at the chute and stream sampler respectively. The analysis also showed that the minimum practical error (MPE) was around 0.2(%w/w)² at both chute and stream sampler.

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.

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.