Recent progress in continuous manufacturing of oral solid dosage forms

Establishment of a semi-continuous nano-production line using the Microfluidizer® technology for the fabrication of lipid-based nanoparticles part 1: Screening of critical parameters and design of experiment optimization studies

A variety of strategies for producing high-quality nanoparticles have been reported in recent years. Batch-based bottom-up and top-down technologies are generally the most efficient methods, but present a number of challenges, particularly in terms of variability, safety, sustainability and large-scale production. In this study, a scalable, semi-continuous production line was built by connecting individual processing units, including a high shear mixing device, the Microfluidizer® technology and a cooling system. Each unit was equipped with an adequate temperature control to allow solvent-free production of solid lipid nanoparticles (consisting of Precirol® ATO 5 or Gelucire® 43/01) and nanostructured lipid carriers (additionally comprising Labrafac™ lipophile WL 1349). Subsequently, critical formulation parameters and critical process parameters (CPPs) of the individual processing units and their effects on particle size (i.e., critical quality attribute (CQA)) were investigated to identify appropriate input parameters for the subsequent Design of Experiment (DoE) studies conducted after linking the process units to a semi-continuous production line. For particle size monitoring, spatially resolved dynamic light scattering (SR-DLS) measurements were conducted and compared to standard DLS measurements to evaluate the applicability of SR-DLS as an inline monitoring tool. It was found that matrix composition, emulsifier concentration, pressure and number of cycles when processing through Microfluidizer® processor were the most influencing parameters. By optimizing these parameters, five-times higher throughputs could be achieved by the semi-continuous manufacturing line. In addition, the particle size measurements with SR-DLS confirmed the feasibility of implementing this technology for real-time particle size monitoring as an important safety factor in quality control.

Nutraceutical tablets: Manufacturing processes, quality assurance, and effects on human health

Consumers are increasingly focused on food products' nutritional content and health aspects. Nutraceutical tablets containing nutritional supplements have seen remarkable progress and are well-known for their precise dosage, which can improve consumer health by increasing the intake of bioactive compounds and vital nutrients. Oral nutraceuticals are frequently used to enhance consumer well-being, with around 80% of products being in solid form. This manuscript aims to thoroughly analyze and summarize the gathered literature using various search engines to investigate key trends in the market, the components involved, and the functional impact of nutraceutical tablets. Furthermore, the manuscript explores various nutraceutical tablets such as chewable tablets, gelling capsules, vitamin tablets, spirulina tablets, and bran tablets. A perspective is provided on multiple production and manufacturing methods of nutraceutical tablets, along with comparing these processes. Following this, evaluating quality characteristics and enforcing quality assurance procedures have been emphasized. The manuscript discussed the physiological breakdown of ingestible nutraceutical tablets in the human body and the possible toxic effects of the components found in these tablets. Furthermore, the focus is on producing nutraceutical tablets in a more environmentally friendly manner, tackling sustainability issues, offering solutions, and delving into potential opportunities. This manuscript will create a significant platform for people from the research, scientific, and industrial fields seeking novel and inventive projects.

Process intensification of pharmaceutical powder blending at commercial throughputs by utilizing semi-continuous mini-blending

Process intensification involves the miniaturization of equipment while retaining process throughput and performance. The pharmaceutical industry can benefit from this approach especially during drug product development, where the availability of active pharmaceutical ingredients (API) is often limited. It reduces the need for process scale up, as equipment used during product development and commercial production is identical. However, applications of process intensification for processing pharmaceutical powders are limited so far. Here we show that semi-continuous mini-blending can be utilized for process intensification of blending of API and excipients. Uniform blending at commercially relevant throughputs was achieved through mini-blends with a volume of less than ten liters. Our results demonstrate that blending speed, cycle time and blender fill level can be optimized without compromising blending performance. Acceptable blend uniformity is obtained over a broad range of operating parameters, by choosing the right excipients. The optimized throughput of the mini-blending process is in line with the desired throughput of a commercial Continuous Direct Compression (CDC) process.

Evaluating the Improvement of Blend Potency Measurements in the Feed Frame of a Rotary Tablet Press Using Combined NIR and Raman Spectroscopy

This study investigated the added value of combining both near-infrared (NIR) and Raman spectroscopy into a single NIRaman Combi Fiber Probe for in-line blend potency determination in the feed frame of a rotary tablet press. A five-component platform formulation was used, containing acetylsalicylic acid as the Active Pharmaceutical Ingredient (API). Calibration models for the determination of 1 and 5%w/w label claim tablets were developed using NIR and Raman spectra of powder blends ranging from 0.75 to 1.25%w/w and 3.75 to 6.25%w/w API, respectively. Step-change experiments with deliberate 10% deviation steps from the label claims were performed, from which the collected spectra were used for model validation. For model development and validation, low-level data fusion was explored through concatenation of preprocessed NIR and Raman spectra. Mid-level data fusion was also evaluated, based on extracted features of the preprocessed data. Herewith, score vectors were extracted by transforming preprocessed spectra through Principal Component Analysis, followed by critical feature selection through Elastic Net Regression. Partial Least Squares regression was applied to regress singular, low-level or mid-level fused data versus blend potency. It could be concluded that irrespective of the data fusion technique, an increase in Step-Change Sensitivity (SCS) and decrease in Root Mean Squared Error (RMSE) was observed when predicting the 5%w/w step-change experiment. For the prediction of the 1%w/w step-change experiment, no added benefit with regard to SCS and RMSE was observed due to the addition of the noisy NIR spectra.

A framework for the in silico assessment of the robustness of an MPC in a CDC line in function of process variability

The shift from batch manufacturing towards continuous manufacturing for the production of oral solid dosages requires the development and implementation of process models and process control. Previous work focused mainly on developing deterministic models for the investigated system. Furthermore, the in silico tuning and analysis of a control strategy are mostly done based on deterministic models. This deterministic approach could lead to wrong actions in diversion strategies and poor transferability of the controller performance if the system behaves differently than the deterministic model. This work introduces a framework that explicitly includes the process variability which is characteristic of powder handling processes and tests it on a novel continuous feeding-blending unit (i.e., the FE continuous processing system (CPS)), followed by a tablet press (i.e., the FE 55). It employs a stochastic model by allowing the model parameters to have a probability distribution. The performance of a model predictive control (MPC), steering the feed rate of the main excipient feeder to compensate for the feed rate deviations of the active pharmaceutical ingredient (API) feeder to keep the API concentration close to the desired value, is evaluated and the impact of process variability is assessed in a Monte Carlo (MC) analysis. Next to the process variability, a model for the prediction error of the chemometric model and realistic feed rate disturbances were included to increase the transferability of the results to the real system. The obtained results show that process variability is inherently present and that wrong conclusions can be drawn if it is not taken into account in the in silico analysis.

Ten years of the manufacturing classification system: a review of literature applications and an extension of the framework to continuous manufacture

The MCS initiative was first introduced in 2013. Since then, two MCS papers have been published: the first proposing a structured approach to consider the impact of drug substance physical properties on manufacturability and the second outlining real world examples of MCS principles. By 2023, both publications had been extensively cited by over 240 publications. This article firstly reviews this citing work and considers how the MCS concepts have been received and are being applied. Secondly, we will extend the MCS framework to continuous manufacture. The review structure follows the flow of drug product development focussing first on optimisation of API properties. The exploitation of links between API particle properties and manufacturability using large datasets seems particularly promising. Subsequently, applications of the MCS for formulation design include a detailed look at the impact of percolation threshold, the role of excipients and how other classification systems can be of assistance. The final review section focusses on manufacturing process development, covering the impact of strain rate sensitivity and modelling applications. The second part of the paper focuses on continuous processing proposing a parallel MCS framework alongside the existing batch manufacturing guidance. Specifically, we propose that continuous direct compression can accommodate a wider range of API properties compared to its batch equivalent.

Statistical data treatment for residence time distribution studies in pharmaceutical manufacturing

Residence time distribution (RTD) method has been widely used in the pharmaceutical manufacturing for understanding powder dynamics within unit operations and continuous integrated manufacturing lines. The dynamics thus captured is then used to develop predictive models for unit operations and important RTD-based applications ensuring product quality assurance. Despite thorough efforts in tracer selection, data acquisition, and calibration model development to obtain tracer concentration profiles for RTD studies, there can exist significant noise in these profiles. This noise can make it challenging to identify the underlying signal and get a representative RTD of the system under study. Such concerns have previously indicated the importance of noise handling for RTD measurements in literature. However, the literature does not provide sufficient information on noise handling or data treatment strategies for RTD studies. To this end, we investigate the impact of varying levels of noise using different tracers on measurement of RTD profile and its applications. We quantify the impact of different denoising methods (time and frequency averaging methods). Through this investigation, we see that Savitsky Golay filtering turns out to a good method for denoising RTD profiles despite varying noise levels. The investigation is performed such that the key features of the RTD profile (which are important for RTD based applications) are preserved. Subsequently, we also investigate the impact of denoising on RTD-based applications such as out-of-specification (OOS) analysis and RTD modeling. The results show that the degree of noise levels considered in this work do not significantly impact the RTD-based applications.

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.

Manufacturing process transfer to a 30 kg/h continuous direct compression line with real-time composition monitoring

Transferring an existing marketed pharmaceutical product from batch to continuous manufacturing (CM) without changes in regulatory registration is a challenging task in the pharmaceutical industry. Continuous manufacturing can provide an increased production rate and better equipment utilisation while retaining key quality attributes of the final product. Continuous manufacturing necessitates the monitoring of critical quality attributes in real time by appropriate process analytical tools such as near infra-red (NIR) probes. The present work reports a successful transfer of an existing drug product from batch to continuous manufacturing process without changing the formulation. A key step was continuous powder blending, whose design and operating parameters including weir type, agitation rate, dynamic hold-up and residence time were systematically investigated with respect to process repeatability. A NIR-based multivariate data model for in-line composition monitoring has been developed and validated against an existing quality control method for measuring tablet content uniformity. A continuous manufacturing long-run with a throughput of 30 kg/h (approx. 128,000 tablets per hour), uninterrupted for 320 min, has been performed to test and validate the multivariate data model as well as the batch to continuous process transfer. The final disintegration and dissolution properties of tablets manufactured by the continuous process were found to be equivalent to those manufactured by the original batch process.

Machine learning modeling for ultrasonic quality attribute assessment of pharmaceutical tablets for continuous manufacturing and real-time release testing

In in-process quality monitoring for Continuous Manufacturing (CM) and Critical Quality Attributes (CQA) assessment for Real-time Release (RTR) testing, ultrasonic characterization is a critical technology for its direct, non-invasive, rapid, and cost-effective nature. In quality evaluation with ultrasound, relating a pharmaceutical tablet's ultrasonic response to its defect state and quality parameters is essential. However, ultrasonic CQA characterization requires a robust mathematical model, which cannot be obtained with traditional first principles-based modeling approaches. Machine Learning (ML) using experimental data is emerging as a critical analytical tool for overcoming such modeling challenges. In this work, a novel Deep Neural Network-based ML-driven Non-Destructive Evaluation (ML-NDE) modeling framework is developed, and its effectiveness for extracting and predicting three CQAs, namely defect states, compression force levels, and amounts of disintegrant, is demonstrated. Using a robotic tablet handling experimental rig, each attribute's distinct waveform dataset was acquired and utilized for training, validating, and testing the respective ML models. This study details an advanced algorithmic quality assessment framework for pharmaceutical CM in which automated RTR testing is expected to be critical in developing cost-effective in-process real-time monitoring systems. The presented ML-NDE approach has demonstrated its effectiveness through evaluations with separate (unused) test datasets.

Reviewing the process intensification landscape through the introduction of a novel, multitiered classification for downstream processing

A demand for process intensification in biomanufacturing has increased over the past decade due to the ever-expanding market for biopharmaceuticals. This is largely driven by factors such as a surge in biosimilars as patents expire, an aging population, and a rise in chronic diseases. With these market demands, pressure upon biomanufacturers to produce quality products with rapid turnaround escalates proportionally. Process intensification in biomanufacturing has been well received and accepted across industry based on the demonstration of its benefits of improved productivity and efficiency, while also reducing the cost of goods. However, while these benefits have been shown empirically, the challenges of adopting process intensification into industry remain, from smaller independent start-up to big pharma. Traditionally, moving from batch to a process intensification scheme has been viewed as an "all or nothing" approach involving continuous bioprocessing, in which the factors of complexity and significant capital costs hinder its adoption. In addition, the literature is crowded with a variety of terms used to describe process intensification (continuous, periodic counter-current, connected, intensified, steady-state, etc.). Often, these terms are used inappropriately or as synonyms, which generates confusion in the field. Through a detailed review of current state-of-the-art systems, consumables, and process intensification case studies, we herein propose a defined approach in the implementation of downstream process intensification through a standardized nomenclature and viewing it as distinct independent levels. These can function separately as intensified single-unit operations or be built upon by integration with other process steps allowing for simple, incremental, cost-effective implementation of process intensification in the manufacturing of biopharmaceuticals.

Liquid API feeding in pharmaceutical HME: Novel options in solid dosage manufacturing

Hot melt extrusion (HME) is a common unit operation. It is broadly applicable in the pharmaceutical industry and can be implemented in a continuous manufacturing line. However, the conventional way of active pharmaceutical ingredient (API) feeding with a pre-blend consisting of a powdered API and a polymer does not allow the flexibility and agility to adjust the process parameters, which is generally an essential part of continuous manufacturing. In addition, this method of API feeding may result in the segregation of the individual powder components or agglomeration of highly cohesive materials, leading to an inhomogeneous API content in the extrudates, especially at low doses. In this study, the universal applicability of liquid side feeding in pharmaceutical HME was demonstrated using various APIs suspended or dissolved in water and fed as suspension or undersaturated, supersaturated, and highly concentrated solutions into anterior parts of the extruder. The extrudates were characterized in terms of their API content, residual moisture content, and solid-state of the API embedded in the polymer. The results show that a uniform API content without major deviations can be obtained via this method. Furthermore, the residual moisture content of the extrudates was low enough to have no significant influence on further processing of the final dosage form. In summary, this advanced way of feeding allows an accurate, flexible, and agile feeding of APIs, facilitating the production of personalized final dosage forms and a novel option to link the manufacturing of the drug substance and the drug product.

A case study on decentralized manufacturing of 3D printed medicines

Pharmaceutical 3D printing (3DP) is one of the emerging enabling technologies of personalised medicines as it affords the ability to fabricate highly versatile dosage forms. In the past 2 years, national medicines regulatory authorities have held consultations with external stakeholders to adapt regulatory frameworks to embrace point-of-care manufacturing. The proposed concept of decentralized manufacturing (DM) involves the provision of feedstock intermediates (pharma-inks) prepared by pharmaceutical companies to DM sites for manufacturing into the final medicine. In this study, we examine the feasibility of this model, with respect to both manufacturing and quality control. Efavirenz-loaded granulates (0-35%w/w) were produced by a manufacturing partner and shipped to a 3DP site in a different country. Direct powder extrusion (DPE) 3DP was subsequently used to prepare printlets (3D printed tablets), with mass ranging 266-371 mg. All printlets released more than 80% drug load within the first 60 min of the in vitro drug release test. An in-line near-infrared spectroscopy system was used as a process analytical technology (PAT) to quantify the printlets' drug load. Calibration models were developed using partial least squares regression, which showed excellent linearity (R² = 0.9833) and accuracy (RMSE = 1.0662). Overall, this work is the first to report the use of an in-line NIR system to perform real-time analysis of printlets prepared using pharma-inks produced by a pharmaceutical company. By demonstrating the feasibility of the proposed distribution model through this proof-of-concept study, this work paves the way for investigation of further PAT tools for quality control in 3DP point-of-care manufacturing.

Machine learning framework for extracting micro-viscoelastic and micro-structural properties of compressed oral solid dosage forms

A compressed pharmaceutical oral solid dosage (OSD) form is a strongly micro-viscoelastic material composite arranged as a network of agglomerated particles due to its constituent powders and their bonding and fractural mechanical properties. An OSD product's Critical Quality Attributes, such as disintegration, drug release (dissolution) profile, and structural strength ("hardness"), are influenced by its micro-scale properties. Ultrasonic evaluation is direct, non-destructive, rapid, and cost-effective. However, for practical process control applications, the simultaneous extraction of the micro-viscoelastic and scattering properties from a tablet's ultrasonic response requires a unique solution to a challenging inverse mathematical wave propagation problem. While the spatial progression of a pulse traveling in a composite medium with known micro-scale properties is a straightforward computational task when its dispersion relation is known, extracting such properties from the experimentally acquired waveforms is often non-trivial. In this work, a novel Machine Learning (ML)-based micro-property extraction technique directly from waveforms, based on Multi-Output Regression models and Neural Networks, is introduced and demonstrated. Synthetic waveforms with a given set of micro-properties of virtual tablets are computationally generated to train, validate, and test the developed ML models for their effectiveness in the inverse problem of recovering specified micro-scale properties. The effectiveness of these ML models is then tested and demonstrated for a set of physical OSD tablets. The micro-viscoelastic and micro-structural properties of physical tablets with known properties have been extracted through experimentally acquired waveforms to exhibit their consistency with the generated ML-based attenuation results.

Leveraging a multivariate approach towards enhanced development of direct compression extended release tablets

Extended release formulations play a crucial role in the pharmaceutical industry by maintaining steady plasma levels, reducing side effects, and improving therapeutic efficiency and compliance. One commonly used method to develop extended release formulations is direct compression, which offers several advantages, such as simplicity, time savings, and cost-effectiveness. However, successful direct compression-based extended release formulations require careful assessment and an understanding of the excipients' attributes. The scope of this work is the characterization of the compaction behavior of some matrix-forming agents and diluents for the development of extended release tablets. Fifteen excipients commonly used in extended release formulations were evaluated for physical, compaction and tablet properties. Powder properties (e.g., particle size, flow properties, bulk density) were evaluated and linked to the tablet's mechanical properties in a fully integrated approach, and data were analyzed by constructing a principal component analysis (PCA). Significant variability was observed among the various excipients. The present work successfully demonstrates the applicability of PCA as an effective tool for comparative analysis, pattern and clustering recognition and correlations between excipients and their properties, facilitating the development and manufacturing of direct compressible extended release formulations.

Application of Positron Emission Particle Tracking (PEPT) for the evaluation of powder behaviour in an incline linear blender for Continuous Direct Compression (CDC)

Positron Emission Particle Tracking (PEPT) is a non-invasive measurement technique which offers the ability to track the motion of individual particles with high temporal and spatial resolution, and thus build up an understanding of the bulk behaviour of a system from its microscopic (particle level) dynamics. Using this measurement technique, we have developed a series of novel metrics to better understand the behaviours of powders during the steady-state operation of a continuous blender system. Results are presented concerning the response of particle motion to processing parameters (mixing blade configuration and RPM), quantifying the motion in terms of predicted mixing performance. It was found that both increasing rpm and increasing hold-up mass (by selecting fewer transport blades and more mixing blades) provided improved mixing conditions. Interestingly, under specific conditions, there is evidence of convection-like mixing occurring at the interface of the transport and mixing region. This suggests the existence of a potential 'folding region' whereby powder is transported up the barrel (and away from the powder bulk bed) before being reconstituted back into the bulk mass. The results also provide valuable experimental data for the development, calibration and validation of future Discrete Element Method (DEM) simulations.

An adaptive modeling approach using spiking-augmentation method to improve chemometric model performance in bioprocess monitoring

Intensified and continuous processes require fast and robust methods and technologies to monitor product titer for faster analytical turnaround time, process monitoring, and process control. The current titer measurements are mostly offline chromatography-based methods which may take hours or even days to get the results back from the analytical labs. Thus, offline methods will not meet the requirement of real time titer measurements for continuous production and capture processes. FTIR and chemometric based multivariate modeling are promising tools for real time titer monitoring in clarified bulk (CB) harvests and perfusate lines. However, empirical models are known to be vulnerable to unseen variability, specifically a FTIR chemometric titer model trained on a given biological molecule and process conditions often fails to provide accurate predictions of titer in another molecule under different process conditions. In this study, we developed an adaptive modeling strategy: the model was initially built using a calibration set of available perfusate and CB samples and then updated by augmenting spiking samples of the new molecules to the calibration set to make the model robust against perfusate or CB harvest of the new molecule. This strategy substantially improved the model performance and significantly reduced the modeling effort for new molecules.

Can Continuous Manufacturing of Topical Semisolids by Hot Melt Extrusion Soon Be a Reality?

For more than five decades, pharmaceutical manufacturers have been relying heavily on batch manufacturing that is a sequential, multistep, laborious, and time-consuming process. However, late advances in manufacturing technologies have prompted manufacturers to consider continuous manufacturing (CM) is a feasible manufacturing process that encompasses fewer steps and is less tedious and quick. Global regulatory agencies are taking a proactive role to facilitate pharmaceutical industries to adopt CM that assures product quality by employing robust manufacturing technologies encountering fewer interruptions, thereby substantially reducing product failures and recalls. However, adopting innovative CM is known to pose technical and regulatory challenges. Hot melt extrusion (HME) is one such state-of-the-art enabling technology that facilitates CM of diverse pharmaceutical dosage forms, including topical semisolids. Efforts have been made to continuously manufacture semisolids by HME integrating the principles of Quality by Design (QbD) and Quality Risk Management (QRM) and deploying Process Analytical Technologies (PAT) tools. Attempts have been made to systematically elucidate the effect of critical material attributes (CMA) and critical process parameters (CPP) on product critical quality attributes (CQA) and Quality Target Product Profiles (QTPP) deploying PAT tools. The article critically reviews the feasibility of one of the enabling technologies such as HME in CM of topical semisolids. The review highlights the benefits of the CM process and challenges ahead to implement the technology to topical semisolids. Once the CM of semisolids adopting melt extrusion integrated with PAT tools becomes a reality, the process can be extended to manufacture sterile semisolids that usually involve more critical processing steps.

Evaluation of the influence of material properties and process parameters on granule porosity in twin-screw wet granulation

In recent years, continuous twin-screw wet granulation (TSWG) is gaining increasing interest from the pharmaceutical industry. Despite the many publications on TSWG, only a limited number of studies focused on granule porosity, which was found to be an important granule property affecting the final tablet quality attributes, e.g. dissolution. In current study, the granule porosity along the length of the twin-screw granulator (TSG) barrel was evaluated. An experimental set-up was used allowing the collection of granules at the different TSG compartments. The effect of active pharmaceutical ingredient (API) properties on granule porosity was evaluated by using six formulations with a fixed composition but containing APIs with different physical-chemical properties. Furthermore, the importance of TSWG process parameters liquid-to-solid (L/S) ratio, mass feed rate and screw speed for the granule porosity was evaluated. Several water-related properties as well as particle size, density and flow properties of the API were found to have an important effect on granule porosity. While the L/S ratio was confirmed to be the dictating TSWG process parameter, granulator screw speed was also found to be an important process variable affecting granule porosity. This study obtained crucial information on the effect of material properties and process parameters on granule porosity (and granule formation) which can be used to accelerate TSWG process and formulation development.

Flowsheet modelling of a powder continuous feeder-mixer system

In this study, an integrated flowsheet model of the continuous feeder-mixer system was calibrated, simulated and compared against experimental data. The feeding process was first investigated using two major components (ibuprofen and microcrystalline cellulose (MCC)), in a formulation comprised of: 30 wt% of ibuprofen, 67.5 wt% MCC, 2 wt% of sodium starch glycolate and 0.5 wt% of magnesium stearate. The impact of a refill on feeder performance was experimentally evaluated for different operating conditions. Results showed that it had no influence on feeder performance. While simulations with the feeder model fairly reproduced the material behaviour observed in the feeder, unintended disturbances were underpredicted due to the model's low complexity. Experimentally, mixer's efficiency was assessed based on ibuprofen residence time distribution. Mean residence time pointed to a higher mixer's efficiency at lower flow rates. Blend homogeneity results showed that for the entire set of experiments, ibuprofen RSD <5%, irrespective of process variables. A feeder-mixer flowsheet model was calibrated, after regressing the axial model coefficients. The regression curves exhibited a R² above 0.96, whereas the RMSE varied from 1.58x10^-4 to 1.06x10^-3 s^-1 across all fitted curves. Simulations confirmed that flowsheet model captured the powder dynamics inside the mixer and qualitatively predicted the mixer's filtering ability against feeding composition fluctuations, as well as ibuprofen RSD in blend, in line with real experiments.

Steady-state modeling of a new continuous API dryer: Reduced-order model and investigation of dryer performance

In the present study, a reduced-order model is proposed to analyze a novel continuous dryer with an application in the pharmaceutical industry. The model was validated using process data from ibuprofen drying test runs, and the results were in good agreement with the experimental data. The test substance was an ibuprofen paste with an initial LOD of up to 30 w%. The simulations showed that the contact heat transfer coefficient can be correlated with the degree of wetness. Furthermore, a set of simulations was performed to analyze the influence of input parameters on the dryer's performance: i) the inlet air flow rate and ii) the inlet air temperature. The simulation results demonstrated that a variation in the inlet air temperature significantly affects the air temperature profile, while the inlet air flow rate has a minor effect. Besides, it was also established that the inlet solid LoD has the most considerable effect on the product quality (e.g., final solid moisture content). The results showed a deviation of less than 10% for the product LoD and the product temperature in most cases.

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.

Continuous Manufacturing of Oil in Water (O/W) Emulgel by Extrusion Process

Pharmaceutical industries and drug regulatory agencies are inclining towards continuous manufacturing due to better control over the processing conditions and in view to improve product quality. In the present work, continuous manufacturing of O/W emulgel by melt extrusion process was explored using lidocaine as an active pharmaceutical ingredient. Emulgel was characterized for pH, water activity, globule size distribution, and in vitro release rate. Additionally, effect of temperature (25°C and 60°C) and screw speed (100, 300, and 600 rpm) on the globule size and in vitro release rate was studied. Results indicated that at a given temperature, emulgel prepared under screw speed of 300 rpm resulted in products with smaller globules and faster drug release.

Natural Alternatives to Non-biodegradable Polymers in 3D Printing of Pharmaceuticals

BACKGROUND

Due to potential toxicity, non-biodegradable polymers used in 3D (3-dimensional) printing of drugs could be dangerous for patient safety and the environment.

OBJECTIVE

This review aims to investigate the toxicity of non-biodegradable polymers and investigate the use of natural materials as an alternative in 3D printing medicines. The study evaluates the dangers connected to 3D printing.

METHODS

A review of the literature on various 3D printing processes, such as inkjet printing, fused filament manufacturing, and extrusion-related 3DP systems, was done for this study. Also, the use of cellulose derivatives and natural materials in 3D printing and their potential as active excipients was proposed.

RESULTS

The review identified potential toxicity risks linked to non-biodegradable polymers used in drug 3D printing. As a potential fix for this issue, the use of natural materials with improved mechanical and thermal properties was explored. The use of cellulose derivatives as an alternative to non-biodegradable polymers in 3D printing pharmaceuticals was also investigated in the study.

CONCLUSION

This study emphasises the significance of evaluating the risks connected to drug 3D printing and recommends using natural materials as an alternative to non-biodegradable polymers. More study is required to create secure and reliable 3D printing processes for pharmaceuticals.

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.

Continuous integrated production of glucose granules with enhanced flowability and tabletability

Glucose is widely used in both the food and pharmaceutical industry. However, the application of industrially crystallized glucose in solid dosage forms is challenged by its poor flowability and tabletability. To improve these characteristics continuous twin-screw granulation was tested, which has the potential to be integrated into the continuous production of solid glucose from corn starch. A completely continuous manufacturing line (including drying and milling) was developed and the different production steps were examined and synchronized. Our line was supplemented with an in-line applicable near-infrared spectroscopic probe to monitor the moisture content of the milled granules in real-time. The flowability and tabletability of the powder improved significantly, and tablets with acceptable breaking force (greater than 100 N) could be prepared from the granules. The developed continuous line can be easily installed into the industrial solid glucose production process resulting in pure glucose granules with adequate flow properties and tabletability in a simple, continuous and efficient way.

Model-Guided Development of a Semi-Continuous Drying Process

INTRODUCTION

With an increased adoption of continuous manufacturing for pharmaceutical production, the ConsiGma® CTL25 wet granulation and tableting line has reached widespread use. In addition to the continuous granulation step, the semi-continuous six-segmented fluid bed dryer is a key unit in the line. The dryer is expected to have an even distribution of the inlet air between the six drying cells. However, process observations during manufacturing runs showed a repeatable pattern in drying time, which suggests a variability in the drying performance between the different cells of the dryer. The aim of this work is to understand the root-cause of this variability.

MATERIALS AND METHODS

In a first step, the variability in the air temperature and air flow velocity between the dryer cells was measured on an empty dryer. In a second step, the experimental data were interpreted with the help of results from computational fluid dynamics (CFD) simulations to better understand the reasons for the observed variability.

RESULTS

The CFD simulations were used to identify one cause of the measured difference in the air temperature, showing the impact of the air inlet design on the temperature distribution in the dryer.

CONCLUSIONS

Although the simulation could not predict the exact temperature, the trend was similar to the experimental observations, demonstrating the added value of this type of simulation to guide process development, engineering decisions and troubleshoot equipment performance variability.

Control strategy definition for a drug product continuous wet granulation process: Industrial case study

This paper describes the specific control strategy of the commercial manufacturing process of an immediate release tablet formulation based on continuous twin-screw wet granulation. This control strategy has been defined by a multidisciplinary team using an enhanced approach, in alignment with the quality by design principles. During process development, experiments have been performed according to multivariate designs first to identify critical material attributes and critical process parameters and then, to define process conditions generating a product having the required quality. Hence, controls have been applied on critical quality attributes and on related critical process parameters and critical material attributes. Due to the specificity of the process that combines batch and continuous unit operations, a specific control strategy has been designed to ensure intermediate and end product quality. Therefore, controls including soft sensor model and in process controls have been developed to continuously monitor granules residual moisture content, assay and dissolution as granules and tablets critical attributes. In addition, process analytical technology implementation enabled increased process understanding and provided support for the development of the control strategy. This study is therefore considered as a real industrial case study of control strategy definition and implementation for an intended commercial continuous manufacturing process.

Tracking raw material flow through a continuous direct compression line Part I of II: Residence time distribution modeling and sensitivity analysis enabling increased process yield

Continuous manufacturing (CM) offers advantages in quality and space-time yield compared to common batch manufacturing. However, higher yield losses due to the start-up procedure make a broad application uneconomical. This work discusses the possibility of reducing yield losses by adjusting the degree of back-mixing. Back-mixing of nonconforming material from disturbances or start-up will result in the contamination of subsequent material. Therefore, higher degrees of back-mixing cause the discharge of additional material. Choosing an advantageous setting of operational parameters may be a simple way to change the degree of back-mixing. Based on direct compression, this work demonstrates the identification of promising parameters. Therefore, step-change experiments using color-marked material in the feeder, blender, and tablet press quantify the impact of three operational parameters per device. Models for the devices and the entire process result from those measurements. Subsequently, a global variance-based sensitivity analysis identifies the most influential parameters. As a result, adjusting the minimal filling level of the feeder and the rotational feed frame speed of the tablet press reduces back-mixing by more than 30%. At high costs of the raw materials, the resulting savings can significantly improve the economic performance of CM compared to batch manufacturing.

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.

The Effect of Binder Types on the Breakage and Drying Behavior of Granules in a Semi-Continuous Fluid Bed Dryer after Twin Screw Wet Granulation

Current study investigated the effect of different binder types on the granule drying process and the granule breakage behavior in a semi-continuous fluid bed dryer integrated in the C25 ConsiGma-system. The studied binders (i.e. hydroxypropyl pea starch, hydroxypropyl methylcellulose E15, polyvinylpyrrolidone K12, and starch octenyl succinate CO 01) required different liquid amounts to produce similar granule quality. These different liquid requirements were translated into different drying conditions for each binder to result in sufficiently dry granules at the end of a drying cycle. By comparing the size distribution of the granules before entering and after exiting the fluid bed dryer, granule breakage could be evaluated. No effect of the binder type on the granule breakage during drying was observed. However, differences in granule breakage were observed for the binders when processed with the horizontal set-up of the C25 system, as granule breakage during pneumatic transport depended on the binder type. Only one binder (hydroxypropyl pea starch) allowed to avoid granule breakage during the entire process. Furthermore, this research showed that the drying process was mainly steered by the liquid requirements for granulation, and that these liquid requirements depended on the binder used.

Impedance Spectroscopy Sensing Material Properties for Self-Tuning Ratio Control in Pharmaceutical Industry

Following the paradigm shift in the pharmaceutical industry from batch to continuous production, additional instrumentation and revision of control strategies to optimize material flow throughout the downstream processes are required. Tableting manufacturing is one of the most productive in terms of turnover and investment into new sensor technologies is an important decision-making step. This paper proposes a continuous solution to detect changes in material properties, and a control algorithm to aid in minimizing risk at the end-product line. Some of the sub-processes involved in tableting manufacturing perform changes in powder and liquid mixtures, granulation, density, therefore changing flow conditions of the raw material. Using impedance spectroscopy in a continuous sensing and monitoring context, it is possible to perform online identification of generalized (fractional) order parametric models where the coefficients are correlated to changes in material properties. The model parameters are then included in a self-tuning control gain used in ratio control as part of the local process control loop. The solution proposed here is easy to implement and poses a significant added value to the current state of art in pharmaceutical manufacturing technologies.

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.

Using residence time distribution in pharmaceutical solid dose manufacturing - A critical review

While continuous manufacturing (CM) of pharmaceutical solid-based drug products has been shown to be advantageous for improving the product quality and process efficiency in alignment with FDA's support of the quality-by-design paradigm (Lee, 2015; Ierapetritou et al., 2016; Plumb, 2005; Schaber, 2011), it is critical to enable full utilization of CM technology for robust production and commercialization (Schaber, 2011; Byrn, 2015). To do so, an important prerequisite is to obtain a detailed understanding of overall process characteristics to develop cost-effective and accurate predictive models for unit operations and process flowsheets. These models are utilized to predict product quality and maintain desired manufacturing efficiency (Ierapetritou et al., 2016). Residence time distribution (RTD) has been a widely used tool to characterize the extent of mixing in pharmaceutical unit operations (Vanhoorne, 2020; Rogers and Ierapetritou, 2015; Teżyk et al., 2015) and manufacturing lines and develop computationally cheap predictive models. These models developed using RTD have been demonstrated to be crucial for various flowsheet applications (Kruisz, 2017; Martinetz, 2018; Tian, 2021). Though extensively used in the literature (Gao et al., 2012), the implementation, execution, evaluation, and assessment of RTD studies has not been standardized by regulatory agencies and can thus lead to ambiguity regarding their accurate implementation. To address this issue and subsequently prevent unforeseen errors in RTD implementation, the presented article aims to aid in developing standardized guidelines through a detailed review and critical discussion of RTD studies in the pharmaceutical manufacturing literature. The review article is divided into two main sections - 1) determination of RTD including different steps for RTD evaluation including experimental approach, data acquisition and pre-treatment, RTD modeling, and RTD metrics and, 2) applications of RTD for solid dose manufacturing. Critical considerations, pertaining to the limitations of RTDs for solid dose manufacturing, are also examined along with a perspective discussion of future avenues of improvement.

Metamorphosis of Twin Screw Extruder-Based Granulation Technology: Applications Focusing on Its Impact on Conventional Granulation Technology

In order to be at pace with the market requirements of solid dosage forms and regulatory standards, a transformation towards systematic processing using continuous manufacturing (CM) and automated model-based control is being thought through for its fundamental advantages over conventional batch manufacturing. CM eliminates the key gaps through the integration of various processes while preserving quality attributes via the use of process analytical technology (PAT). The twin screw extruder (TSE) is one such equipment adopted by the pharmaceutical industry as a substitute for the traditional batch granulation process. Various types of granulation techniques using twin screw extrusion technology have been explored in the article. Furthermore, individual components of a TSE and their conjugation with PAT tools and the advancements and applications in the field of nutraceuticals and nanotechnology have also been discussed. Thus, the future of granulation lies on the shoulders of continuous TSE, where it can be coupled with computational mathematical studies to mitigate its complications.

Analysis of the Effects of Process Parameters on Start-Up Operation in Continuous Wet Granulation

Toward further implementation of continuous tablet manufacturing, one key issue is the time needed for start-up operation because it could lead to lower product yield and reduced economic performance. The behavior of the start-up operation is not well understood; moreover, the definition of the start-up time is still unclear. This work investigates the effects of process parameters on the start-up operation in continuous wet granulation, which is a critical unit operation in solid drug manufacturing. The profiles of torque and granule size distribution were monitored and measured for the first hour of operation, including the start-up phase. We analyzed the impact of process parameters based on design of experiments and performed an economic assessment to see the effects of the start-up operation. The torque profiles indicated that liquid-to-solid ratio and screw speed would affect the start-up operation, whereas different start-up behavior resulted in different granule size. Depending on the indicator used to define the start-up operation, the economic optimal point was significantly different. The results of this study stress that the start-up time differs according to the process parameters and used definition, e.g., indicators and criteria. This aspect should be considered for the further study and regulation of continuous manufacturing.

Review: Continuous Manufacturing of Small Molecule Solid Oral Dosage Forms

Continuous manufacturing (CM) is defined as a process in which the input material(s) are continuously fed into and transformed, and the processed output materials are continuously removed from the system. CM can be considered as matching the FDA's so-called 'Desired State' of pharmaceutical manufacturing in the twenty-first century as discussed in their 2004 publication on 'Innovation and Continuous Improvement in Pharmaceutical Manufacturing'. Yet, focused attention on CM did not really start until 2014, and the first product manufactured by CM was only approved in 2015. This review describes some of the benefits and challenges of introducing a CM process with a particular focus on small molecule solid oral dosage forms. The review is a useful introduction for individuals wishing to learn more about CM.

Continuous Melt Granulation for Taste-Masking of Ibuprofen

Taste-masking of drugs, particularly to produce formulations for pediatric patients, can be challenging and require complex manufacturing approaches. The objective of this study was to produce taste-masked ibuprofen granules using a novel process, twin-screw melt granulation (TSMG). TSMG is an emerging, high-productivity, continuous process. Granules of ibuprofen embedded in a lipid matrix were produced across a range of process conditions, resulting in a range of output granule particle sizes. The ibuprofen appeared to be miscible with the lipid binder though it recrystallized after processing. The ibuprofen melt granules were tested in simulated saliva using a novel, small-volume dissolution technique with continuous acquisition of the ibuprofen concentration. The ibuprofen release from the granules was slower than the neat API and physical blend, beyond the expected residence time of the granules in the mouth. The ibuprofen release was inversely related to the granule size. A Noyes–Whitney dissolution model was used and the resulting dissolution rate constants correlated well with the granule size.

Characteristics of residence time distribution in a continuous high shear mixer granulation using scraper rotation

Characteristics of residence time distribution (RTD) in a continuous high shear mixer granulation were investigated to promote the development of a continuous manufacturing process in the pharmaceutical industry. A continuous granulator with an impeller and a scraper was utilized. The tracer behavior in the continuous wet granulation was verified in impulse-response experiments with acetaminophen. The RTD of acetaminophen changed depending on the scraper speed (15-50 rpm), and the mean residence time could be adjusted by the scraper speed in the wet granulation. The impact of changes in the liquid-to-solid ratio (0.10-0.20) and the addition of binder were also examined, and the variance of RTD was influenced by both. The degree of axial mixing was quantitatively evaluated with a dimensionless index, the Peclet number (Pe). Higher scraper speed was found to suppress fluctuations of the axial mixing that occurred with changes in the liquid feed. Moreover, the transition of granule size distribution with the change in liquid feed reached a steady state more quickly under the higher scraper speed. These results show that scraper rotation can help to adjust the RTD and the axial mixing, leading to a more robust continuous granulation.

Soft sensor for real-time estimation of tablet potency in continuous direct compression manufacturing operation

One of the critical quality attributes of the solid oral dosage forms produced in continuous direct compression operations is the tablet potency. A novel soft sensor comprising of a combination of first principle-based and empirical models has been developed to enable real-time monitoring of blend and tablet potency, and concentrations of other excipients at various stream levels along the direct compression line. The soft sensor model has only three adjustable parameters, primarily associated with the equipment design and operation, so the model is product agnostic which is key to enable flexible manufacturing. The estimation accuracy of the soft sensor is demonstrated through a series of real time experiments which include steady state and dynamic transitions of potency during the runs, compared with offline analytically tested tablet cores. The results indicate that the proposed soft sensor can be utilized as a robust tool for real-time monitoring of potency, suggesting an extension of its utilization to higher levels of control. Two potential applications of the soft sensor are: 1. An element of a control strategy for product diversion; 2. A predictive model for advanced process control strategy to minimize the variability in tablet composition.

Hybrid multi-zonal compartment modeling for continuous powder blending processes

To modernize drug manufacturing, the pharmaceutical industry has been moving towards implementing emerging technologies to enhance manufacturing robustness and process reliability for production of regulation compliant drug products. Although different science and risk based technologies, like Quality-by-Design, have been used to illustrate their potential, there still exist some underlying obstacles. Specifically, for the production of oral solid drug products, an in-depth process understanding, and predictive modeling of powder mixing in continuous powder blenders is one such major obstacle and originates from the current limitations of the experimental and modeling approaches. Though first principle based discrete element modeling (DEM) approach can address the above issues, it can get very computationally intensive which limits its applications for predictive modeling. In the proposed work, we aim to address this limitation using a multi-zonal compartment modeling approach, which is constructed from DEM. The approach provides a computationally efficient and mechanistically informed hybrid model. The application of the proposed approach is first demonstrated for a periodic section of the blender, followed by its extension for the entire continuous powder blender and the obtained model predictions are validated. The proposed approach provides an overall assessment of powder mixing along axial and radial directions, which is an important requirement for the quantification of blend uniformity. Given the low computational cost, the developed model can further be integrated within the predictive flowsheet model of the manufacturing line.

Continuous Twin Screw Granulation: A Review of Recent Progress and Opportunities in Formulation and Equipment Design

Continuous twin screw wet granulation is one of the key continuous manufacturing technologies that have gained significant interest in the pharmaceutical industry as well as in academia over the last ten years. Given its considerable advantages compared to wet granulation techniques operated in batch mode such as high shear granulation and fluid bed granulation, several equipment manufacturers have designed their own manufacturing setup. This has led to a steep increase in the research output in this field. However, most studies still focused on a single (often placebo) formulation, hence making it difficult to assess the general validity of the obtained results. Therefore, current review provides an overview of recent progress in the field of continuous twin screw wet granulation, with special focus on the importance of the formulation aspect and raw material properties. It gives practical guidance for novel and more experienced users of this technique and highlights some of the unmet needs that require further research.

Strategies and formulations of freeze-dried tablets for controlled drug delivery

The freeze-drying process has been particularly attractive for preparing tablets for controlled drug release. Although traditional methods, such as granulation or direct compression methods, have been used in various studies to produce tablets with controlled release, freeze-drying processes have been utilized in certain circumstances due to their distinct advantages. However, overall, further development of these strategies, which started with early studies on orally disintegrating tablets, is still necessary. In this review, the incorporation of different formulations into freeze-dried tablets will be discussed. Moreover, the use of excipients, freeze-drying conditions, formulation reconstitution and tablet structure for optimizing the performance of freeze-dried tablets will be reported, including strategies with nanoformulations and natural materials. Generally, this discussion with potential approaches will benefit further development of freeze-dried tablets containing drugs in the pharmaceutical industry.

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.