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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.

Pharmaceutical products represent a meaningful target for sustainability improvement and emissions reduction. It is proposed here that rethinking the standard, and often linear, approach to the synthesis of Active Pharmaceutical Ingredients (API) and subsequent formulation and drug product processing will deliver transformational sustainability opportunities. The greatest potential arguably involves API that have challenging physico-chemical properties. These can require the addition of excipients that can significantly exceed the weight of the API in the final dosage unit, require multiple manufacturing steps to achieve materials amenable to delivering final dosage units, and need highly protective packaging for final product stability. Co-processed API are defined as materials generated via addition of non-covalently bonded, non-active components during drug substance manufacturing steps, differing from salts, solvates and co-crystals. They are an impactful example of provocative re-thinking of historical regulatory and quality precedents, blurring drug substance and drug product operations, with sustainability opportunities. Successful examples utilizing co-processed API can modify properties with use of less excipient, while simultaneously reducing processing requirements by delivering material amenable to continuous manufacturing. There are also opportunities for co-processed API to reduce the need for highly protective packaging. This commentary will detail the array of sustainability impacts that can be delivered, inclusive of business, regulatory, and quality considerations, with discussion on potential routes to more comprehensively commercialize co-processed API technologies. [ABSTRACT FROM AUTHOR]

Continuous direct compression (CDC) of solid oral dosage forms requires materials exhibiting acceptable flow and compression properties. The desired active pharmaceutical ingredient (API) powder properties can be difficult to achieve through conventional particle engineering approaches, such as particle size and habit modification during crystallization. Co-processing of API with excipients can significantly improve the powder properties to overcome these difficulties. In this manuscript, performance of a co-processed API was evaluated in a continuous feeding and blending process using GEA ConsiGma® Continuous Dosing and Blending Unit (CDB1). The co-processed theophylline was generated via a methodology in which polymer was precipitated and coated the crystalline theophylline particles resulting in nearly spherical agglomerates. A range of drug loads (1-25% w/w), flow rates (15-40 kg/h) and blender speeds (220-400 rpm) were studied. The results demonstrated that the co-processed API can be successfully fed through a loss-in-weight feeder and blended with other excipients in a high shear blender to generate tablets with acceptable content uniformity at 1-25% w/w drug loads. This study supports that using co-processed API with enhanced powder properties is a promising approach to enable continuous manufacturing for APIs with challenging properties. [ABSTRACT FROM AUTHOR]

Continuous blenders are a key unit operation in Continuous Direct Compaction, a route to solid oral dosage forms that is receiving significant interest. Mass holdup in these blenders is a crucial variable; understanding how it is influenced by material properties, equipment configuration and process settings is key. The present work evaluated a Gericke GCM-450 blender for range of outlet weir aperture geometries (angled or horizontal), material properties (pure components and blends) and process settings (throughput and impeller speed). Results show opposing mass holdup behaviour depending on weir choice, material density and flowability, likely linked to the propensity of the material to form an inclined powder surface that matches – or does not – the chosen weir geometry. The present work underscores the need for fundamental process phenomena understanding, especially when insight is sought for how blender performance varies across multiple dimensions (throughput, impeller speed, material properties) and discrete equipment choices (weir geometry). [Display omitted] • Interaction between equipment geometry and material properties highlighted. • Opposing behaviour of high-density free-flowing material and low-density cohesive material. • Impact on mass hold up behaviour of process settings and material properties (equipment configuration dependant). • Impact on continuous direct compression operation. [ABSTRACT FROM AUTHOR]

Process integration efforts in the pharmaceutical industry have led to an increased interest in Direct Compression, including Continuous Direct Compression. Accurate scale-up of powder blending and prediction of blend Critical Quality Attributes (CQAs) is key. The present work takes a modified approach for blend CQA characterisation in a high-shear semi-continuous blender (originally developed for low-shear batch blenders), and combines it with a blend content uniformity model (developed for high-shear continuous blenders) to characterise content uniformity responses of a high-shear semi-continuous blender (Gericke GBM-10-P Mini Blender). Blend content uniformity assessed across process conditions and formulations shows that for a given formulation one set of model parameters can be regressed for all datapoints, allowing insight to be transferred between blender scales and types. This infers that lab-scale low-shear batch blenders can be used to predict the content uniformity response of the high-shear semi-continuous blender, minimising materials consumption and experimental burden. [Display omitted] • Equation for transferrable process conditions of a semi-batch Gericke Mini Blender. • Demonstrated application to a low-dose formulation. • Process intensification compared to traditional tumble blending. • Rapid axial dispersion of components throughout the bulk of the powder. • Limiting content uniformity based on particle size of active ingredient. [ABSTRACT FROM AUTHOR]

In this study, an empirical predictive model was developed based on the quantitative relationships between blend properties, critical quality attributes (CQA) and critical process parameters (CPP) related to blending and tableting. The blend uniformity and API concentration in the tablets were used to elucidate challenges related to the processability as well as the implementation of PAT tools. Thirty divergent ternary blends were evaluated on a continuous direct compression line (ConsiGma™ CDC-50). The trials showed a significant impact of the impeller configuration and impeller speed on the blending performance, whereas a limited impact of blend properties was observed. In contrast, blend properties played a significant role during compression, where changes in blend composition significantly altered the tablet quality. The observed correlations allowed to develop an empirical predictive model for the selection of process configurations based on the blend properties, reducing the number of trial runs needed to optimize a process and thus reducing development time and costs of new drug products. Furthermore, the trials elucidated several challenges related to blend properties that had a significant impact on PAT implementation and performance of the CDC-platform, highlighting the importance of further process development and optimization in order to solve the remaining challenges.

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. [Display omitted] • A stochastic process model is developed for a continuous feeding–blending unit. • The impact of process variability on the performance of an MPC is investigated. • A case study is carried out for a realistic setup of a CDC line in closed-loop. [ABSTRACT FROM AUTHOR]

[Display omitted] 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. [ABSTRACT FROM AUTHOR]

The aim of this study is to show the robustness of a commercial direct compression system running continuously under relevant process conditions for over 120 h. The study will apply a representative commercial control strategy including real time monitoring of process parameters, rejection of OOS material, use of in-line NIR prediction for blend potency monitoring, application of mathematical RTD modelling for real-time prediction of product potency, and tablet concentration prediction by tablet NIR. The study showed that the process can produce in specification product robustly over significant operating times. Across 122 h of actual run time (including pauses) the process manufactured over 15 million tablets to give a product yield of 99.2%. Whilst the purpose of this study was to evaluate the process for over 120 h, this process is not limited to running longer periods of time given the performance of the equipment and the control strategy. Unlabelled Image • Continuous direct compression manufacturing demonstrated over 120 h. • Application of commercial control strategy including PAT. • Real time control of product quality. • Demonstration of high process capability throughout the entire run. • Yield of 99.2%, producing 15 million tablets. [ABSTRACT FROM AUTHOR]

Purpose: Understanding and predicting the flow of bulk pharmaceutical materials could be key in enabling pharmaceutical manufacturing by continuous direct compression (CDC). This study examines whether, by taking powder and bulk measurements, and using statistical modelling, it would be possible to predict the flow of a range of materials likely to be used in CDC. Methods: More than 100 materials were selected for study, from four pharmaceutical companies. Particle properties were measured by static image analysis, powder surface area and surface energy techniques, and flow by shear cell measurements. The data was then analysed, and a range of statistical modelling techniques were used to build predictive models for flow. Results: Using the results from static image analysis, a model could be built which allowed the prediction of likely flow in a shear cell, which can be related to performance in a CDC system. Only a small amount of powder was required for the image analysis. Surface area did not add to the precision of the model, and the available surface energy technique did not correlate with flow. Conclusions: A small sample of powder can be examined by static image analysis, and this data can be used to give an early read on likely flow of a material in a CDC system or other pharmaceutical process, allowing early intervention (if necessary) to improve the characteristics of a material, early in development. [ABSTRACT FROM AUTHOR]

Residence-time-distribution (RTD)-based models are key to understanding the mixing dynamics of continuous manufacturing systems. Such models can allow for material traceability throughout the process and can provide the ability for removal of non-conforming material from the finished product. These models have been implemented in continuous pharmaceutical manufacturing mainly for monitoring purposes, not as an integral part of the control strategy and in-process specifications. This paper discusses the steps taken to develop an RTD model design space and how the model was statistically incorporated into the product’s control strategy. To develop the model, experiments were conducted at a range of blender impeller speeds and total system mass flow rates. RTD parameters were optimized for each condition tested using a tank-in-series-type model with a delay. Using the experimental RTD parameters, an equation was derived relating the mean residence time to the operating conditions (i.e., blender impeller speed and mass flow rate). The RTD parameters were used in combination with real-time upstream process data to predict downstream API concentration, where these predictions allowed validation across the entire operating range of the process by comparison to measured tablet assay. The standard in-process control limits for the product were statistically tightened using the validation acceptance criteria. Ultimately, this model and strategy were accepted by regulatory authorities.

Continuous manufacturing of oral-dosage drug products is increasing the need for rigorous process understanding both from a process design and control perspective. The purpose of this study is to develop a methodology that analyzes the effects of upstream process parameters on continuous tablet compaction and then correlates associated upstream variables to the final tablet attributes (e.g. relative density and hardness). The impact of three process parameters (system throughput, blender speed, and compaction force) on tablet attributes is investigated using a full factorial experimental design. As expected, the compaction force was found to be the most significant process parameter. However, importantly, throughput was discovered to have a non-negligible impact which was previously unaccounted for. This impact is proposed to be related to differing levels of powder pre-compression. An empirical model for this relationship is regressed and incorporated into a flowsheet model. The flowsheet model is then used to develop an in silico design space which is compared favorably to that built from experiments. Moreover, in the future, the in silico design space based on the validated flowsheet model can provide better manufacturing flexibility and make control strategy development simpler. [ABSTRACT FROM AUTHOR]

This work aims to expand the typical raw material attributes that can successfully be processed on a continuous direct compression line with a particular focus on the continuous dry powder blender. Three grades of Acetaminophen were investigated as model active pharmaceutical ingredients and chosen to span a broad range of material attributes wider than what would normally be considered for a direct compression process. An experimental design was set-up for each grade of Acetaminophen to investigate the effect of throughput, impeller speed and impeller configuration on the critical process responses and attributes. The strain experienced by the in-process material was found critical to improve content uniformity. The impeller speed and design can be optimised at a given throughput to obtain a strain which would deliver the required content homogeneity. The content uniformity of the final tablets can be modelled as a function of the strain using an exponential decay model. Unlabelled Image • Wide range of parameters deliver acceptable tablet content uniformity. • Blender throughput, speed and configuration significantly affect residence mass. • Final tablet uniformity is a function of the mean residence time and impeller speed. • Prediction of final tablet content uniformity from process imparted strain. [ABSTRACT FROM AUTHOR]

Utilising three artificial intelligence (AI)/machine learning (ML) tools, this study explores the prediction of fill level in inclined linear blenders at steady state by mapping a wide range of bulk powder characteristics to processing parameters. Predicting fill levels enables the calculation of blade passes (strain), known from existing literature to enhance content uniformity. We present and train three AI/ML models, each demonstrating unique predictive capabilities for fill level. These models collectively identify the following rank order of feature importance: RPM, Mixing Blade Region (MB) size, Wall Friction Angle (WFA), and Feed Rate (FR). Random Forest Regression, a machine learning algorithm that constructs a multitude of decision trees at training time and outputs the mode of the classes (classification) or mean prediction (regression) of the individual trees, develops a series of individually useful decision trees. but also allows the extraction of logic and breakpoints within the data. A novel tool which utilises smart optimisation and symbolic regression to model complex systems into simple, closed-form equations, is used to build an accurate reduced-order model. Finally, an Artificial Neural Network (ANN), though less interrogable emerges as the most accurate fill level predictor, with an r 2 value of 0.97. Following training on single-component mixtures, the models are tested with a four-component powdered paracetamol formulation, mimicking an existing commercial drug product. The ANN predicts the fill level of this formulation at three RPMs (250, 350 and 450) with a mean absolute error of 1.4%. Ultimately, the modelling tools showcase a framework to better understand the interaction between process and formulation. The result of this allows for a first-time-right approach for formulation development whilst gaining process understanding from fewer experiments. Resulting in the ability to approach risk during product development whilst gaining a greater holistic understanding of the processing environment of the desired formulation. [Display omitted] [ABSTRACT FROM AUTHOR]

• Empirical relationships between operating parameters and model equation parameters create a predictive powder mixing model. • Empirical model predicts general behaviour and observations well but does not outperform parameter estimation. • Potential for a model based soft sensor for out-of-specification material detection was demonstrated. Continuous manufacturing of oral-dosage pharmaceuticals is widely understood to ensure consistent product quality and higher productivity at lower costs. Here, a hybrid flowsheet model is developed in order to link the process variables to the residence time distribution (RTD) of mixed pharmaceutical powders in a continuous direct compression (CDC) process containing two separate powder blending units. An empirical equation is regressed from collected RTD data for one formulation that calculates parameters for a tanks-in-series model as a function of system throughput and blender impeller speed. The prediction power of the hybrid flowsheet was tested against the regression dataset and validated against five conditions that were not used in the regression. The hybrid flowsheet was found to perform accurately against the regression dataset and could predict the behavior of the validation dataset. The potential applications of the hybrid flowsheet were demonstrated by developing a soft sensor for predicting off-target material based on a large in-silico dataset generated by the hybrid flowsheet. The soft sensor was demonstrated to accurately predict diversion events triggered by off-target material as well as adjust the throughput and blender speed to prevent the diversion event from occurring. [ABSTRACT FROM AUTHOR]

A flowsheet model for a continuous direct compression tableting process is developed and applied to process data generated at production scale. The model contains powder feeding, blending and tablet compaction unit operations. The dataset was provided by Merck & Co., Inc., Kenilworth, NJ USA using a GEA ConsiGma™ continuous direct compression process designed for approximately 50 kg/h throughput using a six ingredient, potentially commercial, formulation. A tanks-in-series methodology is used to model the transport of powders through the blending units and a number of tablet compaction equations are selectable which can illustrate how upstream changes in composition are propagated to tablet properties. The flowsheet model performed well based on the available dataset with accurate predictions of API concentration and tablet hardness. Monte Carlo simulations were used along with the flowsheet model to investigate the contribution of feeder flowrate variability to measurement noise and the sensitivity of tablet hardness to process parameters and material properties. Unlabelled Image • Tanks in series approach provides simple and accurate residence time model results. • Model performed well over a wide range of operating conditions. • Flowsheet model could simulate realistic failure modes for risk assessment purposes. • Impact of process parameters and material properties were investigated. • Process parameters more significant than material properties for tablet compaction. [ABSTRACT FROM AUTHOR]

In this work, the transfer of oral solid dosage forms, currently manufactured via wet granulation, to a continuous direct compression process was considered. Two main challenges were addressed: (1) a poorly flowing API (Canagliflozin) and (2) high drug loading (51 wt%). A scientific approach was utilised for formulation development, targeting flow and compaction behaviour suitable for manufacturing scale. This was achieved through systematic screening of excipients to identify feasible formulations. Targeted design of experiments based on factors such as formulation mixture and processing parameters were utilised to investigate key responses for tablet properties, flow and compaction behaviour. Flow behaviour was primarily evaluated from percentage compressibility and shear cell testing on a powder flow rheometer (FT4). The compaction behaviour was studied using a compaction simulator (Gamlen). The relationships between tablet porosity, tensile strength and compaction pressure were used to evaluate tabletability, compactibility and compressibility to assess scale-up. The success of this design procedure is illustrated by scaling up from the compaction simulator to a Riva Piccola rotary tablet press, while maintaining critical quality attributes (CQAs). Compactibility was identified as a suitable scale-up relationship. The developed procedure should allow accelerated development of formulations for continuous direct compression. [ABSTRACT FROM AUTHOR]

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.

Graphical abstract Abstract In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models for in silico process and formulation development based on (a selection of) property descriptors. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract Based on characterization of a wide range of fillers and APIs, thirty divergent blends were composed and subsequently compressed on a rotary tablet press, varying paddle speed and turret speed. The tablet weight variability was determined of 20 grab samples consisting of each 20 tablets. Additionally, the bulk residence time, ejection force, pre-compression displacement, main compression force, die fill fraction and feed frame fill fraction were determined during each run. Multivariate data analysis was applied to investigate the relation between the process parameters, blend characteristics, product and process responses. Blends with metoprolol tartrate as API showed high ejection forces. This behavior could be linked to the high wall friction value of metoprolol tartrate. The main responses related to the die filling could be predicted via a PLS model based on blend characteristics. Tablet weight variability was highly correlated with the variability on pre-compression displacement and main compression force. A good predictive model for tablet weight variability was obtained taking the porosity, wall friction angle, flowability, density, compressibility and permeability into account. Additionally, turret speed and paddle speed were included in the calibration of the model. The applied approach can save resources (material, time) during early drug product development. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The production of pharmaceutical tablets is shifting towards continuous manufacturing. Therefore, individual unit operations such as powder blending need to be re-designed. Continuous powder blending has been implemented successfully, but for low-dose formulations this is challenging due to difficulties with continuously dosing small amounts of powder. To overcome such challenges, a semi-continuous mini-blending operation combined with batch-wise dosing can be introduced in a continuous process. The objective of this study is to investigate key factors that affect blending performance of a novel, semi-continuous mini-blending process. A design of experiments is performed, varying both process settings and blend formulations. This reveals that blending performance of the mini-blending process is largely controlled by process settings. These results show that the mini-blender design, with high mixing intensity and short mixing times, supports process intensification of powder blending. The results obtained can be used for Quality by Design-based formulation development for continuous direct compression. [Display omitted] • Demonstration of a semi-continuous powder mini-blender for process intensification. • Mini-blender design supports continuous direct compression of low drug loads. • Extend of process intensification is impacted by blending regime. • Powder flow and tablet properties are affected by blending process and excipients. • Mixing process intensification allows product optimization to focus on other CQA's. [ABSTRACT FROM AUTHOR]

In this work a continuous direct compression process was developed for a low-dosed drug product. Each unit operation of the GEA CDC-50 system was thoroughly investigated. This paper aimed to tackle the macroscopic and microscopic blend uniformity challenges inherently associated with continuous direct compression of cohesive and agglomerated APIs formulated at low dose. Density, compressibility and flow were identified as key material properties at the feeding stage. The screw speed coupled with powder flow regulated the gravimetric feeding performance. The impact of process and design variables was elucidated at the blending stage. The impeller configuration (number and pattern of radial mixing blades) and speed were key variables to steer the residence time distribution at the blending stage. An impeller configuration with distributed radial mixing blades could sufficiently filter the steady state feeding variability at low mixer speed, but exerted limited strain and shear on the blend. Hence micro-agglomerates persisted through the blending process and occasionally resulted in super potent tablets. Therefore, a new configuration was evaluated with more radial mixing blades centered on the impeller. This configuration resulted in a long mixing time at high tip speed which induced a maximized strain and shear. Consequently, excellent uniformity of the blend and tablets at macroscopic and microscopic level was achieved. Besides, this impeller improved robustness towards feeding disturbances, changes in process settings and variable blend properties. Next, it was demonstrated that the lubrication step requires critical attention during the design of the equipment, formulation and process. This study provided abundant evidence that an optimized continuous direct compression process allows direct compression of challenging low-dose drug products. [ABSTRACT FROM AUTHOR]

This study presents a framework for process and product development on a continuous direct compression manufacturing platform. A challenging sustained release formulation with high content of a poorly flowing low density drug was selected. Two HPMC grades were evaluated as matrix former: standard Methocel CR and directly compressible Methocel DC2. The feeding behavior of each formulation component was investigated by deriving feed factor profiles. The maximum feed factor was used to estimate the drive command and depended strongly upon the density of the material. Furthermore, the shape of the feed factor profile allowed definition of a customized refill regime for each material. Inline NIRs was used to estimate the residence time distribution (RTD) in the mixer and monitor blend uniformity. Tablet content and weight variability were determined as additional measures of mixing performance. For Methocel CR, the best axial mixing (i.e. feeder fluctuation dampening) was achieved when an impeller with high number of radial mixing blades operated at low speed. However, the variability in tablet weight and content uniformity deteriorated under this condition. One can therefore conclude that balancing axial mixing with tablet quality is critical for Methocel CR. However, reformulating with the direct compressible Methocel DC2 as matrix former improved tablet quality vastly. Furthermore, both process and product were significantly more robust to changes in process and design variables. This observation underpins the importance of flowability during continuous blending and die-filling. At the compaction stage, blends with Methocel CR showed better tabletability driven by a higher compressibility as the smaller CR particles have a higher bonding area. However, tablets of similar strength were achieved using Methocel DC2 by targeting equal porosity. Compaction pressure impacted tablet properties and dissolution. Hence controlling thickness during continuous manufacturing of sustained release tablets was crucial to ensure reproducible dissolution. [ABSTRACT FROM AUTHOR]

In the present work the viability of integrated continuous mixing and compression processes for manufacturing of extended release (ER) matrix tablets was investigated in terms of dissolution behavior. The purpose was also to evaluate the combined effect of processing variables and compositional variables on the release robustness. The continuous process was provoked by a challenging formulation design, including variable powder characteristics and compositions of high and low amount of poorly soluble and poorly flowing drug substance (ibuprofen). Additionally a relatively low amount of two different ER matrix former grades (standard granulation grade CR and direct compression grade DC2 of hydroxypropyl methylcellulose, HPMC) was used to challenge the system. Robust ibuprofen release was obtained faster when HPMC CR was used. However, robust release was also achieved when using HPMC DC2 at high ibuprofen content, even though it took slightly longer time to reach the steady state of the process. Due to its poor flow properties, HPMC CR would be very challenging to use in traditional direct compression. The results showed that by using continuous processing it is possible to manufacture and achieve robust performance of compositions that would not be possible with traditional batch processing due to for instance poorly flowability. [ABSTRACT FROM AUTHOR]

[Display omitted] The pharmaceutical industry is continuously overcoming ways to reduce its development times to market and bring new medicines to patients with the highest quality standards faster. This can be achieved with continuous manufacturing and digital design by minimising the amount of active pharmaceutical ingredient (API) needed in drug product design, early project de-risking, and reducing the use of clinical manufacturing equipment, rework, and quality investigations. This paper presents the digital twin of a continuous direct compression line combining first-principles models, residence time distribution (RTD) models obtained from discrete element method (DEM) simulations, science of scale tools and data-driven models from process data in a hybrid flowsheet approach. The flowsheet predicts critical process parameters in the feeders, blender, and tablet press, and critical quality attributes, like tablet composition, weight, thickness, and hardness. It allows the study of the steady state operation in the design space, the impact of operating conditions, material and process parameters, and the dynamic response to disturbances. This is used to de-risk and optimise drug product and process development while reducing the number of experiments. The digital twin also has the potential to guide manufacturing runs and respond to new drug product market approval queries using flowsheet modelling. [ABSTRACT FROM AUTHOR]

[Display omitted] In this study, quantitative relationships were established between blend properties, process settings and blending responses via multivariate data-analysis. Four divergent binary blends were composed in three different ratios and processed at various throughputs and impeller speeds. Additionally, different impeller configurations were tested to see their impact on the overall blending performance. During each run, feeder mass flows were compared with the API concentration (BU) in order to investigate the dampening potential of the blender. The blender hold-up mass (HM), mean residence time (MRT), strain on the powder (#BP) and BU variability (RSD BU) were determined as blending descriptors and analyzed via PLS-regression. This elucidated the correlation between process settings (i.e. throughput and impeller speed) and blending responses, as well as the impact of blend properties on MRT and RSD BU. Furthermore, the study revealed that HM does not need to be in steady state conditions to assure a stable BU, while it became clear that long/large feeder deviations can only be dampened by the blender when using dedicated impeller configurations. Overall, this study demonstrated the generic application of the blender, while the developed PLS models could be used to predict the blender performance based on the blend properties. [ABSTRACT FROM AUTHOR]

Residence-time-distribution (RTD)-based models are key to understanding the mixing dynamics of continuous manufacturing systems. Such models can allow for material traceability throughout the process and can provide the ability for removal of non-conforming material from the finished product. These models have been implemented in continuous pharmaceutical manufacturing mainly for monitoring purposes, not as an integral part of the control strategy and in-process specifications. This paper discusses the steps taken to develop an RTD model design space and how the model was statistically incorporated into the product's control strategy. To develop the model, experiments were conducted at a range of blender impeller speeds and total system mass flow rates. RTD parameters were optimized for each condition tested using a tank-in-series-type model with a delay. Using the experimental RTD parameters, an equation was derived relating the mean residence time to the operating conditions (i.e., blender impeller speed and mass flow rate). The RTD parameters were used in combination with real-time upstream process data to predict downstream API concentration, where these predictions allowed validation across the entire operating range of the process by comparison to measured tablet assay. The standard in-process control limits for the product were statistically tightened using the validation acceptance criteria. Ultimately, this model and strategy were accepted by regulatory authorities. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel hybrid soft sensor for monitoring blend potency along continuous direct compression line. • Capable of estimating tablet potency with R2 = 96% linearity across 85%-115% potency range. • Application in control strategy for product diversion and APC to minimize variability in potency. 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. [ABSTRACT FROM AUTHOR]

[Display omitted] In this study, a quantitative relationship between material properties, process settings and screw feeding responses of a high-throughput feeder was established via multivariate models (PLS). Thirteen divergent powders were selected and characterized for 44 material property descriptors. During volumetric feeder trials, the maximum feed capacity (FCC max), the relative standard deviation on the maximum feed capacity (RSD F C max), the short term variability (STRSD) and feed capacity decay (FC decay) were determined. The gravimetric feeder trials generated values for the mass flow rate variability (RSD LC), short term variability (STRSD) and refill responses (V refill and RSD refill). The developed PLS models elucidated that the material properties and process settings were clearly correlated to the feeding behavior. The extended volumetric feeder trials pointed out that there was a significant influence of the chosen screw type and screw speed on the feeding process. Furthermore, the process could be optimized by reducing the feeding variability through the application of optimized mass flow filters, high frequency vibrations, independent agitator control and optimized top-up systems. Overall, the models could allow the prediction of the feeding performance for a wide range of materials based on the characterization of a subset of material properties greatly reducing the number of required feeding experiments. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]