Control of a system of loss-in-weight feeders for drug product continuous manufacturing

Critical review on the role of excipient properties in pharmaceutical powder-to-tablet continuous manufacturing

INTRODUCTION

The pharmaceutical industry is gradually changing batch-wise manufacturing processes to continuous manufacturing processes, due to the advantages it has to offer. The final product quality and process efficiency of continuous manufacturing processes is among others impacted by the properties of the raw materials. Existing knowledge on the role of raw material properties in batch processing is however not directly transferable to continuous processes, due to the inherent differences between batch and continuous processes.

AREAS COVERED

A review is performed to evaluate the role of excipient properties for different unit operations used in continuous manufacturing processes. Unit operations that will be discussed include feeding, blending, granulation, final blending, and compression.

EXPERT OPINION

Although the potency of continuous manufacturing is widely recognized, full utilization still requires a number of challenges to be addressed effectively. An expert opinion will be provided that discusses those challenges and potential solutions to overcome those challenges. The provided overview can serve as a framework for the pharmaceutical industry to push ahead process optimization and formulation development for continuous manufacturing processes.

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.

Batch vs. continuous direct compression - a comparison of material processability and final tablet quality

In this study, an in-depth comparison was made between batch and continuous direct compression using similar compression set-ups. The overall material processability and final tablet quality were compared and evaluated. Correlations between material properties, process parameters and final tablet properties were made via multivariate data analyses. In total, 10 low-dosed (1% w/w) and 10 high-dosed (40% w/w) formulations were processed, using a total of 10 different fillers/filler combinations. The trials indicated that the impact of filler type, drug load or process settings was similar for batch and continuous direct compression. The main differentiator between batch and continuous was the flow dynamics in the operating system, where properties related to flow, compressibility and permeability played a crucial role. The less consistent flow throughout a batch process resulted in a significantly higher variability within the tablet press (σCF) and for the tablet quality responses (σMass, σTS). However, the better controlled blending procedure prior to batch processing was reflected in a more consistent API concentration variability. Overall, the comparison showed the benefits of selecting appropriate excipients and process settings to achieve a specific outcome, keeping in mind some key differentiators between both processes.

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.

Feed factor profile prediction model for two-component mixed powder in the twin-screw feeder

In continuous pharmaceutical manufacturing processes, it is crucial to control the powder flow rate. The feeding process is characterized by the amount of powder delivered per screw rotation, referred to as the feed factor. This study aims to develop models for predicting the feed factor profiles (FFPs) of two-component mixed powders with various formulations, while most previous studies have focused on single-component powders. It further aims to identify the suitable model type and to determine the significance of material properties in enhancing prediction accuracy by using several FFP prediction models with different input variables. Four datasets from the experiment were generated with different ranges of the mass fraction of active pharmaceutical ingredients (API) and the powder weight in the hopper. The candidates for the model inputs are (a) the mass fraction of API, (b) process parameters, and (c) material properties. It is desirable to construct a high-performance prediction model without the material properties because their measurement is laborious. The results show that using (c) as input variables did not improve the prediction accuracy as much, thus there is no need to use them.

A review on the modernization of pharmaceutical development and manufacturing - Trends, perspectives, and the role of mathematical modeling

Recently, the pharmaceutical industry has been facing several challenges associated to the use of outdated development and manufacturing technologies. The return on investment on research and development has been shrinking, and, at the same time, an alarming number of shortages and recalls for quality concerns has been registered. The pharmaceutical industry has been responding to these issues through a technological modernization of development and manufacturing, under the support of initiatives and activities such as quality-by-design (QbD), process analytical technology, and pharmaceutical emerging technology. In this review, we analyze this modernization trend, with emphasis on the role that mathematical modeling plays within it. We begin by outlining the main socio-economic trends of the pharmaceutical industry, and by highlighting the life-cycle stages of a pharmaceutical product in which technological modernization can help both achieve consistently high product quality and increase return on investment. Then, we review the historical evolution of the pharmaceutical regulatory framework, and we discuss the current state of implementation and future trends of QbD. The pharmaceutical emerging technology is reviewed afterwards, and a discussion on the evolution of QbD into the more effective quality-by-control (QbC) paradigm is presented. Further, we illustrate how mathematical modeling can support the implementation of QbD and QbC across all stages of the pharmaceutical life-cycle. In this respect, we review academic and industrial applications demonstrating the impact of mathematical modeling on three key activities within pharmaceutical development and manufacturing, namely design space description, process monitoring, and active process control. Finally, we discuss some future research opportunities on the use of mathematical modeling in industrial pharmaceutical environments.

Impact of Vertical Blender Unit Parameters on Subsequent Process Parameters and Tablet Properties in a Continuous Direct Compression Line

The continuous manufacturing of solid oral-dosage forms represents an emerging technology among the pharmaceutical industry, where several process steps are combined in one production line. As all mixture components, including the lubricant (magnesium stearate), are passing simultaneously through one blender, an impact on the subsequent process steps and critical product properties, such as content uniformity and tablet tensile strength, is to be expected. A design of experiment (DoE) was performed to investigate the impact of the blender variables hold-up mass (HUM), impeller speed (IMP) and throughput (THR) on the mixing step and the subsequent continuous manufacturing process steps. Significant impacts on the mixing parameters (exit valve opening width (EV), exit valve opening width standard deviation (EV SD), torque of lower impeller (T_L), torque of lower impeller SD (T_L SD), HUM SD and blend potency SD), material attributes of the blend (conditioned bulk density (CBD), flow rate index (FRI) and particle size (d₁₀ values)), tableting parameters (fill depth (FD), bottom main compression height (BCH) and ejection force (EF)) and tablet properties (tablet thickness (TT), tablet weight (TW) and tensile strength (TS)) could be found. Furthermore, relations between these process parameters were evaluated to define which process states were caused by which input variables. For example, the mixing parameters were mainly impacted by impeller speed, and material attributes, FD and TS were mainly influenced by variations in total blade passes (TBP). The current work presents a rational methodology to minimize process variability based on the main blender variables hold-up mass, impeller speed and throughput. Moreover, the results facilitated a knowledge-based optimization of the process parameters for optimum product properties.

Precise Dosing of Pramipexole for Low-Dosed Filament Production by Hot Melt Extrusion Applying Various Feeding Methods

The aim of this research was the production of low-dosed filaments via hot-melt extrusion (HME) with the model drug pramipexole for the treatment of Parkinson’s disease. The active pharmaceutical ingredient (API) and one of the polymers polyvinyl alcohol (PVA) or basic butylated methacrylate copolymer (bPMMA) were fed by various dosing techniques with the aim of achieving the smallest deviation (RSD) from the target concentration of 0.1% (w/w) pramipexole. It was found that deviation from target pramipexole concentration occurred due to degradation products in bPMMA formulations. Additionally, material temperature above 120 °C led to the formation of the anhydrous form of pramipexole within the extruded filaments and need to be considered in the calculation of the recovered API. This study clearly shows that even if equilibrium state of the extrusion parameters was reached, equilibrium condition for drug content was reached relatively late in the process. In addition, the RSD calculated by the Stange–Poole equation was proposed by us to predict the final content uniformity considering the sample size of the analyzed filament. The calculated RSD, depending on sample size and drug load, can serve as upper and lower limits of variation from target concentration and can be used to evaluate the deviations of drug content in equilibrium conditions of the HME process. The lowest deviations from target concentration in equilibrium condition for drug content were obtained in filaments extruded from previously prepared granule mixtures (RSD = 6.00%, acceptance value = 12.2). These promising results can be transferred to other API–excipient combinations to produce low-dosed filaments, which can be used for, e.g., fused filament 3D printing. The introduced calculation of the RSD by Stange–Poole equation can be used for precise determination of the homogeneity of an extruded batch.

Development of a Controlled Continuous Low-Dose Feeding Process

This paper proposes a feed rate control strategy for a novel volumetric micro-feeder, which can accomplish low-dose feeding of pharmaceutical raw materials with significantly different powder properties. The developed feed-forward control strategy enables a constant feed rate with a minimum deviation from the set-point, even for materials that are typically difficult to accurately feed (e.g., due to high cohesion or low density) using conventional continuous feeders. Density variations observed during the feeding process were characterized via a displacement feed factor profile for each powder. The characterized effective displacement density profile was applied in the micro-feeder system to proactively control the feed rate by manipulating the powder displacement rate (i.e., computing the feed rate from the powder displacement rate). Based on the displacement feed factor profile, the feed rate can be predicted during the feeding process and at any feed rate set-point. Three pharmaceutically relevant materials were used for the micro-feeder evaluation: di-calcium phosphate (large-particle system, high density), croscarmellose sodium (small-particle system, medium density), and barium sulfate (very small-particle <10 μm, high density). A significant improvement in the feeding performance was achieved for all investigated materials. The feed rate deviation from the set-point and its relative standard deviation were minimal compared to operations without the control strategy.

Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press

The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-model mismatch, careful monitoring and continuous improvement strategies are studied. When moving horizon estimation (MHE) is integrated with NMPC, historical data in the past time window together with real-time data from the sensor network enable state estimation and accurate tracking of the highly sensitive model parameters. The adaptive model used in the NMPC strategy can compensate for process uncertainties, further reducing plant-model mismatch effects. The nonlinear mechanistic model used in both MHE and NMPC can predict the essential but complex powder properties and provide physical interpretation of abnormal events. The adaptive NMPC implementation and its real-time control performance analysis and practical applicability are demonstrated through a series of illustrative examples that highlight the effectiveness of the proposed approach for different scenarios of plant-model mismatch, while also incorporating glidant effects.

Powder composition monitoring in continuous pharmaceutical solid-dosage form manufacturing using state estimation - Proof of concept

In continuous solid-dosage form manufacturing, the powder feeding system is responsible for supplying downstream the correct formulation of the drug product ingredients. The composition of the powder delivered by the feeding system is inferred from the measurements of powder mass flow from the system feeders. The mass flows are, in turn, inferred from the loss in weight measured in the feeder hoppers. Most loss-in-weight feeders post-process the mass flow signal to deliver a smoothed value to the user. However, such estimated mass flows can exhibit a low signal-to-noise ratio. As the feeders are critical elements of the control strategy of the manufacturing line, better instantaneous estimates of mass flow are desirable for improving the quality assurance. In this study, we propose a model-based approach for monitoring the composition of the powder fed to a continuous solid-dosage line. The monitoring system is based on a moving-horizon state estimator, which carries out model-based reconciliation of the feeder mass measurements, thus enabling accurate composition estimation of the powder mixture. Experimental datasets from a direct compression line are used to validate the methodology. Results demonstrate improvement with respect to current industrial solutions.

Loss-in-weight feeding, powder flow and electrostatic evaluation for direct compression hydroxypropyl methylcellulose (HPMC) to support continuous manufacturing

Minimizing variability in the feeding process is important for continuous manufacturing since materials are fed individually and can impact the final product. This study demonstrates the importance of measuring powder properties and highlights the need to characterize the feeding performance both offline with multiple refills and in the intended configuration for the continuous manufacturing equipment. The standard grade hydroxypropyl methylcellulose (HPMC) had material buildup on the loss-in-weight feeder barrel from triboelectric charging and resulted in more mass flow excursions and failed refills which were not observed with the direct compression grades. The location of the electrostatic buildup changed when the feeder was connected to a hopper instead of feeding offline into a collection bucket. Overall, the direct compression HPMC exhibited better flow which resulted in more accurate loss-in-weight feeding with less excursions from the target mass flow and all refills were completed in the first attempt. The improvements with the direct compression HPMC would be beneficial when running any continuous process (wet granulation, roller compaction, or direct compression) or other processes where loss-in-weight feeding is utilized, such as melt extrusion or twin screw granulation.

A solution for low-dose feeding in continuous pharmaceutical processes

Continuous feeding of small quantities of powder is increasingly applied in pharmaceutical manufacturing. With that regard, what is crucial is not only the feasibility, but also the accuracy and stability. To enable stable processing, low amounts of various agents, e.g., lubricants, can be used. Even more important is the exact dosage of highly potent active pharmaceutical ingredients (APIs), which require feed rates within the range of grams per hour. Conventional feeders cannot supply powder at such rates, especially when the material properties are challenging. In this work, a novel micro-feeder was integrated into a continuous manufacturing line and its capability to supply API at feed rates down to one gram per hour was tested. The micro-feeder system is based on the principle of active volumetric displacement: a piston pushes the powder out of the cartridge upwards to the end of a plate, where a scraper places it into the process inlet. In this study, a hot melt extrusion process was used, during which the API was dissolved in a polymer matrix. Samples of the strand were analysed with regard to their content by means of HPLC. The results showed that the novel micro-feeder system can feed powder with good accuracy and reproducibility, indicating its high potential for continuous process implementation.

Continuous Manufacturing of Ketoprofen Delayed Release Pellets Using Melt Extrusion Technology: Application of QbD Design Space, Inline Near Infrared, and Inline Pellet Size Analysis

Delayed-release dosage forms are mainly manufactured as batch processes and include coated tablets, pellets, or particles with gastric resistant polymers. Authors propose a novel approach using the hot-melt extrusion technique to prepare delayed release dosage forms via a continuous manufacturing process, a new trend in the pharmaceutical industry. A full factorial design was employed to correlate input variables, including stearic acid (SA) content, drug content, and pellet size with drug release properties of the pellets. PLS fit method suitably elaborated the relationship between input and output variables with reasonably good fit and goodness of prediction. All three input factors influenced drug release in enzyme-free simulated gastric fluid (SGF) after 120 min; however, SA content did not significantly affect drug dissolution in the enzyme-free simulated intestinal fluid (SIF). An optimized formulation and design space were determined by overlaying multiple contours established from regression equations. The continuous manufacturing process was successfully monitored using inline near-infrared (NIR) and inline particle size analysis, with drug load and pellet size being well-controlled within the design space. The obtained pellets released less than 5% after 120 min in SGF and more than 85% and 95% after 30 min and 45 min, respectively, after switching to SIF.

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

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

Partial Least Squares Regression-Based Robust Forward Control of the Tableting Process

In this study, we established a robust feed-forward control model for the tableting process by partial least squares regression using the near-infrared (NIR) spectra and physical attributes of the granules to be compressed. The NIR spectra of granules are rich in information about chemical attributes, such as the compositions of any ingredients and moisture content. Polymorphism and pseudo-polymorphism can also be quantitatively evaluated by NIR spectra. We used the particle size distribution, flowability, and loose and tapped density as the physical attributes of the granules. The tableting process was controlled by the lower punch fill depth and the minimum distance between the upper and lower punches at compression, which were specifically related to the tablet weight and thickness, respectively. The feed-forward control of the process would be expected to provide some advantages for automated and semi-automated continuous pharmaceutical manufacturing. As a result, our model, using a combination of NIR spectra and the physical attributes of granules to control the distance between punches, resulted in respectable agreement between the predicted process parameters and actual settings to produce tablets of the desired thickness.

Continuous Formulation Approaches of Amorphous Solid Dispersions: Significance of Powder Flow Properties and Feeding Performance

Preparation and formulation of amorphous solid dispersions (ASDs) are becoming more and more popular in the pharmaceutical field because the dissolution of poorly water-soluble drugs can be effectively improved this way, which can lead to increased bioavailability in many cases. During downstream processing of ASDs, technologists need to keep in mind both traditional challenges and the newest trends. In the last decade, the pharmaceutical industry began to display considerable interest in continuous processing, which can be explained with their potential advantages such as smaller footprint, easier scale-up, and more consistent product, better quality and quality assurance. Continuous downstream processing of drug-loaded ASDs opens new ways for automatic operation. Therefore, the formulation of poorly water-soluble drugs may be more effective and safe. However, developments can be challenging due to the poor flowability and feeding properties of ASDs. Consequently, this review pays special attention to these characteristics since the feeding of the components greatly influences the content uniformity in the final dosage form. The main purpose of this paper is to summarize the most important steps of the possible ASD-based continuous downstream processes in order to give a clear overview of current course lines and future perspectives.

Deriving control parameter settings from process models to control capsule fillers integrated into continuous manufacturing

The aim of this work was to investigate the mean fill weight control of a continuous capsule-filling process, whether it is possible to derive controller settings from an appendant process model. To that end, a system composed out of fully automated capsule filler and an online gravimetric scale was used to control the filled weight. This setup allows to examine challenges associated with continuous manufacturing processes, such as variations in the amount of active pharmaceutical ingredient (API) in the mixture due to fluctuations of the feeders or due to altered excipient batch qualities. Two types of controllers were investigated: a feedback control and a combination of feedback and feedforward control. Although both of those are common in the industry, determining the optimal parameter settings remains an issue. In this study, we developed a method to derive the control parameters based on process models in order to obtain optimal control for each filled product. Determined via rapid automated process development (RAPD), this method is an effective and fast way of determining control parameters. The method allowed us to optimize the weight control for three pharmaceutical excipients. By conducting experiments, we verified the feasibility of the proposed method and studied the dynamics of the controlled system. Our work provides important basic data on how capsule filler can be implemented into continuous manufacturing systems.

Continuous Twin Screw Wet Granulation and Drying-Control Strategy for Drug Product Manufacturing

The use of continuous manufacturing has been increasing within the pharmaceutical industry over the last few years. Continuous direct compression has been the focus of publications on the topic to date. The use of wet granulation can improve segregation resistance, uniformity, enhance density, and flow properties for improved tabletability, or improve stability of products that cannot be manufactured by using a direction compression process. This article focuses on development of appropriate control strategies for continuous wet granulation (especially twin screw wet granulation) through equipment design, material properties and manufacturing process along with areas where additional understanding is required. The article also discusses the use of process analytical technologies as part of the control and automation approach to ensure a higher assurance of product quality. Increased understanding of continuous wet granulation should result in increased utilization of the technique, thereby allowing for an increase in diversity of products manufactured by continuous manufacturing and the benefits that comes with a more complex process such as wet granulation compared with direct compression process.