RTD-based material tracking in a fully-continuous dry granulation tableting line

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.

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.

Elucidation of the powder flow pattern in a twin-screw LIW-feeder for various refill regimes

The importance of residence time distribution modeling is acknowledged as a tool for enabling material tracking and control within a continuous manufacturing line in order to safeguard both product quality and production efficiency. One of the first unit-operations into a continuous direct compression line (i.e. CDC-line) worthwhile doing extensive RTD-analysis upon are the LIW-feeders since they dose the ingredients in a controlled way following the label claim and hence can directly influence critical quality attributes like content uniformity. An NIR measurement method was developed determining the RTD of selected powders at specific feeder settings. Step-change experiments using sodium saccharin as a tracer were conducted. In order to gain and in depth understanding of the material flow, spatial samples throughout the hopper were taken at predefined timepoints during the step change experiments. This revealed the presence of a bypass trajectory along the edges of the agitator, while in the center of the agitator an inner mixing volume in which the tracer concentration lags behind seemed to be present. Finally, a model based on a plug flow and continuous stirred tank reactor was evaluated. The fitted model was not able to capture this complex flow behavior and shows the need for an extended compartmental model distinguishing between a bypass trajectory formed by the agitator and an inner mixing volume.

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.

Soft sensor for content prediction in an integrated continuous pharmaceutical formulation line based on the residence time distribution of unit operations

In this study, a concentration predicting soft sensor was achieved based on the Residence Time Distribution (RTD) of an integrated, three-step pharmaceutical formulation line. The RTD was investigated with color-based tracer experiments using image analysis. Twin-screw wet granulation (TSWG) was directly coupled with a horizontal fluid bed dryer and an oscillating mill. Based on integrated measurement, we proved that it is also possible to couple the unit operations in silico. Three surrogate tracers were produced with a coloring agent to investigate the separated unit operations and the solid and liquid inputs of the TSWG. The soft sensor's prediction was compared to validating experiments of a 0.05 mg/g (15% of the nominal) concentration change with High-Performance Liquid Chromatography (HPLC) reference measurements of the active ingredient proving the adequacy of the soft sensor (RMSE < 4%).

100% visual inspection of tablets produced with continuous direct compression and coating

Visual appearance of tablets is an important property for patients. Since the visual appearance is most strongly influenced by the applied coating, this necessitates a high level of process control and homogeneity in the coating process. In recent years, a number of tablet coaters have been developed that can be used in combination with continuous tablet production lines. In this study, 180 kg of tablets were produced using a continuous direct compaction line with a throughput of 25 kg/h. Tablets were consequently subdivided into 12 lots and coated in a semi-batch drum coater directly after compression. For a detailed understanding of intra-lot and lot-to-lot variability, a 100% visual inspection of the tablets was performed using an automatic tablet inspection and sorting machine. All tablets were analyzed from all 6 sides and the unsuitable tablets were sorted out. In the worst lot, only 1 out of around 300 tablets was sorted out due to color mismatch. For some tablets, edge chipping was also observed, which would presumably not be detected during routine sampling. Root causes for the defects could be found in the intentionally chosen set of old punches and in the operation parameters of the coater. Nonetheless, the lot-to-lot variability according to all criteria was very low.

Development and Use of a Residence Time Distribution (RTD) Model Control Strategy for a Continuous Manufacturing Drug Product Pharmaceutical Process

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.

Challenges in tracing material flow passing a loss-in-weight feeder in continuous manufacturing processes

Loss-in-weight feeders are an integral part of most continuous manufacturing processes, ensuring a constant mass flow. The feeders cause a significant degree of back-mixing in such lines. Understanding back-mixing is essential for the treatment of disturbances. However, feeders refilled semi-continuously contradict the common theory assuming steady-state. This study aims at understanding dynamic back-mixing and related phenomena. Low filling levels of a feeder are investigated using a fluorescent tracer. These investigations prove an impact of the addition of material probably caused by a non-uniform draw-in of the screws and dead material in the hopper. In turn, the dead material accounts for up to 50 % of the material in the hopper. Possible evidence of dead zones at higher filling levels and in feeders from literature are discussed additionally. Steady-state models from literature are extended to represent the observations and back-mixing at all filling levels. This extension reduces the root-mean-squared deviation of the model from the experimental data by 41%. The model predicts different responses to similar disturbances depending on the filling. This state-dependent back-mixing and the observed dead zones are challenging for diverting non-conforming material and material traceability. Therefore, these phenomena should be considered in selecting and operating feeders.

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.

Residence time distribution as a traceability method for lot changes in a pharmaceutical continuous manufacturing system

Residence time distribution (RTD) models were developed to track raw material lots and investigate batch transitions in a continuous manufacturing system. Two raw materials with similar physical properties (granular metformin and lactose) were identified via Principal Component Analysis (PCA) from a library of bulk material properties and used to simulate the switching of lots during production. In-line near-infrared (NIR) spectra were collected with the powder flowing through a chute in a continuous manufacturing system to monitor metformin and lactose concentration in step-change experiments with Partial Least Squares (PLS) models. RTD provided an understanding of raw material propagation through the continuous manufacturing system. Transition times between raw material changes were identified using the results of two multivariate approaches PLS and PCA. The methodology was implemented to discriminate the transition zone in a raw material change, contributing to design control strategies for acceptance and diverting mechanisms.

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.

Continuous blending monitored and feedback controlled by machine vision-based PAT tool

In a continuous powder blending process machine vision is utilized as a Process Analytical Technology (PAT) tool. While near-infrared (NIR) and Raman spectroscopy are reliable methods in this field, measurements become challenging when concentrations below 2 w/w% are quantified. However, an active pharmaceutical ingredient (API) with an intense color might be quantified in even lower quantities by images recorded with a digital camera. Riboflavin (RI) was used as a model API with orange color, its Limit of Detection was found to be 0.015 w/w% and the Limit of Quantification was 0.046 w/w% using a calibration based on the pixel value of images. A calibration for in-line measurement of RI concentration was prepared in the range of 0.2-0.45 w/w%, validation with UV/VIS spectrometry showed great accuracy with a relative error of 2.53 %. The developed method was then utilized for a residence time distribution (RTD) measurement in order to characterize the dynamics of the blending process. Lastly, the technique was applied in real-time feedback control of a continuous powder blending process. Machine vision based direct or indirect API concentration determination is a promising and fast method with a great potential for monitoring and control of continuous pharmaceutical processes.

Development of an RTD-Based Flowsheet Modeling Framework for the Assessment of In-Process Control Strategies

Continuous manufacturing (CM) is an emerging technology which can improve pharmaceutical manufacturing and reduce drug product quality issues. One challenge that needs to be addressed when adopting CM technology is material traceability through the entire continuous process, which constitutes one key aspect of control strategy. Residence time distribution (RTD) plays an important role in material traceability as it characterizes the material spreading through the process. The propagation of upstream disturbances could be predictively tracked through the entire process by convolution of the disturbance and the RTD. The present study sets up the RTD-based modeling framework in a commonly used process modeling environment, gPROMS, and integrates it with existing modules and built-in tools (e.g., parameter estimation). Concentration calculations based on the convolution integral requires access to historical stream property information, which is not readily available in flowsheet modeling platforms. Thus, a novel approach is taken whereby a partial differential equation is used to propagate and store historical data as the simulation marches forward in time. Other stream properties not modeled by an RTD are determined in auxiliary modules. To illustrate the application of the framework, an integrated RTD-auxiliary model for a continuous direct compression manufacturing line was developed. An excellent agreement was found between the model predictions and experiments. The validated model was subsequently used to assess in-process control strategies for feeder and material traceability through the process. Our simulation results show that the employed modeling approach facilitates risk-based assessment of the continuous line by promoting our understanding on the process.

Determination of Residence Time Distribution in a Continuous Powder Mixing Process With Supervised and Unsupervised Modeling of In-line Near Infrared (NIR) Spectroscopic Data

Successful implementation of continuous manufacturing processes requires robust methods to assess and control product quality in a real-time mode. In this study, the residence time distribution of a continuous powder mixing process was investigated via pulse tracer experiments using near infrared spectroscopy for tracer detection in an in-line mode. The residence time distribution was modeled by applying the continuous stirred tank reactor in series model for achieving the tracer (paracetamol) concentration profiles. Partial least squares discriminant analysis and principal component analysis of the near infrared spectroscopy data were applied to investigate both supervised and unsupervised chemometric modeling approaches. Additionally, the mean residence time for three powder systems was measured with different process settings. It was found that a significant change in the mean residence time occurred when comparing powder systems with different flowability and mixing process settings. This study also confirmed that the partial least squares discriminant analysis applied as a supervised chemometric model enabled an efficient and fast estimate of the mean residence time based on pulse tracer experiments.

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

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

Determining key parameters of continuous wet granulation for tablet quality and productivity: A case in ethenzamide

This paper aims to determine key parameters that affect tablet quality and productivity in continuous tablet manufacturing. Experiments were performed based on design of experiments using a continuous high-shear granulator and ethenzamide as the active pharmaceutical ingredient. To guide a systematic and comprehensive parameter analysis, a parameter framework was defined that comprised five input parameters on raw material properties and process parameters, 11 intermediate parameters on granule properties, and 11 output parameters on tablet quality and productivity. The interrelationships were analyzed statistically and were described as matrix functions. The liquid/solid ratio was the key parameter that affected circularity, density, and flowability as the granule properties, and disintegration and dissolution as the tablet quality. The maximum acceptable manufacturing rate that governs productivity was also affected by the liquid/solid ratio. Circularity was found to affect disintegration and dissolution. This result was specific to the setup of the study, but suggested development opportunities for a new process analytical technology system/quality-by-design application based on circularity. In addition, practical findings were obtained as follows: (1) high-speed manufacturing favored a lower liquid/solid ratio, and (2) high circularity slowed down disintegration/dissolution. This obtained knowledge will enhance the applicability of continuous technology in an actual manufacturing environment.

Model-based approach to the design of pharmaceutical roller-compaction processes

This work presents a new model based approach to process design and scale-up within the same equipment of a roller compaction process. The prediction of the operating space is not performed fully in-silico, but uses low-throughput experiments as input. This low-throughput data is utilized in an iterative calibration routine to describe the behavior of the powder in the roller compactor and improves the predictive quality of the mechanistic models at low and high-throughput. The model has been validated with an experimental design of experiments of two ibuprofen formulations. The predicted sweet spots in the operating space are in good agreement with the experimental results.

Explicit Residence Time Distribution of a Generalised Cascade of Continuous Stirred Tank Reactors for a Description of Short Recirculation Time (Bypassing)

The tanks-in-series model (TIS) is a popular model to describe the residence time distribution (RTD) of non-ideal continuously stirred tank reactors (CSTRs) with limited back-mixing. In this work, the TIS model was generalised to a cascade of n CSTRs with non-integer non-negative n. The resulting model describes non-ideal back-mixing with n > 1. However, the most interesting feature of the n-CSTR model is the ability to describe short recirculation times (bypassing) with n < 1 without the need of complex reactor networks. The n-CSTR model is the only model that connects the three fundamental RTDs occurring in reactor modelling by variation of a single shape parameter n: The unit impulse at n→0, the exponential RTD of an ideal CSTR at n = 1, and the delayed impulse of an ideal plug flow reactor at n→∞. The n-CSTR model can be used as a stand-alone model or as part of a reactor network. The bypassing material fraction for the regime n < 1 was analysed. Finally, a Fourier analysis of the n-CSTR was performed to predict the ability of a unit operation to filter out upstream fluctuations and to model the response to upstream set point changes.

Integrated continuous manufacturing in pharmaceutical industry: current evolutionary steps toward revolutionary future

Continuous manufacturing (CM) has the potential to provide pharmaceutical products with better quality, improved yield and with reduced cost and time. Moreover, ease of scale-up, small manufacturing footprint and on-line/in-line monitoring and control of the process are other merits for CM. Regulating authorities are supporting the adoption of CM by pharmaceutical manufacturers through issuing proper guidelines. However, implementation of this technology in pharmaceutical industry is encountered by a number of challenges regarding the process development and quality assurance. This article provides a background on the implementation of CM in pharmaceutical industry, literature survey of the most recent state-of-the-art technologies and critically discussing the encountered challenges and its future prospective in pharmaceutical industry.

Material tracking in a continuous direct capsule-filling process via residence time distribution measurements

Continuous production of pharmaceuticals requires traceability from the raw material to the final dosage form. With that regard, understanding the residence time distribution (RTD) of the whole process and its unit operations is crucial. This work describes a structured approach to characterizing and modelling of RTDs in a continuous blender and a tamping pin capsule filling machine, including insights into data processing. The parametrized RTD models were interconnected to model a continuous direct capsule-filling process, showing the batch transition as well as the propagation of a 2 min feed disturbance throughout the process. Various control strategies were investigated in-silico, aiding in the selection of optimal material diversion point to minimize the material waste. Additionally, the RTD models can facilitate process design and optimization. In this work, adaptions to the capsule filling machine were made and their influence on the RTD was examined to achieve an optimal machine setup.