Continuous Pharmaceutical Manufacturing Research Articles

Development and Application of Control Concepts for Twin-Screw Wet Granulation in the ConsiGmaTM-25: Part 1 Granule Composition

Continuous manufacturing of pharmaceuticals offers several benefits, such as increased production efficiency, enhanced product quality control, and lower environmental footprint. To fully exploit these benefits, standard operation mode (production processes with no or minimal disturbance mitigation measures) should be supported by adopting novel quality-by-control (QbC) methodologies. The paper at hand is the first part of a study focused on developing QbC algorithms for optimizing twin-screw wet granulation in the industrial manufacturing line ConsiGmaTM-25, specifically addressing granule composition.This work relies on previously established process-analytical-technology (PAT) equipment for real-time monitoring of the granule composition, i.e., the active pharmaceutical ingredient (API) and liquid content in wet granules. The developed control platform integrates model-based process control algorithms that aim to keep the API- and liquid content at target values through real-time adjustments of the process parameters. Furthermore, the platform integrates a digital operator assistant, which aims to detect and classify granulation disturbances and provides messages and instructions for the plant operator.The present manuscript systematically outlines all design steps from the development phase in the simulation environment to the final real system application and validation. The control platform’s performance is demonstrated through selected test scenarios on the ConsiGmaTM-25 manufacturing line. The obtained results indicate improved disturbance robustness and an increase in intermediate/final product quality (compared to conventional operating modes): The process control algorithms successfully maintained the API- and liquid content at target values despite process disturbances. Furthermore, realistic disturbances (feeder, pump, and material) were accurately detected and classified by the digital assistant algorithm. The information was provided through a user interface, offering real-time support for plant personnel.

Development and Application of Control Concepts for Twin-Screw Wet Granulation in the ConsiGmaTM-25: Part 2 Granule Size

Traditional operation modes, such as running the production processes at constant process settings or within a narrow design space, do not fully exploit the advantages of continuous pharmaceutical manufacturing. Integrating Quality by Control (QbC) algorithms as a standard component of production processes can mitigate the effect of diverse process disturbances and enhance process efficiency, particularly in terms of production costs and environmental footprint. This paper explores the potential of QbC algorithms for optimizing twin-screw wet granulation in the ConsiGmaTM-25 manufacturing line, specifically addressing granule size. It represents the second part of a study (Celikovic et al. (2024)) focused on granule composition.The concepts proposed in this work rely on process analytical technology (PAT) equipment for real-time monitoring of the granulation CQAs and a dynamic process model linking the granulation process parameters and the monitored CQAs. The granule size model identified via the local-linear-model-tree (LoLiMoT) algorithm is used to develop both a model predictive controller (MPC) and a granule size soft sensor. The MPC employs this model as a core component for selecting optimal granulation parameters to ensure the production of granules with target size. A digital operator assistant is developed to address disturbances that cannot be mitigated via MPC but can be eliminated by the plant operators.This study systematically outlines a workflow, starting from conceptualization, moving through simulation development, and finally ending with real-world application on a production line. In this final step, all proposed concepts are transferred to the ConsiGmaTM-25 manufacturing line, where their performance is validated through selected disturbance scenarios.

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

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

Digital design of an integrated purification system for continuous pharmaceutical manufacturing

In this work dynamic models of the continuous crystallization, filtration, deliquoring, washing, and drying steps are introduced, which are developed in the open-source pharmaceutical modeling tool PharmaPy. These models enable the simulation and digital design of an integrated continuous two-stage crystallization and filtration-drying carousel system. The carousel offers an intensified process that can manufacture products with tailored properties through optimal design and control. Results show that improved crystallization design enhances overall process efficiency by improving critical material attributes of the crystal slurry for downstream filtration and drying operations. The digital design of the integrated process achieves enhanced productivity while satisfying multiple design and product quality constraints. Additionally, the impact of model uncertainty on the optimal operating conditions is investigated. The findings demonstrate the systematic process development potential of PharmaPy, providing improved process understanding, design space identification, and optimized robust operation.

Advanced process automation of a pharmaceutical continuous wet granulation line: Perspectives on the application of a model predictive control from solid feeders to dryer

Pharmaceutical continuous manufacturing provides the appropriate tools (e.g. the understanding of process dynamics and appropriate and adaptable control strategy) in order to deal with Quality-by-Design expectations and even to the future smart manufacturing described by Quality-by-Control. Those tools form part of the given framework of the regulatory agencies led by an effective quality risk management. Soft sensors and control algorithms such as model predictive control are stepping stones for more agile processes and increased robustness by keeping the quality attributes of the final drug product in their acceptable ranges and by mitigating undesired events. The implementation of a model predictive control (MPC) system on a pharmaceutical continuous manufacturing plant for the wet granulation process is described. The control objectives and strategy are presented as well as the selected variables, the process dynamics identification, the MPC performance and its specific tuning where a commercial software has been used, setting the framework of this study. MPCs have been applied successfully on two pharmaceutical drug products (Diclofenac and Paracetamol): an accurate control of the API content and of the LOD was achieved in order to produce a constant quality of tablets on both drug products. In addition, some of the process parameters have been identified as mandatory to be step tested for each change of drug product, leading to a simplified MPC implementation.

Research progress and maturity assessment of continuous manufacturing of traditional Chinese medicine

The pharmaceutical manufacturing model is gradually changing from intermittent manufacturing to continuous manufacturing and intelligent manufacturing. This paper briefly reviewed the supervision and research progress in continuous pharmaceutical manufacturing in China and abroad and described the definition and advantages of continuous pharmaceutical manufacturing. The continuous manufacturing of traditional Chinese medicine(TCM) at the current stage was summarized in the following three terms: the enhancement of the continuity of intermittent manufacturing operations, the integration of continuous equipment to improve physical continuity between units, and the application of advanced process control strategies to improve process continuity. To achieve continuous manufacturing of TCM, the corresponding key technologies, such as material property characterization, process modeling and simulation, process analysis technology, and system integration, were analyzed from the process and equipment, respectively. It was proposed that the continuous manufacturing equipment system should have the characteristics of high speed, high response, and high reliability, "three high(H~3)" for short. Considering the characteristics and current situation of TCM manufacturing, based on the two dimensions of product quality control and production efficiency, a maturity assessment model for continuous manufacturing of TCM, consisting of operation continuity, equipment continuity, process continuity, and quality control continuity, was proposed to provide references for the application of continuous manufacturing technology for TCM. The implementation of continuous manufacturing or the application of key continuous manufacturing technologies in TCM can help to systematically integrate advanced pharmaceutical technology elements and promote the uniformity of TCM quality and the improvement of production efficiency.

An integrated data management and informatics framework for continuous drug product manufacturing processes: A case study on two pilot plants

The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. In this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.

Model predictive in vitro dissolution testing in pharmaceutical continuous manufacturing: An equivalence study

AbstractA predictive mathematical model for tablet dissolution was developed and implemented in an end‐to‐end integrated continuous manufacturing pilot plant. The tablets were produced for immediate release with a proprietary extrusion‐molding‐coating (EMC) unit operation. Besides the mass balance of API solute in the buffer solution, the model consisted of the dissolution, diffusion, and population balance of API particles in the swollen tablet, which was mainly controlled by the swelling and erosion of the polymeric excipient matrix. An equivalence study was investigated by comparing the model prediction to the experiments that were conducted according to USP42‐NF37 General Chapter <711> Dissolution, during which the drug dose level was varied in a range from 60 to 80 wt%. Consistent equivalence was demonstrated with the similarity factor f2 > 50 for all sampled tablets. Concluding remarks and industrial perspectives on model predictive in vitro dissolution testing are provided.

Study of the feeding performance of mesoporous silica in a loss-in-weight feeder

Accurate and reliable continuous feeding is essential for the continuous manufacturing of solid-dose pharmaceuticals to ensure the reproducible composition of the final product. Consistent feeding of cohesive powders is challenging and requires an understanding of the interplay between material properties and feeder configuration. This study presents the volumetric and gravimetric feeding behaviour of a cohesive pharmaceutical, excipient mesoporous silica, at low feed rates (< 0.6 kg/h) using a twin-screw loss-in-weight feeder. The study investigates how the screw pitch, screen type and gravimetric setpoint impact the feed factor and feed rate variability. Additionally, the flow function and bulk density of the fed and unfed silica samples were determined and related to the feeding process parameters. Volumetric experiments highlight inconsistent feed due to the poor screw flight filling at high screw speeds and for configurations with the larger pitch, coarse concave screw. Poor screw flight filling also resulted in an inverse relationship between screw speed and feed factor in volumetric mode. In gravimetric mode, feed variability, expressed as %RSD, was greatest at the lower gravimetric setpoints with minimal impact due to tooling configuration. Discharge screen set-up was identified as the parameter which had a significant effect on the bulk density and flowability of the powder post-feeding.

Advanced technology using supercritical fluid for particle production in pharmaceutical continuous manufacturing

Advanced technology using supercritical fluid for particle production in pharmaceutical continuous manufacturing

Investigation of granular dynamics in a continuous blender using the GPU-enhanced discrete element method

Continuous powder blending is an essential operation during continuous pharmaceutical manufacturing. However, the complex granular dynamics in the blender is still poorly understood. This study employs a graphic processor unit (GPU) enhanced discrete element method (DEM) to analyse the granular dynamics in a continuous blender. Numerical results indicate that only a small fraction of powder distributes in the upper region of the blender, while most of that distributes in the middle and lower regions. Besides, a higher impeller speed leads to a smaller hold-up mass and a shorter mean residence time. Interestingly, the maximum number of blade passes is achieved at an intermediate impeller speed. There are two distinct regimes during continuous blending: i) a shearing regime at low impeller speeds; and ii) a dynamic regime at high impeller speeds. This study demonstrates that the GPU-enhanced DEM can be a robust tool for analysing powder flow during continuous pharmaceutical manufacturing. • GPU-enhanced DEM analysis on the full-scale continuous blending is performed. • Impeller speed has a significant impact on the powder flow in the inclined blender. • At steady-state, powder mainly distributes in the middle and bottom zones of blender. • Maximum number of blade passes can be achieved at an intermediate impeller speed.

Continuous Manufacturing and Molecular Modeling of Pharmaceutical Amorphous Solid Dispersions.

Amorphous solid dispersions enhance solubility and oral bioavailability of poorly water-soluble drugs. The escalating number of drugs with poor aqueous solubility, poor dissolution, and poor oral bioavailability is an unresolved problem that requires adequate interventions. This review article highlights recent solubility and bioavailability enhancement advances using amorphous solid dispersions (ASDs). The review also highlights the mechanism of enhanced dissolution and the challenges faced by ASD-based products, such as stability and scale-up. The role of process analytical technology (PAT) supporting continuous manufacturing is highlighted. Accurately predicting interactions between the drug and polymeric carrier requires long experimental screening methods, and this is a space where computational tools hold significant potential. Recent advancements in data science, computational tools, and easy access to high-end computation power are set to accelerate ASD-based research. Hence, particular emphasis has been given to molecular modeling techniques that can address some of the unsolved questions related to ASDs. With the advancement in PAT tools and artificial intelligence, there is an increasing interest in the continuous manufacturing of pharmaceuticals. ASDs are a suitable option for continuous manufacturing, as production of a drug product from an ASD by direct compression is a reality, where the addition of multiple excipients is easy to avoid. Significant attention is necessary for ongoing clinical studies based on ASDs, which is paving the way for the approval of many new ASDs and their introduction into the market.

An audit of pharmaceutical continuous manufacturing regulatory submissions and outcomes in the US

Continuous manufacturing (CM) sends materials directly and continuously to the next step of a process, eliminating hold times and reducing processing times. The potential benefits of CM include improved product quality, reduced waste, lower costs, and increased manufacturing flexibility and agility. Some pharmaceutical manufacturers have been hesitant to adopt CM owing to perceived regulatory risks such as increased time to regulatory approval and market entry, more difficulty submitting postapproval changes, and higher inspectional scrutiny. An FDA self-audit of regulatory submissions in the U.S. examined the outcomes, at approval and during the product lifecycle, of continuous manufacturing applications as compared to traditional batch applications. There were no substantial regulatory barriers identified for CM applications related to manufacturing process changes or pre-approval inspections. CM applicants had relatively shorter times to approval and market as compared to similar batch applications, based on the mean or median times to approval (8 or 3 months faster) and marketing (12 or 4 months faster) from submission, translating to an estimated $171–537 M in early revenue benefit.

A benchmark simulator for quality-by-design and quality-by-control studies in continuous pharmaceutical manufacturing ‒ Intensified filtration-drying of crystallization slurries

This article introduces ContCarSim, a benchmark simulator for the development and testing of quality-by-design and quality-by-control strategies in the continuous intensified filtration-drying of paracetamol/ethanol slurries on a novel carousel technology, developed by Alconbury Weston Ltd (United Kingdom). The simulator is based on a detailed mechanistic mathematical modeling framework, and has been validated with filtration and drying experiments on a prototype equipment. A set of design- and control-relevant challenges to be addressed through ContCarSim are proposed. A case study is developed, to demonstrate the features of the simulator and its suitability to design, test and optimize the unit operation. ContCarSim is expected to promote the transition to end-to-end continuous pharmaceutical manufacturing and the adoption of closed-loop quality control by the pharmaceutical industry. The simulator can also be employed as a benchmark for data analytics and process monitoring studies.

Confidence intervals for point-of-stabilization of content uniformity.

Within the framework of continuous pharmaceutical manufacturing, we are interested in statistical modeling of the initial behavior of the production line. Assuming a gradually changing sequence of a suitable product quality characteristic (e.g., the content uniformity), we estimate the so-called point-of-stabilization (PoSt) and construct corresponding confidence regions based on appropriate asymptotic distributions and bootstrap. We investigate linear, quadratic, and nonlinear gradual change models both in homoscedastic and heteroscedastic setup. We propose a new nonlinear Emax gradual change model and show that it is applicable even if the true model is linear. Asymptotic distribution of the PoSt estimator is known only in a homoscedastic linear and quadratic model and, therefore, bootstrap approximations are used to construct one-sided PoSt confidence intervals.

Investigating the Trade-Off between Design and Operational Flexibility in Continuous Manufacturing of Pharmaceutical Tablets: A Case Study of the Fluid Bed Dryer

Market globalisation, shortened patent lifetimes and the ongoing shift towards personalised medicines exert unprecedented pressure on the pharmaceutical industry. In the push for continuous pharmaceutical manufacturing, processes need to be shown to be agile and robust enough to handle variations with respect to product demands and operating conditions. In this paper we examine the use of operational envelopes to study the trade-off between the design and operational flexibility of the fluid bed dryer at the heart of a tablet manufacturing process. The operating flexibility of this unit is key to the flexibility of the full process and its supply chain. The methodology shows that for the fluid bed dryer case study there is significant effect on flexibility of the process at different drying times with the optimal obtained at 700 s. The flexibility is not affected by the change in volumetric flowrate, but only by the change in temperature. Here the method used a black box model to show how it could be done without access to the full model equation set, as this often needs to be the case in commercial settings.

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.

A review on key aspects of wet granulation process for continuous pharmaceutical manufacturing of solid dosage oral formulations

Wet granulation process is a major unit operation in production of pharmaceuticals as solid dosage oral formulation. Indeed, granulation is used to improve the formulation properties such as flowability, compressibility, and so on for pharmaceutical manufacturing. Different types of granulations can be used in pharmaceutical manufacturing in which the selection of proper process depends on the operational conditions as well as formulation properties. In current decades, twin-screw wet granulation has been of paramount interest owing to its superior properties. Pharmaceutical manufacturing industry are trying to move towards continuous mode by which the efficiency can be improved compared to the batch mode. Therefore, development of continuous granulation process is of great importance. In this review article, various processing units applicable for wet granulation of pharmaceutical formulations for solid dosage forms are reviewed and discussed. The advantages and disadvantages of the processes are discussed and listed along with modeling approaches for simulation of process. The governing models and numerical schemes applicable for design of wet granulation are also critically discussed. The main focus is on wet granulation as this method has attracted much attention in pharmaceutical processing.

A Comparative Investment Analysis of Batch Versus Continuous Pharmaceutical Manufacturing Technologies.

PurposeThis study examines the risks and economics associated with investing in continuous (CM) versus conventional batch manufacturing for production of oral solid dosage pharmaceutical (OSD) products in the USA and abroad.MethodsA stochastic net present value (NPV) simulation of brand and generic manufacturing for new facilities is conducted comparing batch and continuous manufacturing processes leveraging actual industry financial revenue and cost information, and detailed engineering cost information of batch and CM manufacturing processes from a seminal manufacturing cost analysis of these two technologies.ResultsWhen looking at comparing investment in either CM or batch for a new U.S. facility, the results clearly suggest that the lower costs associated with CM technology should lead to both brand and generic companies investing in the more CM manufacturing technology. The simulation analysis demonstrated that under current U.S. tax rates, investing in batch technology at U.S. sites would be economically more attractive than investing in batch technology in China or India. Investing in CM technology in the USA under current tax rates results in positive expected net NPVs over batch technology investments in China or India for both brand and generic companies. U.S. tax policy has a material impact on whether pharmaceutical companies would decide to invest on the USA or not for their manufacturing.ConclusionsResults indicate that continuous manufacturing has the potential to make manufacturing of OSD pharmaceuticals more economically attractive in the USA than foreign manufacturing of those products.

Tracking raw material flow through a continuous direct compression line. Part II of II: Predicting dynamic changes in quality attributes of tablets due to disturbances in raw material properties using an independent residence time distribution model

Continuous manufacturing of pharmaceuticals promises many advantages regarding economics and quality. However, tracing deviating material in such processes is much more challenging than in batch processes due to axial back-mixing. The literature has proven the traceability of disturbances in the active pharmaceutical ingredient (API) by residence time distribution (RTD) models. Nevertheless, pharmaceutical quality attributes (QAs) and disturbances are not limited to the API content. The present study investigates different disturbances affecting the particle size in a direct compression by recording various QAs. The application of a tracer-based model demonstrates the generalizability of RTD models regarding tracing the propagation of nonconforming material. The model applied may predict the appearance of deviating material in the tablets accurately up to 60 s. However, nonlinear and dynamic effects complicate predicting values of the QAs. Due to dynamic effects, tablet masses deviate up to 2.5 percentage points from values measured in steady-state, at an acceptable total deviation of 7.5 %. Consequently, if other QAs are critical, the transfer of control concepts developed for the API content will be challenging due to such effects different from API-based disturbances. Additionally, higher tolerances for errors will be required considering those deviations.