Continuous Manufacturing Research Articles

A modeling and control framework for extraction processes

Many continuously operated pharmaceutical process routes have been presented recently. Most of these cover the synthesis of the active pharmaceutical ingredient (API) or solid dosage processing. However, the API purification is also gaining attraction. One widespread and waste-intensive unit operation for purification is the liquid–liquid-extraction (LLE). In continuous manufacturing active process control is required, especially for fast processes. Control concepts must be able to react on product quality deviations caused by disturbances or inadequate process settings in real-time. In this study different control concepts for LLE were developed for an extraction column and a multistage extraction. A universally applicable process model was derived and parametrized. The impact of several control concepts including different real-time measurements was evaluated in simulation for both LLE process routes. The results show that simulation tools based on proper process models can support the selection of the most efficient process route and of suitable control concepts.

Real-time release testing of in vitro dissolution and blend uniformity in a continuous powder blending process by NIR spectroscopy and machine vision

Continuous manufacturing is gaining increasing interest in the pharmaceutical industry, also requiring real-time and non-destructive quality monitoring. Multiple studies have already addressed the possibility of surrogate in vitro dissolution testing, but the utilization has rarely been demonstrated in real-time. Therefore, in this work, the in-line applicability of an artificial intelligence-based dissolution surrogate model is developed the first time. NIR spectroscopy-based partial least squares regression and artificial neural networks were developed and tested in-line and at-line to assess the blend uniformity and dissolution of encapsulated acetylsalicylic acid (ASA) – microcrystalline cellulose (MCC) powder blends in a continuous blending process. The studied blend is related to a previously published end-to-end manufacturing line, where the varying size of the ASA crystals obtained from a continuous crystallization significantly affected the dissolution of the final product. The in-line monitoring was suitable for detecting the variations in the ASA content and dissolution caused by the feeding of ASA with different particle sizes, and the at-line predictions agreed well with the measured validation dissolution curves (f2 = 80.5). The results were further validated using machine vision-based particle size analysis. Consequently, this work could contribute to the advancement of RTRT in continuous end-to-end processes.

KT-Biologics I (KTB1): A dynamic simulation model for continuous biologics manufacturing

The pharmaceutical industry's shift towards biological therapeutics has led to a transition from conventional batch production to continuous manufacturing. This change highlights the crucial need for effective process monitoring and control strategies to ensure consistent product quality and stability. Open-source benchmark simulation models have become essential tools for refining these processes, offering a platform for testing research hypotheses. This study uses the production of Lovastatin as a case study for continuous biopharmaceutical production. A comprehensive dynamic model covering upstream and downstream components provides an integrated perspective of the production process. The study introduces a basic control system emphasizing realistic sensor and actuator integration to enhance simulation accuracy. It assesses the benchmark through open-loop and closed-loop simulations, offering an in-depth analysis of the KTB1 model's dynamic response and functionality. KTB1 represents a model-driven decision support tool that enables the evaluation of monitoring strategies, process design, process optimization, and control for biomanufacturing.

A Cyber-Physical Production System for the Integrated Operation and Monitoring of a Continuous Manufacturing Train for the Production of Monoclonal Antibodies.

The continuous manufacturing of biologics offers significant advantages in terms of reducing manufacturing costs and increasing capacity, but it is not yet widely implemented by the industry due to major challenges in the automation, scheduling, process monitoring, continued process verification, and real-time control of multiple interconnected processing steps, which must be tightly controlled to produce a safe and efficacious product. The process produces a large amount of data from different sensors, analytical instruments, and offline analyses, requiring organization, storage, and analyses for process monitoring and control without compromising accuracy. We present a case study of a cyber-physical production system (CPPS) for the continuous manufacturing of mAbs that provides an automation infrastructure for data collection and storage in a data historian, along with data management tools that enable real-time analysis of the ongoing process using multivariate algorithms. The CPPS also facilitates process control and provides support in handling deviations at the process level by allowing the continuous train to re-adjust itself via a series of interconnected surge tanks and by recommending corrective actions to the operator. Successful steady-state operation is demonstrated for 55 h with end-to-end process automation and data collection via a range of in-line and at-line sensors. Following this, a series of deviations in the downstream unit operations, including affinity capture chromatography, cation exchange chromatography, and ultrafiltration, are monitored and tracked using multivariate approaches and in-process controls. The system is in line with Industry 4.0 and smart manufacturing concepts and is the first end-to-end CPPS for the continuous manufacturing of mAbs.

Deep learning based self-adaptive modeling of multimode continuous manufacturing processes and its application to rotary drying process

Deep learning based self-adaptive modeling of multimode continuous manufacturing processes and its application to rotary drying process

A Comprehensive Review of Distillation in the Pharmaceutical Industry

Distillation processes play a pivotal role in the pharmaceutical industry for the purification of active pharmaceutical ingredients (APIs), intermediates, and solvent recovery. This summary explores the fundamental principles governing distillation, including mass transfer and phase equilibrium concepts. It delves into various distillation methods employed in pharmaceutical engineering, encompassing fractional distillation, azeotropic/extractive distillation, steam distillation, vacuum distillation, membrane distillation, and molecular distillation. Recent advancements in distillation technology, such as process intensification, miniaturization, and integration with other separation processes, are highlighted. The current state of distillation in pharmaceutical engineering is discussed, addressing regulatory considerations, solvent selection, and recovery challenges. Future prospects emphasize the need for energy-efficient and sustainable processes, advanced distillation technologies, process modeling and optimization, continuous manufacturing integration, and interdisciplinary collaboration. These efforts aim to drive innovation and address the evolving needs of the pharmaceutical industry, ensuring the continued importance of distillation in the purification and separation of pharmaceutical compounds

Additive manufacture of programmable multi-matrix continuous carbon fiber reinforced gradient composites

Bio-inspired gradient materials and structures, including cartilage scaffolds, soft actuators, and sensors, demonstrate significant potential applications in the fields of biomedicine, robotics, and flexible electronics. This paper introduces a novel method for fabricating continuous fiber-reinforced gradient composites using additive manufacturing techniques. In-situ impregnation 3D printing of two distinct matrix materials and continuous fibers was realized utilizing a specially designed multi-channel nozzle. This allowed for the personalized distribution of matrix materials within the composite by controlling the extrusion rates. Employing polylactic acid (PLA) and thermoplastic polyurethane (TPU), which possess differing mechanical properties, as matrix materials, the study examined the tensile and three-point bending mechanical properties of continuous carbon fiber-reinforced PLA/TPU (CCFR-PLA/TPU) composites with varying ratios of the two matrix materials. Moreover, the ability to control the distribution of matrix materials enabled the tailoring of gradient composites. Additionally, this research investigated the fabrication and compression behavior of gradient thin-walled structures and lattice structures composed of CCFR-PLA/TPU composites. The findings suggest that this programmable, multi-material, continuous carbon fiber-reinforced composites additive manufacturing approach can fabricate composites with a broad spectrum of tunable mechanical properties.

Integrated Subsystems of Materials and Information Flow for Continuous Manufacturing of Coal and Steel

Abstract With the concept of Industry 4.0 production processes are moving towards autonomy and intelligence. Technologies equipped with artificial intelligence (AI) are involved into processes that are more and more digitized. Collaborative technologies are a feature of discrete processes. The automotive industry has achieved many successes in the process innovation towards smart factories. Other plants, such as smelters or coal mining are also striving to develop smart manufacturing with integrated computer systems to support processes. A continuous production is different from a discrete or batch production. Industry 4.0 concept is focused on discrete production (with high level of automation and robotization of manufacturing) meanwhile there is a gap in implementation of these approach in the continuous production. The objective of the publication is to prepare and design the integrated computer management system based on processes realized in coal and steel manufacturing. Coal and steel production are key elements in a chain of any industrial manufacturing e.g. automotive or machinery engineering. These processes are crucial in building of smart value chain. In our paper we present the structure of processes for the continuous production. Based the processes model we proposed the next steps to build the smart manufacturing for continuous production.

3D-Printed Flexible Microfluidic Health Monitor for In Situ Sweat Analysis and Biomarker Detection.

Wearable sweat biosensors have shown great progress in noninvasive, in situ, and continuous health monitoring to demonstrate individuals' physiological states. Advances in novel nanomaterials and fabrication methods promise to usher in a new era of wearable biosensors. Here, we introduce a three-dimensional (3D)-printed flexible wearable health monitor fabricated through a unique one-step continuous manufacturing process with self-supporting microfluidic channels and novel single-atom catalyst-based bioassays for measuring the sweat rate and concentration of three biomarkers. Direct ink writing is adapted to print the microfluidic device with self-supporting structures to harvest human sweat, which eliminates the need for removing sacrificial supporting materials and addresses the contamination and sweat evaporation issues associated with traditional sampling methods. Additionally, the pick-and-place strategy is employed during the printing process to accurately integrate the bioassays, improving manufacturing efficiency. A single-atom catalyst is developed and utilized in colorimetric bioassays to improve sensitivity and accuracy. A feasibility study on human skin successfully demonstrates the functionality and reliability of our health monitor, generating reliable and quantitative in situ results of sweat rate, glucose, lactate, and uric acid concentrations during physical exercise.

Optimizing Drug Development: Harnessing the Sustainability of Pharmaceutical Cocrystals.

Environmental impacts of the industrial revolution necessitate adoption of sustainable practices in all areas of development. The pharmaceutical industry faces increasing pressure to minimize its ecological footprint due to its significant contribution to environmental pollution. Over the past two decades, pharmaceutical cocrystals have received immense popularity due to their ability to optimize the critical attributes of active pharmaceutical ingredients and presented an avenue to bring improved drug products to the market. This review explores the potential of pharmaceutical cocrystals as an ecofriendly alternative to traditional solid forms, offering a sustainable approach to drug development. From reducing the number of required doses to improving the stability of actives, from eliminating synthetic operations to using pharmaceutically approved chemicals, from the use of continuous and solvent-free manufacturing methods to leveraging published data on the safety and toxicology, the cocrystallization approach contributes to sustainability of drug development. The latest trends suggest a promising role of pharmaceutical cocrystals in bringing novel and improved medicines to the market, which has been further fuelled by the recent guidance from the major regulatory agencies.

Co-rotating twin screw process for continuous manufacturing of solid crystal suspension: A promising strategy to enhance the solubility, permeation and oral bioavailability of Carvedilol

Background In the current work, co-rotating twin-screw processor (TSP) was utilized to formulate solid crystal suspension (SCS) of carvedilol (CAR) for enhancing its solubility, dissolution rate, permeation and bioavailability using mannitol as a hydrophilic carrier. Methods In-silico molecular dynamics (MD) studies were done to simulate the interaction of CAR with mannitol at different kneading zone temperatures (KZT). Based on these studies, the optimal CAR: mannitol ratios and the kneading zone temperatures for CAR solubility enhancement were assessed. The CAR-SCS was optimized utilizing Design-of-Experiments (DoE) methodology using the Box-Behnken design. Saturation solubility studies and in vitro dissolution studies were performed for all the formulations. Physicochemical characterization was performed using differential scanning calorimetry , Fourier transform infrared spectroscopy, X-ray diffraction studies, and Raman spectroscopy analysis. Ex vivo permeation studies and in vivo pharmacokinetic studies for the CAR-SCS were performed. Stability studies were performed for the DoE-optimized CAR-SCS at accelerated stability conditions at 40 ºC/ 75% RH for three months. Results Experimentally, the formulation with CAR: mannitol ratio of 20:80, prepared using a KZT of 120 ºC at 100 rpm screw speed showed the highest solubility enhancement accounting for 50-fold compared to the plain CAR. Physicochemical characterization confirmed the crystalline state of DoE-optimized CAR-SCS. In-vitro dissolution studies indicated a 6.03-fold and 3.40-fold enhancement in the dissolution rate of optimized CAR-SCS in pH 1.2 HCl solution and phosphate buffer pH 6.8, respectively, as compared to the pure CAR. The enhanced efficacy of the optimized CAR-SCS was indicated in the ex vivo and in vivo pharmacokinetic studies wherein the apparent permeability was enhanced 1.84-fold and bioavailability enhanced 1.50-folds compared to the plain CAR. The stability studies showed good stability concerning the drug content. Conclusions TSP technology could be utilized to enhance the solubility, bioavailability and permeation of poor soluble CAR by preparing the SCS.

Research and Validation of CF/PEEK-Based Truss Rod Crimping and Pultruding Process for On-Orbit Isoform Forming.

A crimping and pultruding forming process for truss rods using Carbon Fiber (CF)/Polyether-Ether-Ketone (PEEK) prepreg tape as the raw material is proposed to address the problem of continuous manufacturing of space trusses on orbit. The proposed process provides material rods for continuous truss manufacturing. Through numerical simulation and experimental verification, the effects of relevant parameters on the forming process are determined, an efficient method of rod curl pultrusion, in-rail, equal material forming is proposed, and the structural configuration of the rod curl pultrusion forming mold is determined. The equivalent macroscopic mechanical properties of unidirectional CF/PEEK prepreg strips are considered, and the rod-forming process is investigated. Rod samples with different process parameters are prepared, and several tests are conducted on them. The results show that the forming load pull is negatively correlated with the temperature at the same forming speed, and forming speed is positively correlated with the forming load pull at a certain temperature. Temperature and speed affect the surface quality of the rod, the density of the material filling, and the mechanical properties of the rod. The optimal forming process parameters are determined through numerical simulation and experimental verification. The developed molding technology has the advantages of high efficiency, low energy consumption, and high integration. It reduces manufacturing costs and improves manufacturing efficiency, so it can serve as a new and effective solution for the manufacturing of high-performance truss rods in the aerospace field.

Opportunities and Challenges: Process Raman for the Real-Time Release Testing (RTRT) of Extended-Release Formulations

The use of a process analytical technology has been demonstrated using near-infrared spectroscopy for continuous manufacturing of pharmaceutical formulations and is within the scope of the U.S. Food and Drug Administration's real-time release testing initiative. While effective for simple formulations, this preliminary study investigates whether such a spectroscopic surrogate application can replace pharmaceutical dissolution testing for extended-release formulations. In this study, we will assess the use of process Raman spectroscopy for real-time dissolution testing. Extended-release tablet formulations often accomplish the release rate delay through the addition of gelling agents. In this work, hydroxypropyl methylcellulose (HPMC) polymers were used to formulate extended-release niacin tablets. Process Raman spectroscopy was evaluated as a tool to effectively model dissolution profiles to determine if the optical technique has the ability to differentiate HPMC polymers from the background and be selective for the polymer type employed. Our preliminary work indicates that while Raman can effectively detect and monitor the niacin response of the tablet formulations, there are not enough unique spectral features between the different HPMC polymers to selectively resolve their responses. Additional measurements and chemometric analysis might suggest otherwise. Thus, for extended-release tablet applications with continuous manufacturing, further dissolution surrogate development is needed.

Electromagnetic drop-on-demand (DoD) technology as an innovative platform for amorphous solid dispersion production

Production of amorphous solid dispersions (ASDs) is an effective strategy to promote the solubility and bioavailability of poorly water soluble medicinal substances. In general, ASD is manufactured using a variety of classic and modern techniques, most of which rely on either melting or solvent evaporation. This proof-of-concept study is the first ever to introduce electromagnetic drop-on-demand (DoD) technique as an alternative solvent evaporation-based method for producing ASDs. Herein 3D printing of ASDs for three drug-polymer combinations (efavirenz-Eudragit L100-55, lumefantrine-hydroxypropyl methylcellulose acetate succinate, and favipiravir-polyacrylic acid) was investigated to ascertain the reliability of this technique. Polarized light microscopy, differential scanning calorimetry (DSC), X-ray powder diffraction (XRPD), and Fourier Transform Infrared (FTIR) spectroscopy results supported the formation of ASDs for the three drugs by means of DoD 3D printing, which significantly increases the equilibrium solubility of efavirenz from 0.03 ± 0.04 µg/ml to 21.18 ± 4.20 µg/ml, and the equilibrium solubility of lumefantrine from 1.26 ± 1.60 µg/ml to 20.21 ± 6.91 µg/ml. Overall, the reported findings show how this new electromagnetic DoD technology can have a potential to become a cutting-edge 3D printing solvent-evaporation technique for on-demand and continuous manufacturing of ASDs for a variety of drugs.

Continuous and Scalable Manufacture of Coal-Derived Hierarchical Porous Carbon Dominated with Mesopores for High Rate-Performance Supercapacitors

Continuous and Scalable Manufacture of Coal-Derived Hierarchical Porous Carbon Dominated with Mesopores for High Rate-Performance Supercapacitors

Experimental and numerical study on the pressure drop and flow pattern of liquid foam in a foam generator

In the present study, a comprehensive analysis of the pressure drop, flow pattern, and foam structural properties of vertical upward two-phase flow in a Kenics static foam generator of a compressed air foam system was carried out. A liquid with an extremely low surface tension (16.5 mN/m) was used for making the foam. The effects of the number of elements (number of individual elements combined into the mixer), aspect ratio (the ratio of length to diameter of each element), and transition angle (transition angle between elements) of the Kenics mixers on the pressure loss during foam generation were studied in detail over a wide range of Reynolds numbers through experiments and numerical simulation. A new pressure drop correlation was successfully obtained by scaling analysis and the modified Lockhart–Martinelli correlation was proposed to describe the pressure drop during foam generation. Furthermore, the experimental results validated the proposed correlation and exhibited good reliability and predictive accuracy. Finally, four flow patterns for foam generation in vertical pipes that were different from the classical gas–liquid two-phase flow patterns were proposed, and the relationships among the pressure drop, flow pattern, and foam structural properties were explored. This research expands the study of foam generation in vertical tubes containing a built-in spiral structure with low flow resistance. It provides new insights and guidance for developing continuous foam manufacturing.

Manufacturing process of liposomal Formation: A coarse-grained molecular dynamics simulation

A method of producing liposomes has been previously developed using a continuous manufacturing technology that involves a co-axial turbulent jet in co-flow. In this study, coarse-grained molecular dynamics (CG-MD) simulations were used to gain a deeper understanding of how the self-assembly process of liposomes is affected by the material attributes (such as the concentration of ethanol) and the process parameters (such as temperature), while also providing detailed information on a nano-scale molecular level. Specifically, the CG-MD simulations yield a comprehensive internal view of the structure and formation mechanisms of liposomes containing DPPC, DPPG, and cholesterol molecules. The importance of this work is that structural details on the molecular level are proposed, and such detail is not possible to obtain through experimental studies alone. The assessment of structural properties, including the area per lipid, diffusion coefficient, and order parameters, indicated that a thicker bilayer was observed at higher ethanol concentrations, while a thinner bilayer was present at higher temperatures. These conditions led to more water penetrating the interior of the bilayer and an unstable structure, as indicated by a larger contact area between lipids and water, and a higher coefficient of lipid lateral diffusion. However, stable liposomes were found through these evaluations at lower ethanol concentrations and/or lower process temperatures. Furthermore, the CG-MD model was further compared and validated with experimental and computational data including liposomal bilayer thickness and area per lipid measurements.

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.

Design Principles and Restrictions for Continuous Fiber-Reinforced Additive Manufacturing

Abstract In the development of innovative and high-performance products, design expertise is a critical factor. Nevertheless, novel manufacturing processes often frequently lack an accessible comprehensive knowledge base for product developers. To tackle this deficiency in the context of emerging additive manufacturing processes, substantial design knowledge has already been established. However, novel additive manufacturing processes like continuous fiber-reinforced material extrusion have often been disregarded, complicating the process's wider dissemination. The importance of design knowledge availability is paramount, as well as the need for user-friendly design knowledge preparation, standardized structure, and methodological support for accessing the accumulated knowledge with precision. In this paper, we present an approach that provides formalized opportunistic and restrictive design knowledge, ensuring both the comprehensive exploitation of process-specific potentials and the consideration of restrictive limitations in the construction of components. Opportunistic knowledge, presented as principle cards, is systematically derived, prepared, and made accessible. Moreover, an access system is developed to ensure the comprehensive utilization of process-specific potentials throughout the development process. Furthermore, we propose linking these principles through a synergy and conflict matrix, aiming to consider synergistic principles and identify potential conflicts at an early stage. Additionally, an approach to provide restrictive design knowledge in the form of a design rule catalog is proposed. The application of the knowledge system is demonstrated exemplarily using a weight-optimized component.

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.