In-situ monitoring of in vitro drug release processes in tablets using optical coherence tomography.

Film-coated modified-release tablets are an important dosage form amenable to targeted, controlled, or delayed drug release in the specific region of the gastrointestinal (GI) tract. Depending on the film composition and interaction with the GI fluid, such coated products can modulate the local bioavailability, systemic absorption, protection as an enteric barrier, etc. Although the interaction of a dosage form with the surrounding dissolution medium is vital for the resulting release behavior, the underlying physicochemical phenomena at the film and core levels occurring during the drug release process have not yet been well described. In this work, we attempted to tackle this limitation by introducing a novel in vitro test based on optical coherence tomography (OCT) that allows an in-situ investigation of the sub-surface processes occurring during the drug release. Using a commercially available tablet based on osmotic-controlled release oral delivery systems (OROS), we demonstrated the performance of the presented prototype in terms of monitoring the membrane thickness and thickness variability, the surface roughness, the core swelling behavior, and the porosity of the core matrix throughout the in vitro drug release process from OROS. The superior spatial (micron scale) and temporal (less than 10 ms between the subsequent tomograms) resolution achieved in the proposed setup provides an improved understanding of the dynamics inside the microstructure at any given time during the dissolution procedure with the previously unattainable resolution, offering new opportunities for the design and testing of patient-centric dosage forms.

Archaeosomes for Oral Drug Delivery: From Continuous Microfluidics Production to Powdered Formulations.

Archaeosomes were manufactured from natural archaeal lipids by a microfluidics-assisted single-step production method utilizing a mixture of di- and tetraether lipids extracted from Sulfolobus acidocaldarius. The primary aim of this study was to investigate the exceptional stability of archaeosomes as potential carriers for oral drug delivery, with a focus on powdered formulations. The archaeosomes were negatively charged with a size of approximately 100 nm and a low polydispersity index. To assess their suitability for oral delivery, the archaeosomes were loaded with two model drugs: calcein, a fluorescent compound, and insulin, a peptide hormone. The archaeosomes demonstrated high stability in simulated intestinal fluids, with only 5% of the encapsulated compounds being released after 24 h, regardless of the presence of degrading enzymes or extremely acidic pH values such as those found in the stomach. In a co-culture cell model system mimicking the intestinal barrier, the archaeosomes showed strong adhesion to the cell membranes, facilitating a slow release of contents. The archaeosomes were loaded with insulin in a single-step procedure achieving an encapsulation efficiency of approximately 35%. These particles have been exposed to extreme manufacturing temperatures during freeze-drying and spray-drying processes, demonstrating remarkable resilience under these harsh conditions. The fabrication of stable dry powder formulations of archaeosomes represents a promising advancement toward the development of solid dosage forms for oral delivery of biological drugs.

Improvement of a pharmaceutical powder mixing process in a tote blender via DEM simulations.

An industrial-scale pharmaceutical powder blending process was studied via discrete element method (DEM) simulations. A DEM model of two active pharmaceutical ingredient (API) components and a combined excipient component was calibrated by matching the simulated response in a dynamic angle of repose tester to the experimentally observed response. A simulation of the 25-minute bin blending process predicted inhomogeneous API distributions along the rotation axis of the blending container. These concentration differences were confirmed experimentally in a production-scale mixing trial using high-performance liquid chromatography analysis of samples from various locations in the bin. Several strategies to improve the blend homogeneity were then studied using DEM simulations. Reversing the direction of rotation of the blender every minute was found to negligibly improve the blending performance. Introducing a baffle into the lid at a 45° angle to the rotation axis sped up the axial mixing and resulted in a better final blend uniformity. Alternatively, rotating the blending container 90° around the vertical axis five minutes prior to the process end was predicted to reduce axial segregation tendencies.

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.

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.

Extending the Use of Optical Coherence Tomography to Scattering Coatings Containing Pigments.

Coating thickness is a critical quality attribute of many coated tablets. Functional coatings ensure correct drug release kinetics or protection from light, while non-functional coatings are generally applied for cosmetic reasons. Traditionally, coating thickness is assessed indirectly via offline methods, such as weight gain or diameter growth. In the past decade, several methods, including optical coherence tomography (OCT) and Raman spectroscopy, have emerged to perform in-line measurements of various subclasses of coating formulations. However, there are some obstacles. For example, when using OCT, a major challenge is scattering pigments, such as titanium dioxide and iron oxide, which make the interface between the coating and the tablet core difficult to detect. This work explores novel OCT image evaluation techniques using unsupervised machine learning to compute image metrics. Certain image metrics of highly scattering coatings are correlated with the tablet thickness, and hence indirectly with the coating thickness. The method was demonstrated using a titanium dioxide rich coating formulation. The results are expected to be applicable to other scattering coatings and will significantly broaden the applicability of OCT to at-line and in-line coating thickness measurements of a much larger class of coating formulations.

Liquid API feeding in pharmaceutical HME: Novel options in solid dosage manufacturing.

Hot melt extrusion (HME) is a common unit operation. It is broadly applicable in the pharmaceutical industry and can be implemented in a continuous manufacturing line. However, the conventional way of active pharmaceutical ingredient (API) feeding with a pre-blend consisting of a powdered API and a polymer does not allow the flexibility and agility to adjust the process parameters, which is generally an essential part of continuous manufacturing. In addition, this method of API feeding may result in the segregation of the individual powder components or agglomeration of highly cohesive materials, leading to an inhomogeneous API content in the extrudates, especially at low doses. In this study, the universal applicability of liquid side feeding in pharmaceutical HME was demonstrated using various APIs suspended or dissolved in water and fed as suspension or undersaturated, supersaturated, and highly concentrated solutions into anterior parts of the extruder. The extrudates were characterized in terms of their API content, residual moisture content, and solid-state of the API embedded in the polymer. The results show that a uniform API content without major deviations can be obtained via this method. Furthermore, the residual moisture content of the extrudates was low enough to have no significant influence on further processing of the final dosage form. In summary, this advanced way of feeding allows an accurate, flexible, and agile feeding of APIs, facilitating the production of personalized final dosage forms and a novel option to link the manufacturing of the drug substance and the drug product.

Evidence of Reliable Gastro-Resistance of Novel Enteric Ready-to-Fill Capsules Simplifying Pharmaceutical Manufacturing.

Developing delayed-release formulations for acid-sensitive actives can be a costly and time-consuming process. However, ready-to-fill functional capsules, such as EUDRACAP® can significantly mitigate these challenges. The in vitro performance of EUDRACAP® enteric was evaluated in two typical delayed-release scenarios: for diclofenac (a drug that can cause irritation to gastric mucosa), and for omeprazole (a drug susceptible to degradation due to the acidity of gastric fluid). The prototypes were tested in HCl 0.1N according to the USP <711> for at least 2 h and compared to commercial products. The results showed that the performance of EUDRACAP® was below LOD and in compliance with the requirements for drug release in acidic media (NMT 10%). Additionally, the impurities were evaluated after the acidic stress. The low total percentage of impurities of 0.44% for diclofenac (NMT 1.50%) and 0.22% for omeprazole (NMT 2.00%) indicates a very good protection by EUDRACAP®. A comprehensive comparative analysis of the in vitro performance clearly showed the acid protection capability of EUDRACAP® enteric capsules making them a serious alternative to existing enteric dosage forms alternatives. EUDRACAP® is an accessible solution both in large-scale industrial and smaller pharmacy settings. Offering increased accessibility, affordability, and convenience to manufacturers and consumers alike and leading to improved healthcare outcomes.

Prediction of dissolution performance of uncoated solid oral dosage forms via optical coherence tomography.

Real-time prediction of the dissolution behavior of solid oral dosage forms is an important research topic. Although methods such as Terahertz and Raman can provide measurements that can be linked to the dissolution performance, they typically require a longer time off-line for analysis. In this paper, we present a novel strategy for analyzing uncoated compressed tablets by means of optical coherence tomography (OCT). Using OCT, which is fast and in-line capable, makes it possible to predict the dissolution behavior of tablets based on images. In our study, OCT images were obtained of individual tablets from differently produced batches. Differences between tablets or batches in these images were hardly visible to the human eye. Advanced image analysis metrics were developed to quantify the light scattering behavior captured by the OCT probe and depicted in the OCT images. Detailed investigations assured the repeatability and robustness of the measurements. A correlation between these measurements and the dissolution behavior was established. A tree-based machine learning model was used to predict the amount of dissolved active pharmaceutical ingredient (API) at certain time points for each immediate-release tablet. Our results indicate that OCT, which is a non-destructive and real-time technology, can be used for in-line monitoring of tableting processes.

Single-tablet-scale direct-compression: An on-demand manufacturing route for personalized tablets.

Today's pharmaceutical industry is facing various challenges. Two of them are issues with supply chain security and the increasing demand for personalized medicine. Both can be addressed by increasing flexibility and a more decentralized approach to pharmaceutical manufacturing. In this study, we present a setup that provides flexibility in terms of supplied raw materials and the product, i.e., a direct-compression setup for personalized tablets operating at a single-tablet-scale. The performance of the implemented single-tablet-scale technology for dosing and mixing was investigated. In addition, an analysis of the critical quality attributes (CQAs) of immediate release ibuprofen and loratadine tablets was performed. The developed dosing device achieved acceptance rates of > 90 % for doses ≥ 20 mg for various pharmaceutical powders. Regarding the vibratory mixing process, a dependency of the performance on the applied frequencies and acceleration was observed, with 100 Hz and âˆ¼ 90 G performing best, yet still exhibiting varying mixing efficacies depending on the granular system. The tablets produced met U.S. Pharmacopeia requirements regarding mechanical stability and dissolution characteristics. Given these results, we consider the developed setup a proof of concept of a tool to provide personalized tablets to patients while minimizing the dependency on complex supply chains.

On the influence of raw material attributes on process behaviour and product quality in a continuous WET granulation tableting line.

Continuous manufacturing of oral solids is a complex process in which critical material attributes (CMAs), formulation and critical process parameters (CPPs) play a fundamental role. However, assessing their effect on the intermediate and final product's critical quality attributes (CQAs) remains challenging. The aim of this study was to tackle this shortcoming by evaluating the influence of raw material properties and formulation composition on the processability and quality of granules and tablets on a continuous manufacturing line. Powder-to-tablet manufacturing was performed using four formulations in various process settings. Pre-blends of different drug loadings (2.5 % w/w and 25% w/w) and two BCS classes (Class I and II) were continuously processed on an integrated process line ConsiGmaTM 25, including twin screw wet granulation, fluid bed drying, milling, sieving, in-line lubrication and tableting. The liquid-to-solid ratio and the granule drying time were varied to process granules under nominal, dry and wet conditions. It was shown that the BCS class and the drug dosage influenced the processability. Intermediate quality attributes, such as the loss on drying and the particle size distribution, directly correlated with the raw material's properties and process parameters. Process settings had a profound impact on the tablet's hardness, disintegration time, wettability and porosity.

A multi-step machine learning approach for accelerating QbD-based process development of protein spray drying.

This study proposes a new material-efficient multi-step machine learning (ML) approach for the development of a design space (DS) for spray drying proteins. Typically, a DS is developed by performing a design of experiments (DoE) with the spray dryer and the protein of interest, followed by deriving the DoE models via multi-variate regression. This approach was followed as a benchmark to the ML approach. The more complex the process and required accuracy of the final model is, the more experiments are necessary. However, most biologics are expensive and thus experiments should be kept to a minimum. Therefore, the suitability of using a surrogate material and ML for the development of a DS was investigated. To this end, a DoE was performed with the surrogate and the data used for training the ML approach. The ML and DoE model predictions were compared to measurements of three protein-based validation runs. The suitability of using lactose as surrogate was investigated and advantages of the proposed approach were demonstrated. Limitations were identified at protein concentrations >35 mg/ml and particle sizes of x50>6 µm. Within the investigated DS protein secondary structure was preserved, and most process settings, resulted in yields >75% and residual moisture <10 wt%.

Control oriented modeling of twin-screw granulation in the ConsiGmaTM-25 production plant.

ConsiGmaTM-25 is a continuous production plant integrating a twin-screw granulation, fluid bed drying, granule conditioning, and a tableting unit. The particle size distribution (PSD), active pharmaceutical ingredient (API) content, and liquid content of wet granules after twin-screw granulation affect the quality of intermediate and final products. This paper proposes methods for real-time monitoring of these quantities and control-oriented modeling of the granulator. The PSD of wet granules is monitored via an in-line process analytical technology (PAT) probe based on the spatial velocimetry principle. The algorithm for signal processing and evaluation of PSD characteristics is developed and applied to the acquired PSD data. A dynamic process model predicting PSD characteristics from granulation parameters is trained via the local linear model tree (LoLiMoT) approach. The experimental data required for the model training are collected via systematically designed excitation runs. Finally, the performance of the identified model is examined and verified by means of a new set of validation runs. Furthermore, an in-line PAT probe based on Raman spectroscopy is developed and integrated after the granulator. The API- and liquid content of produced wet granules are evaluated from the spectral data by means of chemometric modeling, and chemometric models are validated on a separate set of experimental data. The solutions proposed in this research can be used as a reliable (and necessary) basis for the development of advanced quality-by-design control concepts (e.g., PSD process control). Such concepts would ultimately improve the ConsiGmaTM-25 process performance in terms of robustness against disturbances and quality of intermediate and final products.

A DEM model to evaluate refill strategies of a twin-screw feeder.

Residence time distribution (RTD) modeling has proven to be a valuable tool for material tracking in continuous pharmaceutical processes. Refilling is thoroughly studied in the literature, but the main focus lies on the feed rate disturbances. The impact of the feeders themselves on intermixing of different material batches is often overlooked. Since the experimental methods to measure the RTD feeder discharging processes feeder are complex and material intensive, there is only limited experimental RTD data available in the literature. A DEM (discrete element method) simulation of a discharge of a twin-screw feeder shows that a large fraction of material that is moved and intermixed by the agitator. In addition to the intermixing, there is a tendency to discharge material located above the agitator early. In order to predict the behavior during multiple refill events, three models in order of increasing complexity are presented: (1) A simple exponential RTD assuming perfect intermixing of material batches; (2) a RTD model based on DEM results; (3) particle-level material tracking by extrapolation of the DEM results. All three of these models are able to predict the survival function of old material for late refills at low fill levels, however, earlier refills at high fill levels require more complex models to accurately represent the dynamics inside the hopper of the feeder.

Steady-state modeling of a new continuous API dryer: Reduced-order model and investigation of dryer performance.

In the present study, a reduced-order model is proposed to analyze a novel continuous dryer with an application in the pharmaceutical industry. The model was validated using process data from ibuprofen drying test runs, and the results were in good agreement with the experimental data. The test substance was an ibuprofen paste with an initial LOD of up to 30 w%. The simulations showed that the contact heat transfer coefficient can be correlated with the degree of wetness. Furthermore, a set of simulations was performed to analyze the influence of input parameters on the dryer's performance: i) the inlet air flow rate and ii) the inlet air temperature. The simulation results demonstrated that a variation in the inlet air temperature significantly affects the air temperature profile, while the inlet air flow rate has a minor effect. Besides, it was also established that the inlet solid LoD has the most considerable effect on the product quality (e.g., final solid moisture content). The results showed a deviation of less than 10% for the product LoD and the product temperature in most cases.

Pharmaceutical hot melt extrusion process development using QbD and digital twins.

Pharmaceutical product development guided by Quality by Design (QbD) is based on a complete understanding of the critical process parameters (CPPs) that are important for achieving the desired product critical quality attributes (CQAs). The effect of process settings, such as the screw speed, the throughput, the barrel temperature, and the screw configuration, is a well-known factor in the setup of pharmaceutical hot melt extrusion (HME) processes. A CPP that has not yet been extensively researched is the type of cross-section geometry of the screw elements. Typically, pharmaceutical extruders have double-flighted screw cross-sections, with some elements having a single- or triple-flighted element section. The exception is a NANO16 extruder from Leistritz, with all screw elements having a triple-flighted screw geometry. We investigated the process setup and scale-up to a double-flighted extruder experimentally and in silico via a digital twin. Two formulations were processed on a NANO16 extruder and virtually transferred to a ZSE18 double-flighted co-rotating twin-screw extruder. Detailed smoothed particle hydrodynamics simulations of all screw elements available from both extruders were performed, and their efficiency in conveying, pressure build-up, and power consumption were studied. Reduced-order 1D HME simulations, which were carried out to investigate the process space and scalability of both extruders, were experimentally validated.

Predicting powder feedability: A workflow for assessing the risk of flow stagnation and defining the operating space for different powder-feeder combinations.

Powder feeding is of critical importance for continuous manufacturing (CM) since next to in-process segregation it is the phenomenon primarily responsible for fluctuations in content uniformity and for content deviations in the final drug product. So far, feeding studies have focused on the characterization of specific feeders and the prediction of their performance for various materials. This work presents a more holistic approach, an early general assessment of the "feedability" of raw materials. With that regard, we established a workflow to: i) predict potential feeding issues, such as the flow stagnation in the hopper based on both the material attributes and the feeder's geometry; and ii) predict the feed rate space using various feeder/screw combinations for powders with an acceptable risk of hopper flow stagnation. Statistical models were developed for this twofold approach using a dataset comprising nine powders and four different feeders. In order to include different feeding equipment into the statistical models, novel equipment descriptors (capturing the effect of different geometries) and performance indicators (the end fill level as indicator for the risk of powder flow stagnation) were introduced. The application of the workflow was demonstrated for a simple formulation, and model validation was successfully performed for an additional powder that was not contained in the original dataset. Finally, the most relevant material attributes were identified, and reduced material characterization data sets were investigated in terms of effects on the model's prediction performance. The workflow presents a promising tool for initial process assessment in early-phase development.

Continuous Processing of Micropellets via Hot-Melt Extrusion.

Microparticulate drug delivery systems, e.g., micropellets (MPs), are used in a variety of pharmaceutical formulations such as suspensions, injectable systems, and capsules. MPs are currently manufactured mainly via batch, solvent-based processes, e.g., spray-drying and solvent evaporation-extraction. In this paper, we present a novel, solvent-free, continuous hot-melt extrusion-based approach with an inline cold pelletization step and the potential of unprecedented on-the-fly formulation changes, aiming at producing the smallest particles usable for injectable applications. A biodegradable, crystalline dispersion consisting of poly(DL-lactic acid) (PLA) filled with metformin as the model drug was chosen on purpose to elucidate the broad applicability of the process also to formulations with limited stretchability and complex pelletizability. Next to optical/statistical particle analyses and in-line high-speed camera investigations providing insights into the pelletization process, the injectability of the most promising micropellets was compared to that of one marketed formulation. Fast extrudate haul-off speeds and high numbers of pelletizer knives resulted in particles with a narrow and small particle size distribution with a d50 below 270 µm and aspect ratios close to 1. To omit protruding drug particles to ensure sufficient extrudate stretchability and allow for the smallest MPs, it was found that the d90 of the embedded drug must be significantly below the extrudate diameter. Upon adapting the syringe diameter, the produced micropellets revealed similar injectability parameters to the marketed formulation, showcasing the potential that the proposed setup has for the manufacturing of novel microparticulate formulations.

Can Liposomes Survive Inkjet Printing? The Effect of Jetting on Key Liposome Attributes for Drug Delivery Applications.

Purpose: Inkjet printing has the potential to enable novel personalized and tailored drug therapies based on liposome and lipid nanoparticles. However, due to the significant shear force exerted on the jetted fluids, its suitability for shear-sensitive materials such as liposomes, has not been verified. We have conducted a proof-of-concept study to examine whether the particle concentration and size distribution of placebo liposomes are affected by common inkjet/dispensing technologies. Methods: We have subjected three types of liposome-containing fluids ("inks") to two different commercial dispensing/jetting technologies, which are relevant to most drug printing approaches. The liposome jetting processes were observed in real-time using strobographic imaging techniques. The phospholipid concentrations and particle size distributions were determined before and after jetting via enzymatic colorimetric and dynamic light scattering methods, respectively. Results: Our results have shown that the jetting dynamics of the liposome inks are well predicted by the established inkjet printing regime map based on their physical properties and the jetting conditions. Importantly, although significant shear forces were confirmed during jetting, the liposome concentrations and particle size distributions in the collected samples remain largely unaffected. Conclusion: These findings, we believe, provide the essential proof-of-concept to encourage further development in this highly topical research area.

Analyzing the effect of using axial impellers in large-scale bioreactors.

In high-performance industrial fermentation processes, stirring and aeration may account for significant production costs. Compared to the widely applied Rushton impellers, axial-pumping impellers are known to yield a lower power draw and at the same time improve mixing. However, their lower gas dispersion capability requires stronger agitation, compromising these benefits. Diverse advanced impeller forms have been developed to cope with this challenge. We apply alternating radial and axial impellers and demonstrate strong gas dispersion and energy-efficient mixing for the first time in a large-scale (160 m3 ) bioreactor, based on experimental and computational fluid dynamics simulation data. For equal operating conditions (stirrer speed, aeration rate), this setup yielded similar gas hold-ups and better mixing times (35%) compared to a classical Rushton-only configuration. Hence, applying a radial impeller on an upper level for improving gas dispersion maintains the benefits of axial impellers in terms of reducing energy demand (up to 50%). We conclude that this effect is significant only at large-scale, when bubbles substantially expand due to the release of the hydrostatic pressure and have time to coalesce. The work thus extends current knowledge on mixing and aeration of large-scale reactors using classical impeller types.