Automated Tomographic Assessment of Structural Defects of Freeze-Dried Pharmaceuticals.

The topology and surface characteristics of lyophilisates significantly impact the stability and reconstitutability of freeze-dried pharmaceuticals. Consequently, visual quality control of the product is imperative. However, this procedure is not only time-consuming and labor-intensive but also expensive and prone to errors. In this paper, we present an approach for fully automated, non-destructive inspection of freeze-dried pharmaceuticals, leveraging robotics, computed tomography, and machine learning.

A Novel image processing technique for weighted particle size distribution assessment.

The objective of the study was to create a reliable method that could be used to evaluate the particle size distribution of samples and pre-mixes in real-world situations, particularly those consisting of typical formulation blends. The goal was to use this method to assess the uniformity of the samples and ensure that they met the required quality standards. The researchers aimed to create a method that could be easily incorporated into the manufacturing process, providing a practical and efficient solution. This study demonstrates the use of ImageJ software to analyze the particle size distribution (PSD) of powders. The technique produces qualitative data from microscopy images and quantitative data from analysis of parameters including average diameter, D10, D50, D90, and standard deviation. The method was tested with various treatments, showing differentiating outcomes in all cases. The alternate technique provides a rapid and cost-effective method for PSD analysis, surpassing the limitations of sieve analysis. Extensive testing of the method, using a variety of sample types, including typical formulation blends, was performed. The results suggest that the method can effectively assess the morphology of changing materials during batch manufacturing and characterize uniformity in blends. The methodology has the capability to identify attributes related to PSD that are typically required to be monitored during manufacturing. The technique allows for accurate and reliable quantification of the attributes through image capture technology. The technique has future potential and has important implications for material science, powder rheology, pharmaceutical formulation development, and continual process monitoring.

[Figure: see text]A Novel Image Processing Technique for Weighted Particle Size Distribution Assessment.

Development of inert coatings to prevent drug retention in 3D-printed diffusion cells.

Diffusion cells play a crucial role in the pharmaceutical and cosmetic fields by assessing the release and permeation of active pharmaceutical ingredients across membranes. However, commercially available glass-based devices, such as Franz diffusion cells, are expensive and fragile. The emergence of three-dimensional (3D) printing technology enables the creation of diffusion cells with cost-effective polymeric materials and resins, offering exceptional precision and custom geometries. Nonetheless, there are challenges associated with interactions between 3D printing materials and drug molecules. This work aimed to develop inert coatings for 3D-printed diffusion models. Diffusion devices were designed and 3D-printed with a stereolithography (SLA) 3D printer, and different coatings were applied. Then, two model drugs were used to evaluate drug retention by coated devices. Among the tested coatings, one of them showed great potential in preventing drug retention and was selected for subsequent experiments with different drugs and conditions. Finally, voriconazole eyedrops were used to confirm the viability of 3D-printed Franz diffusion cells as a drug release diffusion model. The favourable results obtained with the coating promote the use of 3D printing as a cost-effective manufacturing technology, capable of producing diffusion cells tailored to specific study requirements.

Development of novel 3D printable inks for protein delivery.

The application of 3D printing technology in the delivery of macromolecules, such as proteins and enzymes, is limited by the lack of suitable inks. In this study, we report the development of novel inks for 3D printing of constructs containing proteins while maintaining the activity of the proteins during and after printing. Different ink formulations containing Pluronic F-127 (20-35 %, w/v), trehalose (2-10 %, w/v) or mannitol, poly (ethylene glycol) diacrylate (PEGDA) (0 or 10 %, w/w), and diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO, 0 or 0.2 mg/mL) were prepared for 3D-microextrusion printing. The F2 formulation that contained ß-galactosidase (ß-gal) as a model enzyme, Pluronic F-127 (30 %), and trehalose (10 %) demonstrated the desired viscosity, printability, and dose flexibility. The shear-thinning property of the F2 formulation enabled the printing of ß-gal containing constructs with a good peak force during extrusion. After 3D printing, the enzymatic activity of the ß-gal in the constructs was maintained for an extended period, depending on the construct design and storage conditions. For instance, there was a 50 % reduction in ß-gal activity in the two-layer constructs, but only a 20 % reduction in the four-layer construct (i.e., 54.5 ± 1.2 % and 82.7 ± 9.9 %, respectively), after 4 days of storage. The ß-gal activity in constructs printed from the F2 formulation was maintained for up to 20 days when stored in sealed bags at room temperatures (21 ± 2 °C), but not when stored unsealed in the same conditions (e.g., ∼60 % activity loss within 7 days). The ß-gal from constructs printed from F2 started to release within 5 min and reached 100 % after 20 min. With the design flexibility offered by the 3D printing, the ß-gal release from the constructs was delayed to 3 h by printing a backing layer of ß-gal-free F5 ink on the constructs printed from the F2 ink. Finally, ovalbumin as an alternative protein was also incorporated in similar ink compositions. Ovalbumin exhibited a release profile like that of the ß-gal, and the release can also be modified with different shape design and/or ink composition. In conclusion, ink formulations that possess desirable properties for 3D printing of protein-containing constructs while maintaining the protein activity during and after printing were developed.

A modified Kushner-Moore approach to characterising small-scale blender performance impact on tablet compaction.

Continuous Direct Compaction (CDC) has emerged as a promising route towards producing solid dosage forms while reducing material, development time and energy consumption. Understanding the response of powder processing unit operations, especially blenders, is crucial. There is a substantial body of work around how lubrication via batch blender operation affects tablet critical quality attributes such as hardness and tensile strength. But, aside from being batch operations, the design of these blenders is such that they operate with low-shear, low-intensity mixing at Froude number values significantly below 0.4 (Froude number Fr being the dimensionless ratio of inertial to gravitational forces). The present work explores the performance of a mini-blender which has a fundamentally different mode of operation (static vessel with rotating blades around a mixing shaft as opposed to rotating vessel with no mixing shaft). This difference allows a substantially wider operating range in terms of speed and shear (and Fr values). The present work evaluates how its performance compares to other blenders studied in the literature. Tablet compaction data from blends produced at various intensities and regimes of mixing in the mini-blender follow a common trajectory. Model equations from literature are suitably modified by inclusion of the Froude number Fr, but only for situations where the Froude number was sufficiently high (1 < Fr). The results suggest that although a similar lubrication extent plateau is eventually reached it is the intensity of mixing (i.e. captured using the Froude number as a surrogate) which is important for the lubrication dynamics in the mini-blender, next to the number of revolutions. The degree of fill or headspace, on the other hand, is only crucial to the performance of common batch blenders. Testing using alternative formulations shows the same common trend across mixing intensities, suggesting the validity of the approach to capture lubrication dynamics for this system.

Optimization of stereolithography 3D printing of microneedle micro-molds for ocular drug delivery.

Microneedles (MN) have emerged as an innovative technology for drug delivery, offering a minimally invasive approach to administer therapeutic agents. Recent applications have included ocular drug delivery, requiring the manufacture of sub-millimeter needle arrays in a reproducible and reliable manner. The development of 3D printing technologies has facilitated the fabrication of MN via mold production, although there is a paucity of information available regarding how the printing parameters may influence crucial issues such as sharpness and penetration efficacy. In this study, we have developed and optimized a 3D-printed MN micro-mold using stereolithography (SLA) 3D printing to prepare a dissolving ocular MN patch. The effects of a range of parameters including aspect ratio, layer thickness, length, mold shape and printing orientation have been examined with regard to both architecture and printing accuracy of the MN micro-mold, while the effects of printing angle on needle fidelity was also examined for a range of basic shapes (conical, pyramidal and triangular pyramidal). Mechanical strength and in vitro penetration of the polymeric (PVP/PVA) MN patch produced from reverse molds fabricated using MN with a range of shapes and height, and aspect ratios were assessed, followed by ex vivo studies of penetration into excised scleral and corneal tissues. The optimization process identified the parameters required to produce MN with the sharpest tips and highest dimensional fidelity, while the ex vivo studies indicated that these optimized systems would penetrate the ocular tissue with minimal applied pressure, thereby allowing ease of patient self-administration.

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.

Implementation of mechanistic modeling and global sensitivity analysis (GSA) for design, optimization, and scale-up of a roller compaction process.

The pharmaceutical industry has been shifting towards the application of mechanistic modeling to improve process robustness, enable scale-up, and reduce time to market. Modeling approaches have been well-developed for processes such as roller compaction, a continuous dry granulation process. Several mechanistic models/approaches have been documented with limited application to high drug-loaded formulations. In this study, the Johanson model was employed to optimize roller compaction processing and guide its scale-up for a high drug loaded formulation. The model was calibrated using a pilot-scale Minipactor and was validated for a commercial-scale Macropactor. Global sensitivity analysis (GSA) was implemented to determine the impact of process parameter variations (roll force, gap, speed) on a quality attribute [solid fraction (SF)]. The throughput method, which estimates SF values of ribbons using granule production rate, was also studied. The model predicted SF values for all 14 Macropactor batches within ± 0.04 SF. The throughput method estimated SF with ± 0.06 SF for 7 out of 11 batches. GSA confirmed that roll force had the largest impact on SF. This case study represents a process modeling approach to build quality into the products/processes and expands the use of mechanistic modeling during drug product development.

Effect of basket mesh size on the hydrodynamics of a partially filled (500 mL) USP rotating basket dissolution testing Apparatus 1.

The USP Rotating Basket Dissolution Testing Apparatus 1 is listed in the USP as one of the tools to assess dissolution of oral solid dosage forms. Baskets of different mesh sizes can be used to differentiate between dissolution profiles of different formulations. Here, we used Particle Image Velocimetry (PIV) to study the hydrodynamics of the USP Apparatus 1 using baskets with different mesh openings (10-, 20- and 40-mesh) revolving at 100 rpm, when the vessel was filled with 500 mL. The velocity profiles throughout the liquid were found to vary significantly using baskets of different mesh sizes, typically increasing with increased size of the opening of the basket mesh, especially for axial and radial velocities. This, in turn, resulted in a significantly different flow rate through the basket, which can be expected to significantly impact the dissolution rate of the drug product. A comparison between the results of this work with those of a previous study with a 900-mL fill volume (Sirasitthichoke et al., Intern. J. Pharmaceutics, 2021, 607: 120976), shows that although the hydrodynamics in the USP Apparatus 1 changed with fill level in the vessel, the flow rate through the basket was not significantly affected. This implies that tablets dissolving in the two systems would experience similar tablet-liquid medium mass transfer coefficients, and therefore similar initial dissolution rates, but different dissolution profiles because of the difference in volume.

Amorphous solid dispersion of a binary formulation with felodipine and HPMC for 3D printed floating tablets.

This study focuses on the combination of three-dimensional printing (3DP) and amorphous solid dispersion (ASD) technologies for the manufacturing of gastroretentive floating tablets. Employing hot melt extrusion (HME) and fused deposition modeling (FDM), the study investigates the development of drug-loaded filaments and 3D printed (3DP) tablets containing felodipine as model drug and hydroxypropyl methylcellulose (HPMC) as the polymeric carrier. Prior to fabrication, solubility parameter estimation and molecular dynamics simulations were applied to predict drug-polymer interactions, which are crucial for ASD formation. Physical bulk and surface characterization complemented the quality control of both drug-loaded filaments and 3DP tablets. The analysis confirmed a successful amorphous dispersion of felodipine within the polymeric matrix. Furthermore, the low infill percentage and enclosed design of the 3DP tablet allowed for obtaining low-density systems. This structure resulted in buoyancy during the entire drug release process until a complete dissolution of the 3DP tablets (more than 8 h) was attained. The particular design made it possible for a single polymer to achieve a zero-order controlled release of the drug, which is considered the ideal kinetics for a gastroretentive system. Accordingly, this study can be seen as an advancement in ASD formulation for 3DP technology within pharmaceutics.

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.

Accelerating Process Development and Product Formulation.

Currently, the lengthy time needed to bring new drugs to market or to implement postapproval changes causes multiple problems, such as delaying patients access to new lifesaving or life-enhancing medications and slowing the response to emergencies that require new treatments. However, new technologies are available that can help solve these problems. The January 2023 NIPTE pathfinding workshop on accelerating drug product development and approval included a session in which participants considered the current state of product formulation and process development, barriers to acceleration of the development timeline, and opportunities for overcoming these barriers using new technologies. The authors participated in this workshop, and in this article have shared their perspective of some of the ways forward, including advanced manufacturing techniques and adaptive development. In addition, there is a need for paradigm shifts in regulatory processes, increased pre-competitive collaboration, and a shared strategy among regulators, industry, and academia.

Premix technologies for drug delivery: manufacturing, applications, and opportunities in regulatory filing.

Active pharmaceutical ingredients (APIs) and excipients can be carefully combined in premix-based materials before being added to dosage forms, providing a flexible platform for the improvement of drug bioavailability, stability, and patient compliance. This is a promising and transformative approach in novel and generic product development, offering both the potential to overcome challenges in the delivery of complex APIs and viable solutions for bypassing patent hurdles in generic product filing. We discuss the different types of premixes; manufacturing technologies such as spray drying, hot melt extrusion, wet granulation, co-crystal, co-milling, co-precipitation; regulatory filing opportunities; and major bottlenecks in the use of premix materials in different aspects of pharmaceutical product development.

[Application of process analysis technology in traditional Chinese medicine manufacturing industry].

In the traditional Chinese medicine(TCM) manufacturing industry, quality control determines the safety, effectiveness, and quality stability of the final product. The traditional quality control method generally carries out sampling off-line testing of drugs after the end of the batch production, which is incomprehensive, and it fails to find the problems in the production process in time. Process analysis technology(PAT) uses process testing, mathematical modeling, data analysis, and other technologies to collect, analyze, feedback, control, and continuously improve the critical quality attributes(CQA) in all aspects of the production of TCM preparations in real time. The application of PAT in the TCM manufacturing industry is one of the research hotspots in recent years, which has the advantages of real-time, systematic, non-destructive, green, and rapid detection for the production quality control of TCM preparations. It can effectively ensure the stability of the quality of TCM preparations, improve production efficiency, and play a key role in the study of the quantity and quality transfer law of TCM. Commonly used PAT includes near-infrared spectroscopy, Raman spectroscopy, online microwave, etc. In addition, the establishment of an online detection model by PAT is the key basic work to realize intelligent manufacturing in TCM production. Obtaining real-time online detection data through PAT and establishing a closed-loop control model on this basis are a key common technical difficulty in the industry. This paper adopted systematic literature analysis to summarize the relevant Chinese and foreign literature, policies and regulations, and production applications, and it introduced the development trend and practical application of PAT, so as to provide references for accelerating the application of PAT in the TCM manufacturing industry, the intelligent transformation and upgrading, and high-quality development of the TCM industry.

The potential of three-dimensional printing for pediatric oral solid dosage forms.

Pediatric patients often require individualized dosing of medicine due to their unique pharmacokinetic and developmental characteristics. Current methods for tailoring the dose of pediatric medications, such as tablet splitting or compounding liquid formulations, have limitations in terms of dosing accuracy and palatability. This paper explores the potential of 3D printing as a solution to address the challenges and provide tailored doses of medication for each pediatric patient. The technological overview of 3D printing is discussed, highlighting various 3D printing technologies and their suitability for pharmaceutical applications. Several individualization options with the potential to improve adherence are discussed, such as individualized dosage, custom release kinetics, tablet shape, and palatability. To integrate the preparation of 3D printed medication at the point of care, a decentralized manufacturing model is proposed. In this setup, pharmaceutical companies would routinely provide materials and instructions for 3D printing, while specialized compounding centers or hospital pharmacies perform the printing of medication. In addition, clinical opportunities of 3D printing for dose-finding trials are emphasized. On the other hand, current challenges in adequate dosing, regulatory compliance, adherence to quality standards, and maintenance of intellectual property need to be addressed for 3D printing to close the gap in personalized oral medication.

Exploring the Potential of Artificial Intelligence as a Facilitating Tool for Formulation Development in Fluidized Bed Processor: a Comprehensive Review.

This in-depth study looks into how artificial intelligence (AI) could be used to make formulation development easier in fluidized bed processes (FBP). FBP is complex and involves numerous variables, making optimization challenging. Various AI techniques have addressed this challenge, including machine learning, neural networks, genetic algorithms, and fuzzy logic. By integrating AI with experimental design, process modeling, and optimization strategies, intelligent systems for FBP can be developed. The advantages of AI in this context include improved process understanding, reduced time and cost, enhanced product quality, and robust formulation optimization. However, data availability, model interpretability, and regulatory compliance challenges must be addressed. Case studies demonstrate successful applications of AI in decision-making, process outcome prediction, and scale-up. AI can improve efficiency, quality, and cost-effectiveness in significant ways. Still, it is important to think carefully about data quality, how easy it is to understand, and how to follow the rules. Future research should focus on fully harnessing the potential of AI to advance formulation development in FBP.

Quality by Design Considerations for Drop-on-Demand Point-of-Care Pharmaceutical Manufacturing of Precision Medicine.

Distributed and point-of-care (POC) manufacturing facilities enable an agile pharmaceutical production paradigm that can respond to localized needs, providing personalized and precision medicine. These capabilities are critical for narrow therapeutic index drugs and pediatric or geriatric dosing, among other specialized needs. Advanced additive manufacturing, three-dimensional (3D) printing, and drop-on-demand (DoD) dispensing technologies have begun to expand into pharmaceutical production. We employed a quality by design (QbD) approach to identify critical quality attributes (CQAs), critical material attributes (CMAs), and critical process parameters (CPPs) of a POC pharmaceutical manufacturing paradigm. This theoretical framework encompasses the production of active pharmaceutical ingredient (API) "inks" at a centralized facility, which are distributed to POC sites for DoD dispensing into/onto delivery vehicles (e.g., orodispersible films, capsules, single liquid dose vials). Focusing on the POC dispensing/dosing processes, QbD considerations and cause-and-effect analyses identified the dispensed API quantity and solid-state form (CQAs), as well as the nozzle diameter, system pressure channel, and number of drops dispensed (CPPs) for detailed investigation. Final assay quantification and content uniformity CQAs were measured from demonstrative levothyroxine sodium single-dose liquid vials of glycerin/water, meeting the standard acceptance values. Each POC facility is unlikely to maintain full quality control laboratory capabilities, requiring the development of appropriate atline or inline methods to ensure quality control. We developed control strategies, including atline ultraviolet-visible (UV-vis) verification of the API ink prior to dispensing, inline drop counting during dispensing, intermediate atline-dispensed volume checks, and offline batch confirmation by liquid chromatography-tandem mass spectrometry (LC-MS/MS) following production.

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.

Innovative Pharmaceutical Techniques for Paediatric Dosage Forms: A Systematic Review on 3D Printing, Prilling/Vibration and Microfluidic Platform.

The production of paediatric pharmaceutical forms represents a unique challenge within the pharmaceutical industry. The primary goal of these formulations is to ensure therapeutic efficacy, safety, and tolerability in paediatric patients, who have specific physiological needs and characteristics. In recent years, there has been a significant increase in attention towards this area, driven by the need to improve drug administration to children and ensure optimal and specific treatments. Technological innovation has played a crucial role in meeting these requirements, opening new frontiers in the design and production of paediatric pharmaceutical forms. In particular, three emerging technologies have garnered considerable interest and attention within the scientific and industrial community: 3D printing, prilling/vibration, and microfluidics. These technologies offer advanced approaches for the design, production, and customization of paediatric pharmaceutical forms, allowing for more precise dosage modulation, improved solubility, and greater drug acceptability. In this review, we delve into these cutting-edge technologies and their impact on the production of paediatric pharmaceutical forms. We analyse their potential, associated challenges, and recent developments, providing a comprehensive overview of the opportunities that these innovative methodologies offer to the pharmaceutical sector. We examine different pharmaceutical forms generated using these techniques, evaluating their advantages and disadvantages.

Ten years of the manufacturing classification system: a review of literature applications and an extension of the framework to continuous manufacture.

The MCS initiative was first introduced in 2013. Since then, two MCS papers have been published: the first proposing a structured approach to consider the impact of drug substance physical properties on manufacturability and the second outlining real world examples of MCS principles. By 2023, both publications had been extensively cited by over 240 publications. This article firstly reviews this citing work and considers how the MCS concepts have been received and are being applied. Secondly, we will extend the MCS framework to continuous manufacture. The review structure follows the flow of drug product development focussing first on optimisation of API properties. The exploitation of links between API particle properties and manufacturability using large datasets seems particularly promising. Subsequently, applications of the MCS for formulation design include a detailed look at the impact of percolation threshold, the role of excipients and how other classification systems can be of assistance. The final review section focusses on manufacturing process development, covering the impact of strain rate sensitivity and modelling applications. The second part of the paper focuses on continuous processing proposing a parallel MCS framework alongside the existing batch manufacturing guidance. Specifically, we propose that continuous direct compression can accommodate a wider range of API properties compared to its batch equivalent.