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.

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.

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.

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.

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.

[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.

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.

Polymer Characteristics for Drug Layering on Particles Using a Novel Melt Granulation Technology, MALCORE®.

MALCORE®, a novel manufacturing technology for drug-containing particles (DCPs), relies on the melt granulation method to produce spherical particles with high drug content. The crucial aspect of particle preparation through MALCORE® involves utilizing polymers that dissolve in the melt component, thereby enhancing viscosity upon heating. However, only aminoalkyl methacrylate copolymer E (AMCE) has been previously utilized. Therefore, this study aims to discover other polymers and comprehend the essential properties these polymers need to possess. The results showed that polyvinylpyrrolidone (PVP) was soluble in the stearic acid (SA) melt component. FTIR examination revealed no interaction between SA and polymer. The phase diagram was used to analyze the state of the SA and polymer mixture during heating. It revealed the mixing ratio and temperature range where the mixture remained in a liquid state. The viscosity of the mixture depended on the quantity and molecular weight of the polymer dissolved in SA. Furthermore, the DCPs prepared using PVP via MALCORE® exhibited similar pharmaceutical properties to those prepared with AMCE. In conclusion, understanding the properties required for polymers in the melt granulation process of MALCORE® allows for the optimization of manufacturing conditions, such as temperature and mixing ratios, for efficient and consistent drug layering.

[Research practice and development direction of intelligent manufacturing of presonalized traditional Chinese medicine preparations].

In recent years, as people's living standards continue to improve, and the pace of life accelerates dramatically, the demand and quality of traditional Chinese medicine(TCM) services from patients continue to rise. As an essential supplement to the existing forms of TCM application, such as Chinese patent medicine, decoction, and formulated granules, presonalized TCM preparations is facing an increasing market demand. Currently, manual and semi-mechanized production are the primary production ways in presonalized TCM preparations. However, the production process control level is low, and digitalization and informatization need to be improved, which restricts the automated and intelligent development of presonalized TCM preparations. Presonalized TCM preparations faces a significant opportunity and challenge in integrating with intelligent manufacturing through research and development of intelligent equipment and core technology. This paper overviews the connotation and characteristics of intelligent manufacturing and summarizes the application of intelligent manufacturing technologies such as "Internet of things" "big data", and "artificial intelligence" in the TCM industry. Based on the innovative research and development model of "intelligent classification of TCM materials, intelligent decision making of prescription and process, and online control and intelligent production" of presonalized TCM preparations, the research practice and achievements from our research group in the field of intelligent manufacturing of presonalized TCM preparations are introduced. Ultimately, the paper proposes the direction for developing intelligent manufacturing of presonalized TCM preparations, which will provide a reference for the research and application of automation and intelligence of presonalized TCM preparations.

Analytical comparison between batch and continuous direct compression processes for pharmaceutical manufacturing using an innovative UV-Vis reflectance method and chemometrics.

Advancements in industrial technologies and the application of quality by design (QbD) guidelines are shifting the attention of manufacturers towards innovative production techniques. In the pharmaceutical field, there is a significant focus on the implementation of continuous processes, in which the production stages are carried out continuously, without the need to interrupt the process and store the production intermediates, as in traditional batch production. Such innovative production techniques also require the development of proper analytical methods able to analyze the products in-line, while still being processed. The present study aims to compare a traditional batch manufacturing process with an alternative continuous one. To this end, a real pharmaceutical formulation was used, substituting the active pharmaceutical ingredient (API) with riboflavin, at the concentration of 2 %w/w. Moreover, a direct and non-destructive analytical method based on UV-Vis reflectance spectroscopy was applied for the quantification of riboflavin in the final tablets, and compared with a traditional absorbance analysis. Good results were obtained in the comparison of both the two manufacturing processes and the two analytical methods, with R2 higher than 0.9 for all the calculated calibration models and predicted riboflavin concentrations that never significantly overcame the 15 % limits recommended by the pharmacopeia. The continuous production method demonstrated to be as reliable as the batch one, allowing to save time and money in the production step. Moreover, UV-Vis reflectance was proved to be an interesting alternative to absorption spectroscopy, which, with the proper technology, could be implemented for in-line process control.

Manufacturing process transfer to a 30 kg/h continuous direct compression line with real-time composition monitoring.

Transferring an existing marketed pharmaceutical product from batch to continuous manufacturing (CM) without changes in regulatory registration is a challenging task in the pharmaceutical industry. Continuous manufacturing can provide an increased production rate and better equipment utilisation while retaining key quality attributes of the final product. Continuous manufacturing necessitates the monitoring of critical quality attributes in real time by appropriate process analytical tools such as near infra-red (NIR) probes. The present work reports a successful transfer of an existing drug product from batch to continuous manufacturing process without changing the formulation. A key step was continuous powder blending, whose design and operating parameters including weir type, agitation rate, dynamic hold-up and residence time were systematically investigated with respect to process repeatability. A NIR-based multivariate data model for in-line composition monitoring has been developed and validated against an existing quality control method for measuring tablet content uniformity. A continuous manufacturing long-run with a throughput of 30 kg/h (approx. 128,000 tablets per hour), uninterrupted for 320 min, has been performed to test and validate the multivariate data model as well as the batch to continuous process transfer. The final disintegration and dissolution properties of tablets manufactured by the continuous process were found to be equivalent to those manufactured by the original batch process.

AI-driven design of customized 3D-printed multi-layer capsules with controlled drug release profiles for personalized medicine.

Personalized medicine aims to effectively and efficiently provide customized drugs that cater to diverse populations, which is a significant yet challenging task. Recently, the integration of artificial intelligence (AI) and three-dimensional (3D) printing technology has transformed the medical field, and was expected to facilitate the efficient design and development of customized drugs through the synergy of their respective advantages. In this study, we present an innovative method that combines AI and 3D printing technology to design and fabricate customized capsules. Initially, we discretized and encoded the geometry of the capsule, simulated the dissolution process of the capsule with classical drug dissolution model, and verified it by experiments. Subsequently, we employed a genetic algorithm to explore the capsule geometric structure space and generate a complex multi-layer structure that satisfies the target drug release profiles, including stepwise release and zero-order release. Finally, Two model drugs, isoniazid and acetaminophen, were selected and fused deposition modeling (FDM) 3D printing technology was utilized to precisely print the AI-designed capsule. The reliability of the method was verified by comparing the in vitro release curve of the printed capsules with the target curve, and the f2 value was more than 50. Notably, accurate and autonomous design of the drug release curve was achieved mainly by changing the geometry of the capsule. This approach is expected to be applied to different drug needs and facilitate the development of customized oral dosage forms.

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.

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.

Cracking the code: Spatial heterogeneity as the missing piece for modeling granular fluidized bed drying.

Pharmaceutical twin-screw wet granulation is a multifaceted and intricate process pivotal to drug product development. Accurate modeling of this process is indispensable for optimizing manufacturing parameters and ensuring product quality. The fluid bed dryer, an integral component of this granulation process, significantly influences the granular critical quality attributes. This study builds upon prior research by integrating experimental findings on granule segregation during fluid bed drying into an existing compartmental model, enhancing its predictive capabilities. An additional model layer on granule segregation behavior is composed and integrated into the existing model structure in this study. The added model compartment describes probability distributions on the vertical position of granules within each granule size class considered. To beware of overfitting, predictions of both the moisture content after drying and the granule bed temperature throughout drying are discussed in this study relative to experimental data from earlier published studies. These independent analyses demonstrated a marked improvement in prediction accuracy compared to earlier published model structures. The refined model accurately predicts the residual moisture content after drying for an untrained formulation. Moreover, it simultaneously makes accurate predictions of the granular bed temperature, which emboldens its structural correctness. This advancement makes it a powerful tool for predicting the behavior of the pharmaceutical fluid bed drying, which holds significant promise to facilitate pharmaceutical product development.