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.

[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.

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.

Formulating biopharmaceuticals using three-dimensional printing.

Additive manufacturing, commonly referred to as three-dimensional (3D) printing, has the potential to initiate a paradigm shift in the field of medicine and drug delivery. Ever since the advent of the first-ever United States Food and Drug Administration (US FDA)-approved 3D printed tablet, there has been an increased interest in the application of this technology in drug delivery and biomedical applications. 3D printing brings us one step closer to personalized medicine, hence rendering the "one size fits all" concept in drug dosing obsolete. In this review article, we focus on the recent developments in the field of modified drug delivery systems in which various types of additive manufacturing technologies are applied.

Numerical study of drop dynamics for inkjet based 3D printing of pharmaceutical tablets.

Interest in 3D printing has been growing rapidly especially in pharmaceutical industry due to its multiple advantages such as manufacturing versatility, personalization of medicine, scalability, and cost effectiveness. Inkjet based 3D printing gained special attention after FDA's approval of Spritam® manufactured by Aprecia pharmaceuticals in 2015. The precision and printing efficiency of 3D printing is strongly influenced by the dynamics of ink/binder jetting, which further depends on the ink's fluid properties. In this study, Computational Fluid Dynamics (CFD) has been utilized to study the drop formation process during inkjet-based 3D printing for piezoelectric and thermal printhead geometries using Volume of Fluid (VOF) method. To develop the CFD model commercial software ANSYS-Fluent was used. The developed CFD model was experimentally validated using drop watcher setup to record drop progression and drop velocity. During the study, water, Fujifilm model fluid, and Amitriptyline drug solutions were evaluated as the ink solutions. The drop properties such as drop volume, drop diameter, and drop velocity were examined in detail in response to change ink solution properties such as surface tension, viscosity, and density. A good agreement was observed between the experimental and simulation data for drop properties such as drop volume and drop velocity.

Fabrication of 3D-Printed Hydrocortisone Triple Pulsatile Tablet Using Fused Deposition Modelling Technology.

Hydrocortisone (HC) is the optimal drug for adolescents diagnosed with congenital adrenal hyperplasia (CAH). Because traditional dosage regimens HC are inconvenient, our study used fused deposition modeling (FDM) three-dimensional (3D) printing technology to solve the problems caused by traditional preparations. First, we designed a core-shell structure tablet with an inner instant release component and an outer delayed release shell. The instant release component was Kollicoat IR: glycerol (GLY): HC = 76.5:13.5:10. Then, we used Affinisol® HPMC 15LV to realize delayed release. Furthermore, we investigated the relationship between the thickness of the delayed release shell and the delayed release time, and an equation was derived through binomial regression analysis. Based on that equation, a novel triple pulsatile tablet with an innovative structure was devised. The tablet was divided into three components, and the drug was released multiple times at different times. The dose and release rate of the tablets can be adjusted by modifying the infill rate of the printing model. The results indicated that the triple pulsatile tablet exhibited desirable release behavior in vitro. Moreover, the physicochemical properties of the drug, excipients, filaments, and tablets were characterized. All these results indicate that the FDM 3D printing method is a convenient technique for producing preparations with intricate structures.

Development of a simple paste for 3D printing of drug formulations containing a mesoporous material loaded with a poorly water-soluble drug.

Poorly soluble drugs represent a substantial portion of emerging drug candidates, posing significant challenges for pharmaceutical formulators. One promising method to enhance the drug's dissolution rate and, consequently, bioavailability involves transforming them into an amorphous state within mesoporous materials. These materials can then be seamlessly integrated into personalized drug formulations using Additive Manufacturing (AM) techniques, most commonly via Fused Deposition Modeling. Another innovative approach within the realm of AM for mesoporous material-based formulations is semi-solid extrusion (SSE). This study showcases the feasibility of a straightforward yet groundbreaking hybrid 3D printing system employing SSE to incorporate drug-loaded mesoporous magnesium carbonate (MMC) into two different drug formulations, each designed for distinct administration routes. MMC was loaded with the poorly water-soluble drug ibuprofen via a solvent evaporation method and mixed with PEG 400 as a binder and lubricant, facilitating subsequent SSE. The formulation is non-aqueous, unlike most pastes which are used for SSE, and thus is beneficial for the incorporation of poorly water-soluble drugs. The 3D printing process yielded tablets for oral administration and suppositories for rectal administration, which were then analyzed for their dissolution behavior in biorelevant media. These investigations revealed enhancements in the dissolution kinetics of the amorphous drug-loaded MMC formulations. Furthermore, an impressive drug loading of 15.3 % w/w of the total formulation was achieved, marking the highest reported loading for SSE formulations incorporating mesoporous materials to stabilize drugs in their amorphous state by a wide margin. This simple formulation containing PEG 400 also showed advantages over other aqueous formulations for SSE in that the formulations did not exhibit weight loss or changes in size or form during the curing process post-printing. These results underscore the substantial potential of this innovative hybrid 3D printing system for the development of drug dosage forms, particularly for improving the release profile of poorly water-soluble drugs.

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

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

A floating 3D printed polypill formulation for the coadministration and sustained release of antihypertensive drugs.

Polypharmacy is a common issue, especially among elderly patients resulting in administration errors and patient inconvenience. Hypertension is a prevalent health condition that frequently leads to polypharmacy, as its treatment typically requires the co-administration of more than one different Active Pharmaceutical Ingredients (API's). To address these issues, floating hollow torus-shaped dosage forms were developed, aiming at providing prolonged gastric retention and sustained drug release. The dosage forms (polypills) containing three anti-hypertensive API's (diltiazem (DIL), propranolol (PRP) and hydrochlorothiazide (HCTZ)) were created via Fused Deposition Modelling 3D printing. A multitude of the dosage forms were loaded into a capsule and the resulting formulation achieved prolonged retention times over a 12-hour period in vitro, by leveraging both the buoyancy of the dosage forms, and the "cheerios effect" that facilitates the aggregation and retention of the dosage forms via a combination of surface tension and shape of the objects. Physicochemical characterization methods and imaging techniques were employed to investigate the properties and the internal and external structure of the dosage forms. Furthermore, an ex vivo porcine stomach model revealed substantial aggregation, adhesion and retention of the 3D printed dosage forms in porcine stomach. In vitro dissolution testing demonstrated almost complete first-order release of PRP and DIL (93.52 % and 99.9 %, respectively) and partial release of HCTZ (65.22 %) in the 12 h timeframe. Finally, a convolution-based single-stage approach was employed in order to predict the pharmacokinetic (PK) parameters of the API's of the formulation and the resemblance of their PK behavior with previously reported data.

The quest for down scale representativeness: how to exploit CFD to design a shear study for vaccines.

In this work, we exploit computational fluid dynamics (CFD) to evaluate stirred tank reactor (STR) process engineer parameters (PEP) and design a scale-down system (SDS) to be representative of the formulation and filling process steps for an Aluminum adjuvanted vaccine drug product (DP). To study the shear history in the SDS we used the concept of number of passages, combined with an appropriate stirring speed down scale strategy comprising of either (i) tip speed equivalence, widely used as a scale-up criterion for a shear-sensitive product, or (ii) rotating shear, a shear metric introduced by Metz and Otto in 1957 but never used as scaling criterion. The outcome of the CFD simulations shows that the tip equivalence generates a worst-case SDS in terms of shear, whereas the rotating shear scaling approach could be used to design a more representative SDS. We monitored the trend over time for "In Vitro Relative Potency" as DP Critical Quality Attribute for both scaling approaches, which highlighted the crucial role of choosing the appropriate scaling-down approach to be representative of the manufacturing scale during process characterization studies.

Cutaneous Pharmacokinetics of Topically Applied Novel Dermatological Formulations.

Novel formulations are developed for dermatological applications to address a wide range of patient needs and therapeutic challenges. By pushing the limits of pharmaceutical technology, these formulations strive to provide safer, more effective, and patient-friendly solutions for dermatological concerns, ultimately improving the overall quality of dermatological care. The article explores the different types of novel dermatological formulations, including nanocarriers, transdermal patches, microsponges, and microneedles, and the techniques involved in the cutaneous pharmacokinetics of these innovative formulations. Furthermore, the significance of knowing cutaneous pharmacokinetics and the difficulties faced during pharmacokinetic assessment have been emphasized. The article examines all the methods employed for the pharmacokinetic evaluation of novel dermatological formulations. In addition to a concise overview of earlier techniques, discussions on novel methodologies, including tape stripping, in vitro permeation testing, cutaneous microdialysis, confocal Raman microscopy, and matrix-assisted laser desorption/ionization mass spectrometry have been conducted. Emerging technologies like the use of microfluidic devices for skin absorption studies and computational models for predicting drug pharmacokinetics have also been discussed. This article serves as a valuable resource for researchers, scientists, and pharmaceutical professionals determined to enhance the development and understanding of novel dermatological drug products and the complex dynamics of cutaneous pharmacokinetics.

Personalised oral dosage forms using an ultra-compact tablet press at the point of care.

Over the last 10 years there is an increasing need for the design of personalised medicines at the point of care (PoC) that meet the specific needs of individual patients. A plethora of technologies has been introduced for making affordable personalised pharmaceutical products, which however, do not address manufacturing and regulatory challenges. Here we introduce a novel ultra-compact tablet press which was used for the design and compression of rosuvastatin-aspirin and amiloride-lysonipril bilayer tablets respectively. By applying precision dosing, it was feasible to manufacture tablets of different dose strengths and control features such as hardness, friability and disintegration times. The compaction of on-demand personalised multidrug pills that meet quality standards could revolutionised the treatment of patients at the point of care.

Application of 3D printing in early phase development of pharmaceutical solid dosage forms.

Three-dimensional printing (3DP) is an emerging technology, offering the possibility for the development of dose-customized, effective, and safe solid oral dosage forms (SODFs). Although 3DP has great potential, it does come with certain limitations, and the traditional drug manufacturing platforms remain the industry standard. The consensus appears to be that 3DP technology is expected to benefit personalized medicine the most, but that it is unlikely to replace conventional manufacturing for mass production. The 3DP method, on the other hand, could prove well-suited for producing small batches as an adaptive manufacturing technique for enabling adaptive clinical trial design for early clinical studies. The purpose of this review is to discuss recent advancements in 3DP technologies for SODFs and to focus on the applications for SODFs in the early clinical development stages, including a discussion of current regulatory challenges and quality controls.

Application of 3D printing technology for the development of dose adjustable geriatric and pediatric formulation of celecoxib.

Developing safe and effective formulations for the geriatric and pediatric population is a challenging task due to issues of swallowability and palatability. The lack of standardized procedures for pediatric formulations further complicates the process. Manipulating adult formulations for children can lead to suboptimal efficacy and safety concerns. To overcome these challenges, minitablets or spinklets are preferred for the geriatric and pediatric population due to their smaller size and flexible dose adjustment. The aim of this study is the development of a 3D printed spinklets formulation of celecoxib, a nonsteroidal anti-inflammatory drug, using hot melt extrusion to address the limitations of traditional manufacturing methods. Three different formulations of celecoxib were prepared using Poly-2-ethyl-tetra-oxazoline (Aquazol) with and without surfactant. Subsequently, the mechanical properties and solubility of the drug-loaded filaments were evaluated. Solid state characterization confirmed the drug conversion into an amorphous form during the extrusion process, Computer-aided design software facilitate sprinklets design for fused deposition modeling and scanning electron microscopy assess the surface morphology. Sophorolipids plasticize better than TPGS, resulting in lowering processing temperatures during melt extrusion. In vitro drug release showed successful enhancements in the dissolution of oral medications for pediatric patients, considering their distinctive physiological characteristics. Overall, this study demonstrates the successful development of PEtOx-based 3D printed celecoxib sprinklets by coupling hot-melt extrusion and 3D printing technology. Future exploration holds the potential to revolutionize pharmaceutical production and advance personalized medication formulations.

Application of Raman spectroscopy during pharmaceutical process development for determination of critical quality attributes in Protein A chromatography.

Raman spectroscopy is considered a Process Analytical Technology (PAT) tool in biopharmaceutical downstream processes. In the past decade, researchers have shown Raman spectroscopy's feasibility in determining Critical Quality Attributes (CQAs) in bioprocessing. This study verifies the feasibility of implementing a Raman-based PAT tool in Protein A chromatography as a CQA monitoring technique, for the purpose of accelerating process development and achieving real-time release in manufacturing. A system connecting Raman to a Tecan liquid handling station enables high-throughput model calibration. One calibration experiment collects Raman spectra of 183 samples with 8 CQAs within 25 h. After applying Butterworth high-pass filters and k-nearest neighbor (KNN) regression for model training, the model showed high predictive accuracy for fragments (Q2 = 0.965) and strong predictability for target protein concentration, aggregates, as well as charge variants (Q2≥ 0.922). The model's robustness was confirmed by varying the elution pH, load density, and residence time using 19 external validation preparative Protein A chromatography runs. The model can deliver elution profiles of multiple CQAs within a set point ± 0.3 pH range. The CQA readouts were presented as continuous chromatograms with a resolution of every 28 s for enhanced process understanding. In external validation datasets, the model maintained strong predictability especially for target protein concentration (Q2 = 0.956) and basic charge variants (Q2 = 0.943), except for overpredicted HCP (Q2 = 0.539). This study demonstrates a rapid, effective method for implementing Raman spectroscopy for in-line CQA monitoring in process development and biomanufacturing, eliminating the need for labor-intensive sample pooling and handling.

Hot-Melt Extrusion: from Theory to Application in Pharmaceutical Formulation-Where Are We Now?

Hot-melt extrusion (HME) is a globally recognized, robust, effective technology that enhances the bioavailability of poorly soluble active pharmaceutical ingredients and offers an efficient continuous manufacturing process. The twin-screw extruder (TSE) offers an extremely resourceful customizable mixer that is used for continuous compounding and granulation by using different combinations of conveying elements, kneading elements (forward and reverse configuration), and distributive mixing elements. TSE is thus efficiently utilized for dry, wet, or melt granulation not only to manufacture dosage forms such as tablets, capsules, or granule-filled sachets, but also for designing novel formulations such as dry powder inhalers, drying units for granules, nanoextrusion, 3D printing, complexation, and amorphous solid dispersions. Over the past decades, combined academic and pharmaceutical industry collaborations have driven novel innovations for HME technology, which has resulted in a substantial increase in published articles and patents. This article summarizes the challenges and models for executing HME scale-up. Additionally, it covers the benefits of continuous manufacturing, process analytical technology (PAT) considerations, and regulatory requirements. In summary, this well-designed review builds upon our earlier publication, probing deeper into the potential of twin-screw extruders (TSE) for various new applications.