Prediction of Solid-State Form of SLS 3D Printed Medicines Using NIR and Raman Spectroscopy

Reducing Temperature of Fused Deposition Modelling 3D Printing for Linalool Fast Dissolving Oral Films by Increasing Printer Nozzle Diameter

Oral thrush and throat infections can occur in a wide range of patients. Treatments are available; however, resistance to drugs is a major problem for treating oral and throat infections. Three-dimensional printing (3DP) of fast dissolving oral films (FDFs) of linalool oil may provide an alternative solution. Linalool oil FDFs were printed by fused deposition modelling across 1-18 % w/w linalool content range with nozzle diameters of 0.4 or 1 mm at the temperature range of 150 °C-185 °C. The FDFs were evaluated for physicochemical and mechanical properties. Increasing the printer nozzle diameter to 1 mm allowed reducing the printing temperature from 185 °C to 150 °C; consequently, more linalool was quantified in the films with improved content uniformity. The higher linalool content in the films increased the film disintegration time and mechanical strength. FDFs containing 10% w/w linalool showed clear antifungal activity against Candida albicans. Raman spectroscopy suggested linalool separation from excipients at higher temperature printing. Viscoelastic measurements indicated that to achieve printing; the elastic modulus of molten filament needed to be higher than the loss modulus at low angular frequencies. In conclusion, increasing the printing nozzle diameter may avoid loss of the active ingredient by reducing the temperature of the 3DP process.

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.

Sketching feasibility of additively manufactured different size gradient conventional hollow capsular shells (HCSs) by selective laser sintering (SLS): From design to applications

Additive manufacturing (AM) is widely used to fabricate 3D printed objects from Computer-aided Design (CAD) prepared using the SolidWorks CAD modelling software. Different printing techniques are used to fabricate desired 3D objects; among all these techniques, it is widely accepted that SLS is one of the most effective methods of 3D printing for fabricating drug-loaded solid oral dosage forms (SODFs) in bulk quantities using the single-step process. Different SODFs, such as pills, miniprintlets, dual miniprintlets, and tablets, were fabricated with different sizes and shapes. In this study, for the first time, we introduce SLS-mediated hollow capsular shells (HCSs) with the help of the SLS 3D printing technique. This work aimed to explore the sinterability and feasibility of sketching HCSs using the SLS-mediated sintering technique with different marketed sizes of capsules ranging from 000 to 5. Here, we have utilized Kolliphor P 188 (KP 188) and Kollidon SR (KSR) in a 1:1 ratio as a matrix-forming agent and 1% charcoal as a laser absorption-enhancing material. In accordance with the CAD models, we have fabricated the gradient conventional different sizes of HCSs ranging from 000 to 5 using the constant printing parameters and composition. Fabricated all biobased HCSs were subjected to the assessment of mechanistic and physicochemical parameters using varied analytical tools. In the current study, tartrazine dye is used to assess the release pattern from HCSs, which resulted in the modified release pattern. The adapted approach will be the futuristic approach to replace animal-based gelatin capsules with pharmaceutical-grade polymer-based HCSs with a modified release with optimum mechanical strength.

Surgical Medical Education via 3D Bioprinting: Modular System for Endovascular Training

There is currently a shift in surgical training from traditional methods to simulation-based approaches, recognizing the necessity of more effective and controlled learning environments. This study introduces a completely new 3D-printed modular system for endovascular surgery training (M-SET), developed to allow various difficulty levels. Its design was based on computed tomography angiographies from real patient data with femoro-popliteal lesions. The study aimed to explore the integration of simulation training via a 3D model into the surgical training curriculum and its effect on their performance. Our preliminary study included 12 volunteer trainees randomized 1:1 into the standard simulation (SS) group (3 stepwise difficulty training sessions) and the random simulation (RS) group (random difficulty of the M-SET). A senior surgeon evaluated and timed the final training session. Feedback reports were assessed through the Student Satisfaction and Self-Confidence in Learning Scale. The SS group completed the training sessions in about half time (23.13 ± 9.2 min vs. 44.6 ± 12.8 min). Trainees expressed high satisfaction with the training program supported by the M-SET. Our 3D-printed modular training model meets the current need for new endovascular training approaches, offering a customizable, accessible, and effective simulation-based educational program with the aim of reducing the time required to reach a high level of practical skills.

Status of Polymer Fused Deposition Modeling (FDM)-Based Three-Dimensional Printing (3DP) in the Pharmaceutical Industry

Additive manufacturing (AM) or 3D printing (3DP) is arguably a versatile and more efficient way for the production of solid dosage forms such as tablets. Of the various 3DP technologies currently available, fused deposition modeling (FDM) includes unique characteristics that offer a range of options in the production of various types of tablets. For example, amorphous solid dispersions (ASDs), enteric-coated tablets or poly pills can be produced using an appropriate drug/polymer combination during FDM 3DP. The technology offers the possibility of evolving personalized medicines into cost-effective production schemes at pharmacies and hospital dispensaries. In this review, we highlight key FDM features that may be exploited for the production of tablets and improvement of therapy, with emphasis on gastrointestinal delivery. We also highlight current constraints that must be surmounted to visualize the deployment of this technology in the pharmaceutical and healthcare industries.

Visualizing disintegration of 3D printed tablets in humans using MRI and comparison with in vitro data

Three-dimensional (3D) printing is revolutionising the way that medicines are manufactured today, paving the way towards more personalised medicine. However, there is limited in vivo data on 3D printed dosage forms, and no studies to date have been performed investigating the intestinal behaviour of these drug products in humans, hindering the complete translation of 3D printed medications into clinical practice. Furthermore, it is unknown whether conventional in vitro release tests can accurately predict the in vivo performance of 3D printed formulations in humans. In this study, selective laser sintering (SLS) 3D printing technology has been used to produce two placebo torus-shaped tablets (printlets) using different laser scanning speeds. The printlets were administered to 6 human volunteers, and in vivo disintegration times were assessed using magnetic resonance imaging (MRI). In vitro disintegration tests were performed using a standard USP disintegration apparatus, as well as an alternative method based on the use of reduced media volume and minimal agitation. Printlets fabricated at a laser scanning speed of 90 mm/s exhibited an average in vitro disintegration time of 7.2 ± 1 min (measured using the USP apparatus) and 25.5 ± 4.1 min (measured using the alternative method). In contrast, printlets manufactured at a higher laser scanning speed of 130 mm/s had an in vitro disintegration time of 2.8 ± 0.8 min (USP apparatus) and 18.8 ± 1.9 min (alternative method). When tested in humans, printlets fabricated at a laser scanning speed of 90 mm/s showed an average disintegration time of 17.3 ± 7.2 min, while those manufactured at a laser scanning speed of 130 mm/s exhibited a shorter disintegration time of 12.7 ± 6.8 min. Although the disintegration times obtained using the alternative method more closely resembled those obtained in vivo, no clear correlation was observed between the in vitro and in vivo disintegration times, highlighting the need to develop better in vitro methodology for 3D printed drug products.

Virtually Possible: Enhancing Quality Control of 3D-Printed Medicines with Machine Vision Trained on Photorealistic Images

Three-dimensional (3D) printing is an advanced pharmaceutical manufacturing technology, and concerted efforts are underway to establish its applicability to various industries. However, for any technology to achieve widespread adoption, robustness and reliability are critical factors. Machine vision (MV), a subset of artificial intelligence (AI), has emerged as a powerful tool to replace human inspection with unprecedented speed and accuracy. Previous studies have demonstrated the potential of MV in pharmaceutical processes. However, training models using real images proves to be both costly and time consuming. In this study, we present an alternative approach, where synthetic images were used to train models to classify the quality of dosage forms. We generated 200 photorealistic virtual images that replicated 3D-printed dosage forms, where seven machine learning techniques (MLTs) were used to perform image classification. By exploring various MV pipelines, including image resizing and transformation, we achieved remarkable classification accuracies of 80.8%, 74.3%, and 75.5% for capsules, tablets, and films, respectively, for classifying stereolithography (SLA)-printed dosage forms. Additionally, we subjected the MLTs to rigorous stress tests, evaluating their scalability to classify over 3000 images and their ability to handle irrelevant images, where accuracies of 66.5% (capsules), 72.0% (tablets), and 70.9% (films) were obtained. Moreover, model confidence was also measured, and Brier scores ranged from 0.20 to 0.40. Our results demonstrate promising proof of concept that virtual images exhibit great potential for image classification of SLA-printed dosage forms. By using photorealistic virtual images, which are faster and cheaper to generate, we pave the way for accelerated, reliable, and sustainable AI model development to enhance the quality control of 3D-printed medicines.

Quality attributes for printable emulsion gels and 3D-printed tablets: Towards production of personalized dosage forms

3D-printing technology offers a flexible manufacturing platform with the potential to address the need of personalized dosage forms. However, quality aspects of such small-scale, on-demand production of pharmaceutical products intended for personalization is still limited. The aim of this study was therefore to study critical quality control attributes of lipid tablets produced by semi-solid extrusion (SSE) 3D printing from emulsion gels incorporating a poorly water-soluble drug. Quality attributes for both the printable emulsion gel and the printed dosage forms were assessed. The emulsion gel was shown to be printable with accurate dosing for at least one month of storage at 4 °C. Tablets were 3D printed in different sizes and a correlation, R2 value of 0.99, was found between the weight and the drug content. The 3D-printed tablets complied with the mass and drug content uniformity requirements described in the European Pharmacopoeia.. Solid-state characterization of the tablets during short-term storage revealed no signs of crystallinity of the drug. Lastly, the lipid digestion and drug release were unchanged after short-term storage of the tablets. This study demonstrates the potential of SSE 3D printing for personalized dosing of a lipid-based formulation strategy and discusses central quality attributes for the printable formulation and the 3D-printed dosage form.

The Upper Limb Orthosis in the Rehabilitation of Stroke Patients: The Role of 3D Printing

Stroke represents the third cause of long-term disability in the world. About 80% of stroke patients have an impairment of bio-motor functions and over half fail to regain arm functionality, resulting in motor movement control disorder with serious loss in terms of social independence. Therefore, rehabilitation plays a key role in the reduction of patient disabilities, and 3D printing (3DP) has showed interesting improvements in related fields, thanks to the possibility to produce customized, eco-sustainable and cost-effective orthoses. This study investigated the clinical use of 3DP orthosis in rehabilitation compared to the traditional ones, focusing on the correlation between 3DP technology, therapy and outcomes. We screened 138 articles from PubMed, Scopus and Web of Science, selecting the 10 articles fulfilling the inclusion criteria, which were subsequently examined for the systematic review. The results showed that 3DP provides substantial advantages in terms of upper limb orthosis designed on the patient's needs. Moreover, seven research activities used biodegradable/recyclable materials, underlining the great potential of validated 3DP solutions in a clinical rehabilitation setting. The aim of this study was to highlight how 3DP could overcome the limitations of standard medical devices in order to support clinicians, bioengineers and innovation managers during the implementation of Healthcare 4.0.

3D printing combined with biopredictive dissolution and PBPK/PD modeling optimization and personalization of pharmacotherapy: Are we there yet?

Precision medicine requires selecting the appropriate dosage regimen for a patient using the right drug, at the right time. Model-Informed Precision Dosing (MIPD) is a concept suggesting utilization of model-based prediction methods for optimizing the treatment benefit-harm balance, based on individual characteristics of the patient, disease, treatment method, and other factors. Here, we discuss a theoretical workflow comprising several elements, beginning from the physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models, through 3D printed tablets with the model proposed dose, information range and flow, and the patient themselves. We also describe each of these elements, and the connection between them, highlighting challenges and potential obstacles.

Development of Simvastatin-Loaded Particles Using Spray Drying Method for Ex Tempore Preparation of Cartridges for 2D Printing Technology

In this work, a spray drying method was developed to produce drug/polymer (simvastatin/polycaprolactone) microparticles that have the potential to be used as a pre-formulation for ex tempore preparation of 2D printing cartridges. An experimental model was designed with the process parameters set to predict the smallest particle size required for successful 2D printing. Three different types of particles (lactose, nanocellulose/lactose, calcium silicate) were produced, and the average size of the dry particles varied depending on the sampling location (cyclone, collection vessel). The encapsulation efficiency of simvastatin was highest with nanocellulose/lactose from the collection vessel. The one-month stability of simvastatin in the particles showed low content, but the addition of ascorbic acid as an antioxidant increased the chemical stability of the drug. Interestingly, the addition of antioxidants decreased the stability of simvastatin in the calcium silicate particles from the collection vessel. Dispersion of the particles in three different propylene glycol and water mixtures (10/90, 50/50, and 90/10% (v/v)), representing a printable ink medium with three different viscosity and surface tension properties, showed that nanocellulose/lactose was the most suitable antiadhesive in terms of dispersed particle size (˂1 µm). After one month of storage, the dispersed particles remained in the same size range without undesirable particle agglomeration.

3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives

3D printing, also known as Additive manufacturing (AM), has emerged as a transformative technology with applications across various industries, including the medical sector. This review paper provides an overview of the current status of AM technology, its challenges, and its application in the medical industry. The paper covers the different types of AM technologies, such as fused deposition modeling, stereolithography, selective laser sintering, digital light processing, binder jetting, and electron beam melting, and their suitability for medical applications. The most commonly used biomedical materials in AM, such as plastic, metal, ceramic, composite, and bio-inks, are also viewed. The challenges of AM technology, such as material selection, accuracy, precision, regulatory compliance, cost and quality control, and standardization, are also discussed. The review also highlights the various applications of AM in the medical sector, including the production of patient-specific surgical guides, prosthetics, orthotics, and implants. Finally, the review highlights the Internet of Medical Things (IoMT) and artificial intelligence (AI) for regulatory frameworks and safety standards for 3D-printed biomedical devices. The review concludes that AM technology can transform the healthcare industry by enabling patients to access more personalized and reasonably priced treatment alternatives. Despite the challenges, integrating AI and IoMT with 3D printing technology is expected to play a vital role in the future of biomedical device applications, leading to further advancements and improvements in patient care. More research is needed to address the challenges and optimize its use for medical applications to utilize AM's potential in the medical industry fully.

Towards Point-of-Care Manufacturing and Analysis of Immediate-Release 3D Printed Hydrocortisone Tablets for The Treatment of Congenital Adrenal Hyperplasia

Hydrocortisone (HC) is the preferred drug in children with congenital adrenal hyperplasia due to its lower potency as well as fewer reports of side effects. Fused deposition modelling (FDM) 3D printing holds the potential to produce low-cost personalised doses for children at the point of care. However, the compatibility of the thermal process to produce immediate-release bespoke tablets for this thermally labile active is yet to be established. This work aims to develop immediate-release HC tablets using FDM 3D printing and assess drug contents as a critical quality attribute (CQA) using a compact, low-cost near-infrared (NIR) spectroscopy as a process analytical technology (PAT). The FDM 3D printing temperature (140 °C) and drug concentration in the filament (10%-15% w/w) were critical parameters to meet the compendial criteria for drug contents and impurities. Using a compact low-cost NIR spectral device over a wavelength of 900-1700 nm, the drug contents of 3D printed tablets were assessed. Partial least squares (PLS) regression was used to develop individual calibration models to detect HC content in 3D printed tablets of lower drug contents, small caplet design, and relatively complex formula. The models demonstrated the ability to predict HC concentrations over a wide concentration range (0-15% w/w), which was confirmed by HPLC as a reference method. Ultimately, the capability of the NIR model had preceding dose verification performance on HC tablets, with linearity (R² = 0.981) and accuracy (RMSECV = 0.46%). In the future, the integration of 3DP technology with non-destructive PAT techniques will accelerate the adoption of on-demand, individualised dosing in a clinical setting.

The Use of Near-infrared as Process Analytical Technology (PAT) during 3D Printing Tablets at the Point-of-Care

Fused deposition modelling (FDM) is one of the most researched 3D printing technologies that holds great potential for low-cost manufacturing of personalised medicine. To achieve real-time release, timely quality control is a major challenge for applying 3D printing technologies as a point-of-care (PoC) manufacturing approach. This work proposes the use of a low-cost and compact near-infrared (NIR) spectroscopy modality as a process analytical technology (PAT) to monitor a critical quality attribute (drug content) during and after FDM 3D printing process. 3D printed caffeine tablets were used to manifest the feasibility of the NIR model as a quantitative analytical procedure and dose verification method. Caffeine tablets (0-40% w/w) were fabricated using polyvinyl alcohol and FDM 3D printing. The predictive performance of the NIR model was demonstrated in linearity (correlation coefficient, R²) and accuracy (root mean square error of prediction, RMSEP). The actual drug content values were determined using the reference high-performance liquid chromatography (HPLC) method. The model of full-completion caffeine tablets demonstrated linearity (R² = 0.985) and accuracy (RMSEP =1.4%), indicated to be an alternative dose quantitation method for 3D printed products. The ability of the models to assess caffeine contents during the 3D printing process could not be accurately achieved using the model built with complete tablets. Instead, by building a predictive model for each completion stage of 20%, 40%, 60% and 80%, the model of different completion caffeine tablets displayed linearity (R² of 0.991, 0.99, 0.987, and 0.983) and accuracy (RMSEP of 2.22%, 1.65%, 1.41%, 0.83%), respectively. Overall, this study demonstrated the feasibility of a low NIR model as a non-destructive, low-cost, compact, and rapid analysis dose verification method enabling the real-time release to facilitate 3D printing medicine production in the clinic.

Advancing non-destructive analysis of 3D printed medicines

Pharmaceutical 3D printing (3DP) has attracted significant interest over the past decade for its ability to produce personalised medicines on demand. However, current quality control (QC) requirements for traditional large-scale pharmaceutical manufacturing are irreconcilable with the production offered by 3DP. The US Food and Drug Administration (FDA) and the UK Medicines and Healthcare Products Regulatory Agency (MHRA) have recently published documents supporting the implementation of 3DP for point-of-care (PoC) manufacturing along with regulatory hurdles. The importance of process analytical technology (PAT) and non-destructive analytical tools in translating pharmaceutical 3DP has experienced a surge in recognition. This review seeks to highlight the most recent research on non-destructive pharmaceutical 3DP analysis, while also proposing plausible QC systems that complement the pharmaceutical 3DP workflow. In closing, outstanding challenges in integrating these analytical tools into pharmaceutical 3DP workflows are discussed.

Selective laser sintering additive manufacturing of dosage forms: Effect of powder formulation and process parameters on the physical properties of printed tablets

Large batches of placebo and drug-loaded solid dosage forms were successfully fabricated using selective laser sintering (SLS) 3D printing in this study. The tablet batches were prepared using either copovidone (N-vinyl-2-pyrrolidone and vinyl acetate, PVP/VA) or polyvinyl alcohol (PVA) and activated carbon (AC) as radiation absorbent, which was added to improve the sintering of the polymer. The physical properties of the dosage forms were evaluated at different pigment concentrations (i.e., 0.5 and 1.0 wt%) and at different laser energy inputs. The mass, hardness, and friability of the tablets were found to be tunable and structures with greater mass and mechanical strength were obtained with increasing carbon concentration and energy input. Amorphization of the active pharmaceutical ingredient in the drug-loaded batches, containing 10 wt% naproxen and 1 wt% AC, was achieved in-situ during printing. Thus, amorphous solid dispersions were prepared in a single-step process and produced tablets with mass losses below 1 wt%. These findings show how the properties of dosage forms can be tuned by careful selection of the process parameters and the powder formulation. SLS 3D printing can therefore be considered to be an interesting and promising technique for the fabrication of personalized medicines.

Machine learning using multi-modal data predicts the production of selective laser sintered 3D printed drug products

Three-dimensional (3D) printing is drastically redefining medicine production, offering digital precision and personalized design opportunities. One emerging 3D printing technology is selective laser sintering (SLS), which is garnering attention for its high precision, and compatibility with a wide range of pharmaceutical materials, including low-solubility compounds. However, the full potential of SLS for medicines is yet to be realized, requiring expertise and considerable time-consuming and resource-intensive trial-and-error research. Machine learning (ML), a subset of artificial intelligence, is an in silico tool that is accomplishing remarkable breakthroughs in several sectors for its ability to make highly accurate predictions. Therefore, the present study harnessed ML to predict the printability of SLS formulations. Using a dataset of 170 formulations from 78 materials, ML models were developed from inputs that included the formulation composition and characterization data retrieved from Fourier-transformed infrared spectroscopy (FT-IR), X-ray powder diffraction (XRPD) and differential scanning calorimetry (DSC). Multiple ML models were explored, including supervised and unsupervised approaches. The results revealed that ML can achieve high accuracies, by using the formulation composition leading to a maximum F1 score of 81.9%. Using the FT-IR, XRPD and DSC data as inputs resulted in an F1 score of 84.2%, 81.3%, and 80.1%, respectively. A subsequent ML pipeline was built to combine the predictions from FT-IR, XRPD and DSC into one consensus model, where the F1 score was found to further increase to 88.9%. Therefore, it was determined for the first time that ML predictions of 3D printability benefit from multi-modal data, combining numeric, spectral, thermogram and diffraction data. The study lays the groundwork for leveraging existing characterization data for developing high-performing computational models to accelerate formulation development.

Inkjet drug printing onto contact lenses: Deposition optimisation and non-invasive dose verification

Inkjet printing has the potential to advance the treatment of eye diseases by printing drugs on demand onto contact lenses for localised delivery and personalised dosing, while near-infrared (NIR) spectroscopy can further be used as a quality control method for quantifying the drug but has yet to be demonstrated with contact lenses. In this study, a glaucoma therapy drug, timolol maleate, was successfully printed onto contact lenses using a modified commercial inkjet printer. The drug-loaded ink prepared for the printer was designed to match the properties of commercial ink, whilst having maximal drug loading and avoiding ocular inflammation. This setup demonstrated personalised drug dosing by printing multiple passes. Light transmittance was found to be unaffected by drug loading on the contact lens. A novel dissolution model was built, and in vitro dissolution studies showed drug release over at least 3 h, significantly longer than eye drops. NIR was used as an external validation method to accurately quantify the drug dose. Overall, the combination of inkjet printing and NIR represent a novel method for point-of-care personalisation and quantification of drug-loaded contact lenses.

Releasing fast and slow: Non-destructive prediction of density and drug release from SLS 3D printed tablets using NIR spectroscopy

Selective laser sintering (SLS) 3D printing is a revolutionary 3D printing technology that has been found capable of creating drug products with varied release profiles by changing the laser scanning speed. Here, SLS 3D printed formulations (printlets) loaded with a narrow therapeutic index drug (theophylline) were produced using SLS 3D printing at varying laser scanning speeds (100-180 mm/s). The use of reflectance Fourier Transform - Near Infrared (FT-NIR) spectroscopy was evaluated as a non-destructive approach to predicting 3D printed tablet density and drug release at 2 h and 4 h. The printed drug products formulated with a higher laser speed exhibited an accelerated drug release and reduced density compared with the slower laser scanning speeds. Univariate calibration models were developed based on a baseline shift in the spectra in the third overtone region upon changing physical properties. For density prediction, the developed univariate model had high linearity (R² value = 0.9335) and accuracy (error < 0.029 mg/mm³). For drug release prediction at 2 h and 4 h, the developed univariate models demonstrated a linear correlation (R² values of 0.9383 and 0.9167, respectively) and accuracy (error < 4.4%). The predicted vs. actual dissolution profiles were found to be statistically similar (f₂ > 50) for all of the test printlets. Overall, this article demonstrates the feasibility of SLS 3D printing to produce drug products containing a narrow therapeutic index drug across a range of drug release profiles, as well as the potential for FT-NIR spectroscopy to predict the physical characteristics of SLS 3D printed drug products (drug release and density) as a non-destructive quality control method at the point-of-care.

Determination of Alteration in Micromeritic Properties of a Solid Dispersion: Brunauer-Emmett-Teller Based Adsorption and Other Structured Approaches

The present study is focused on the use of solid dispersion technology to triumph over the solubility-related problems of bexarotene which is currently used for treating various types of cancer and has shown potential inhibitory action on COVID-19 main protease and human ACE2 receptors. It is based on comparison of green locust bean gum and synthetic poloxamer as polymers using extensive mechanistic methods to explore the mechanism behind solubility enhancement and to find suitable concentration of drug to polymer ratio to prepare porous 3^rd generation solid dispersion. The prepared solid dispersions were characterized using different studies like X-ray diffraction (XRD), thermal gravimetric analysis (TGA), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET), differential scanning calorimetry (DSC), and particle size analysis in order to determine the exact changes occurred in the product which are responsible for enhancing solubility profiles of an insoluble drug. The results showed different profiles for particle size, solubility, dissolution rate, porosity, BET, and Langmuir specific surface area of prepared solid dispersions by using different polymers. In addition to the comparison of polymers, the BET analysis deeply explored the changes occurred in all dispersions when the concentration of polymer was increased. The optimized solid dispersion prepared with MLBG using lyophilization technique showed reduced particle size of 745.7±4.4 nm, utmost solubility of 63.97%, pore size of 211.597 Å, BET and Langmuir specific surface area of 5.6413 m²/g and 8.2757 m²/g, respectively.

Low-Cost Cranioplasty—A Systematic Review of 3D Printing in Medicine

The high cost of biofabricated titanium mesh plates can make them out of reach for hospitals in low-income countries. To increase the availability of cranioplasty, the authors of this work investigated the production of polymer-based endoprostheses. Recently, cheap, popular desktop 3D printers have generated sufficient opportunities to provide patients with on-demand and on-site help. This study also examines the technologies of 3D printing, including SLM, SLS, FFF, DLP, and SLA. The authors focused their interest on the materials in fabrication, which include PLA, ABS, PET-G, PEEK, and PMMA. Three-dimensional printed prostheses are modeled using widely available CAD software with the help of patient-specific DICOM files. Even though the topic is insufficiently researched, it can be perceived as a relatively safe procedure with a minimal complication rate. There have also been some initial studies on the costs and legal regulations. Early case studies provide information on dozens of patients living with self-made prostheses and who are experiencing significant improvements in their quality of life. Budget 3D-printed endoprostheses are reliable and are reported to be significantly cheaper than the popular counterparts manufactured from polypropylene polyester.