Tailoring Atomoxetine Release Rate from DLP 3D-Printed Tablets Using Artificial Neural Networks: Influence of Tablet Thickness and Drug Loading

Pharmaceutical applications and requirements of resins for printing by digital light processing (DLP)

The digital light processing (DLP) printer has proven to be effective in biomedical and pharmaceutical applications, as its printing method does not induce shear and a strong temperature on the resin. In addition, the DLP printer has good resolution and print quality, which makes it possible to print complex structures with a customized shape, being used for various purposes ranging from jewelry application to biomedical and pharmaceutical areas. The big disadvantage of DLP is the lack of a biocompatible and non-toxic resin on the market. To overcome this limitation, an ideal resin for biomedical and pharmaceutical use is needed. The resin must have appropriate properties, so that the desired format is printed when with a determined wavelength is applied. Thus, the aim of this work is to bring the basic characteristics of the resins used by this printing method and the minimum requirements to start printing by DLP for pharmaceutical and biomedical applications. The DLP method has proven to be effective in obtaining pharmaceutical devices such as drug delivery systems. Furthermore, this technology allows the printing of devices of ideal size, shape and dosage, providing the patient with personalized treatment.

Powder bed fusion-laser beam (PBF-LB) three-dimensional (3D) printing: Influence of laser hatching distance on the properties of zolpidem tartrate tablets

Laser sintering, known as powder bed fusion-laser beam (PBF-LB), offers promising potential for the fabrication of patient-specific drugs. The aim of this study was to provide an insight into the PBF-LB process with regard to the process parameters, in particular the laser hatching distance, and its influence on the properties of zolpidem tartrate (ZT) tablets. PHARMACOAT® 603 was used as the polymer, while Candurin® Gold Sheen and AEROSIL® 200 were added to facilitate 3D printing. The particle size distribution of the powder blend showed that the layer height should be set to 100 µm, while the laser hatching distance was varied in five different steps (50, 100, 150, 200 and 250 µm), keeping the temperature and laser scanning speed constant. Increasing the laser hatching distance and decreasing the laser energy input led to a decrease in the colour intensity, mass, density and hardness of the ZT tablets, while the disintegration and dissolution rate were faster due to the more fragile bonds between the particles. The laser hatching distance also influenced the ZT dosage, indicating the importance of this process parameter in the production of presonalized drugs. The absence of drug-polymer interactions and the amorphization of the ZT were confirmed.

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.

3D-printed extraction devices fabricated from silica particles suspended in acrylate resin

In recent years, there has been an increasing worldwide interest in the use of alternative sample preparation methods. Digital light processing (DLP) is a 3D printing technique based on using UV light to form photo-curable resin layer upon layer, which results in a printed shape. This study explores the application of this technique for the development of novel drug extraction devices in analytical chemistry. A composite material consisting of a photocurable resin and C18-modified silica particles was employed as a sorbent device, demonstrating its effectiveness in pharmaceutical analysis. Apart from estimating optimal printing parameters, microscopic examination of the material surface, and sorbent powder to resin ratio, the extraction procedure was also optimised. Optimisation included the type and amount of sample matrix additives, desorption solvent, sorption and desorption times, and proper number of sorbent devices needed in extraction protocol. To demonstrate this method's applicability for sample analysis, the solid-phase extraction followed by gas chromatography coupled with mass spectrometry (SPE-GC-MS) method was validated for its ability to quantify benzodiazepine-type drugs. This evaluation confirmed good linearity in the concentration range of 50-1000 ng/mL, with R2 values being 0.9932 and 0.9952 for medazepam and diazepam, respectively. Validation parameters proved that the presented method is precise (with values ranging in-between 2.98 %-7.40 %), and accurate (88.81 % to 110.80 %). A negative control was also performed to investigate possible sorption properties of the resin itself, proving that the addition of C18-modified silica particles significantly increases the extraction efficiency and repeatability. The cost-effectiveness of this approach makes it particularly advantageous for single-use scenarios, eliminating the need for time-consuming sorbent-cleaning procedures, common in traditional solid-phase extraction techniques. Future optimisation opportunities include refining sorbent size, shape, and geometry to achieve lower limits of quantification. As a result of these findings, 3D-printed extraction devices can serve as a viable alternative to commercially available SPE or solid-phase microextraction (SPME) protocols for studying new sample preparation approaches.

Photopolymer-Based Composite with Substance Release Capability Manufactured Additively with DLP Method

In this study, caffeine-loaded photoresin composites with homogeneous structures, suitable for additive manufacturing of transdermal microneedle systems, were obtained. The properties of the composites with varying caffeine concentrations (0.1-0.4% w/w) were investigated for carbon-carbon double bond conversion using Fourier Transform Infrared Spectroscopy, surface wettability and mechanical properties using a static tensile test and nanoindentation, and caffeine release in ethanol using UV-Vis. The caffeine concentration did not affect the final degree of double bond conversion, which was confirmed in tensile tests, where the strength and Young's modulus of caffeine-loaded samples had comparable values to control ones. Samples with 0.1 and 0.2% caffeine content showed an increase in nanohardness and reduced elastic modulus of 50 MPa and 1.5 MPa, respectively. The good wettability of the samples with water and the increase in surface energy is a favorable aspect for the dedicated application of the obtained composite materials. The amount of caffeine released into the ethanol solution at 1, 3 and 7 days reached a maximum value of 81%, was higher for the lower concentration of caffeine in the sample and increased over time. The conducted research may enhance the potential application of composite materials obtained through the digital light processing method in additive manufacturing.

Artificial neural network-based gene screening and immune cell infiltration analysis of osteosarcoma feature

BACKGROUND

The present study aimed to construct an artificial neural network (ANN) model that leverages characteristic genes associated with osteosarcoma (OS) to enable accurate prognostication for OS patients.

METHODS

Our research revealed 467 differentially expressed genes (DEGs) via gene expression contrast analysis, consisting of 345 downregulated genes and 122 upregulated genes. Gene Ontology (GO) enrichment analysis illuminated functions primarily encompassing T-cell activation, secretory granule lumen and antioxidant activity, among others. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we discovered significant correlations between the DEGs and certain pathways, including phagosome, Staphylococcus aureus infection and human T-cell leukemia virus 1 infection. We then screened out 30 characteristic DEGs (CDEGs) based on random forest analysis and constructed the ANN model using the gene score matrix. To verify the credibility and accuracy of the ANN model, we performed internal and external validation processes, which affirmed our model's predictive capabilities.

RESULTS

The study further delved into the analysis of immune cell infiltration and its correlation with the target CDEGs, revealing disparities in the infiltration of 22 types of immune cells across different groups and their interrelationships. Moreover, we probed the expression of the two foremost CDEGs (YES1 and MFNG) in OS and normal tissues. We noted a positive relationship between the expression of YES1 and MFNG in OS tissues and the clinicopathological characteristics of OS patients.

CONCLUSIONS

Collectively, the findings of the present study validate the effectiveness of the CDEGs-based ANN model in predicting OS patients, which might facilitate early diagnosis and treatment of OS.

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.

Xanthan-Gum/Pluronic-F-127-Based-Drug-Loaded Polymeric Hydrogels Synthesized by Free Radical Polymerization Technique for Management of Attention-Deficit/Hyperactivity Disorder

Smart and intelligent xanthan gum/pluronic F-127 hydrogels were fabricated for the controlled delivery of atomoxetine HCl. Different parameters such as DSC, TGA, FTIR, XRD, SEM, drug loading, porosity, swelling index, drug release, and kinetics modeling were appraised for the prepared matrices of hydrogels. FTIR confirmed the successful synthesis of the hydrogel, while TGA and DSC analysis indicated that the thermal stability of the reagents was improved after the polymerization technique. SEM revealed the hard surface of the hydrogel, while XRD indicated a reduction in crystallinity of the reagents. High gel fraction was achieved with high incorporated contents of the polymers and the monomer. An increase in porosity, drug loading, swelling, and drug release was observed with the increase in the concentrations of xanthan gum and acrylic acid, whereas Pluronic F-127 showed the opposite effect. A negligible swelling index was shown at pH 1.2 and 4.6 while greater swelling was observed at pH 7.4, indicating a pH-responsive nature of the designed hydrogels. Furthermore, a higher drug release was found at pH 7.4 compared to pH 1.2 and 4.6, respectively. The first kinetics order was followed by the prepared hydrogel formulations. Thus, it is signified from the discussion that smart xanthan gum/pluronic F-127 hydrogels have the potential to control the release of the atomoxetine HCl in the colon for an extended period of time.

Application of an AI image analysis and classification approach to characterise dissolution and precipitation events in the flow through apparatus

Imaging and artificial intelligence (AI) approaches have been used with increasing frequency in pharmaceutical industry in recent years. Characterisation of processes such as drug dissolution and precipitation is vital in quality control testing and drug manufacture. To support existing techniques like in vitro dissolution testing, novel process analytical technologies (PATs) can give an insight into these processes. The aim of this study was to create and explore the potential of an automated image classification model based on image analysis to identify events (dissolution and precipitation) occurring in the flow-through apparatus (FTA) test cell, and the ability to characterise a dissolution process over time. Several precipitation conditions were tested in a USP 4 FTA test cell with images recorded during early (plume formation) and late (particulate re-formation) stages of precipitation. An available MATLAB code was used as a base to develop and validate an anomaly classification model able to detect different events occurring during the precipitation process in the dissolution cell. Two variants of the model were tested on images from a dissolution test in the FTA, with a view to application of the image analysis system to quantitative characterization of the dissolution process over time. It was found that the classification model is highly accurate (>90%) in detecting events occurring in the FTA test cell. The model showed potential to be used to characterise the stages of dissolution and precipitation processes, and as a proof of concept demonstrates potential for deep machine learning image analysis to be applied to kinetics of other pharmaceutical processes.

Development of 3D DLP Printed Sustained Release Ibuprofen Tablets and Their Pharmacokinetic Evaluation in Rats

The objective of the present study was to develop digital light processing (DLP) 3D printed sustained release ibuprofen (IBU) tablets using 3D DLP printers for evaluation in in vitro release and in vivo pharmacokinetic studies with their in vitro-in vivo correlation. The resin formulation and printing parameters were optimized using quality by design (QbD) approach, and IBU tablets were printed using DLP printers which works at 385 and 405 nm wavelengths. Our results demonstrated that formulation consisting of polyethylene glycol diacrylate (PEGDA) 700, water, IBU, and riboflavin printed at 40-s bottom layer exposure time and 30-s exposure time produced tablets using both 385 and 405 nm wavelengths. In vitro dissolution studies showed > 70% drug release at the end of 24 h when printed at 405 nm wavelength with no significant difference between tablets printed at 385 nm. In vivo pharmacokinetic evaluation of the optimized 3D printed tablets printed at 405 nm at oral dose of 30 mg/kg in rats showed sustained release of IBU with significantly (p < 0.05) higher Cmax of 30.12 ± 2.45 µg/mL and AUC(0-24 h) of 318.97 ± 16.98 (µg/mL × h) compared to marketed IBU tablet (control). In vivo-in vitro correlation studies showed 80% of drug was absorbed in vivo within 3 h from the pulverized 3D printed tablet, whereas intact 3D tablet showed sustained release of IBU with > 75% IBU release in 24 h in vitro. Overall, IBU tablets fabricated using DLP printing demonstrated sustained release and enhanced systemic absorption with no significant difference in their release profile at different wavelengths.

Investigations into the use of machine learning to predict drug dosage form design to obtain desired release profiles for 3D printed oral medicines

Three-dimensional (3D) printing, digitalization, and artificial intelligence (AI) are gaining increasing interest in modern medicine. All three aspects are combined in personalized medicine where 3D-printed dosage forms are advantageous because of their variable geometry design. The geometry design can be used to determine the surface area to volume (SA/V) ratio, which affects drug release from the dosage forms. This study investigated artificial neural networks (ANN) to predict suitable geometries for the desired dose and release profile. Filaments with 5% API load and polyvinyl alcohol were 3D printed using Fused Deposition Modeling to provide a wide variety of geometries with different dosages and SA/V ratios. These were dissolved in vitro, and the API release profiles were described mathematically. Using these data, ANN architectures were designed with the goal of predicting a suitable dosage form geometry. Poor accuracies of 68.5% in the training and 44.4% in the test settings were achieved with a classification architecture. However, the SA/V ratio could be predicted accurately with a mean squared error loss of only 0.05. This study shows that the prediction of the SA/V ratio using AI works, but not of the exact geometry. For this purpose, a global database could be built with a range of geometries to simplify the prescription process.

Immediate release 3D printed oral dosage forms: How different polymers have been explored to reach suitable drug release behaviour

Three-dimensional (3D) printing has been gaining attention as a new technological approach to obtain immediate release (IR) dosage forms. The versatility conferred by 3D printing techniques arises from the suitability of using different polymeric materials in the production of solids with different porosities, geometries, sizes, and infill patterns. The appropriate choice of polymer can facilitate in reaching IR specifications and afford other specific properties to 3D printed solid dosage forms. This review aims to provide an overview of the polymers that have been employed in the development of IR 3D printed dosage forms, mainly considering their in vitro drug release behaviour. The physicochemical and mechanical properties of the IR 3D printed dosage forms will also be discussed, together with the manufacturing process strategies. Up to now, methacrylic polymers, cellulosic polymers, vinyl derivatives, glycols and different polymeric blends have been explored to produce IR 3D printed dosage forms. Their effects on drug release profiles are critically discussed here, giving a complete overview to drive formulators towards a rational choice of polymeric material and thus contributing to future studies in 3D printing of pharmaceuticals.

Formulation and characterization of immediate-release oral dosage forms with zolpidem tartrate fabricated by digital light processing (DLP) 3D printing technique

The introduction of three-dimensional (3D) printing in the pharmaceutical field has made great strides towards innovations in the way drugs are designed and manufactured. In this study, digital light processing (DLP) technique was used to fabricate oral dosage forms of different shapes with zolpidem tartrate (ZT), incorporated within its therapeutic range. Formulation factors, such as poly(ethylene glycol) diacrylate (PEGDA) and poly(ethylene glycol) 400 (PEG 400) ratio, as well as water content, were varied in combination with the surface area/volume (SA/V) ratio to achieve immediate drug release. Hypromellose (HPMC) was used as a stabilizing agent of photoreactive suspensions in an attempt to prevent drug sedimentation and subsequent variations in drug content uniformity. Oral dosage forms with doses in the range from 0.15 mg to 6.37 mg, showing very rapid and rapid drug dissolution, were successfully fabricated, confirming the potential of this technique in drug manufacturing with the ability to provide flexible dose adjustments and desirable release profiles by varying formulation factors and geometry of 3D models. DSC (differential scanning calorimetry), XRPD (X-ray powder diffraction) and scanning electron microscopy (SEM) showed that ZT remained in a crystalline form within printed dosage forms and no interactions were found between ZT and polymers.

Application and Multi-Stage Optimization of Daylight Polymer 3D Printing of Personalized Medicine Products

Additive technologies have undoubtedly become one of the most intensively developing manufacturing methods in recent years. Among the numerous applications, the interest in 3D printing also includes its application in pharmacy for production of small batches of personalized drugs. For this reason, we conducted multi-stage pre-formulation studies to optimize the process of manufacturing solid dosage forms by photopolymerization with visible light. Based on tests planned and executed according to the design of the experiment (DoE), we selected the optimal quantitative composition of photocurable resin made of PEG 400, PEGDA MW 575, water, and riboflavin, a non-toxic photoinitiator. In subsequent stages, we adjusted the printer set-up and process parameters. Moreover, we assessed the influence of the co-initiators ascorbic acid or triethanolamine on the resin’s polymerization process. Next, based on an optimized formulation, we printed and analyzed drug-loaded tablets containing mebeverine hydrochloride, characterized by a gradual release of active pharmaceutical ingredient (API), reaching 80% after 6 h. We proved the possibility of reusing the drug-loaded resin that was not hardened during printing and determined the linear correlation between the volume of the designed tablets and the amount of API, confirming the possibility of printing personalized modified-release tablets.

Recent progress in three-dimensionally-printed dosage forms from a pharmacist perspective

OBJECTIVE

Additive manufacturing (AM), commonly known as 3D printing (3DP), has opened new frontiers in pharmaceutical applications. This review is aimed to summarise the recent development of 3D-printed dosage forms, from a pharmacists' perspective.

METHODS

Keywords including additive manufacturing, 3D printing and drug delivery were used for literature search in PubMed, Excerpta Medica Database (EMBASE) and Web of Science, to identify articles published in the year 2020.

RESULTS

For each 3DP study, the active pharmaceutical ingredients, 3D printers and materials used for the printing were tabulated and discussed. 3DP has found its applications in various dosage forms for oral delivery, transdermal delivery, rectal delivery, vaginal delivery, implant and bone scaffolding. Several topics were discussed in detail, namely patient-specific dosing, customisable drug administration, multidrug approach, varying drug release, compounding pharmacy, regulatory progress and future perspectives. AM is expected to become a common tool in compounding pharmacies to make polypills and personalised medications.

CONCLUSION

3DP is an enabling tool to fabricate dosage forms with intricate structure designs, tailored dosing, drug combinations and controlled release, all of which lend it to be highly conducive to personalisation, thereby revolutionising the future of pharmacy practice.

State-of-the-Art Review of Artificial Neural Networks to Predict, Characterize and Optimize Pharmaceutical Formulation

During the development of a pharmaceutical formulation, a powerful tool is needed to extract the key points from the complicated process parameters and material attributes. Artificial neural networks (ANNs), a promising and more flexible modeling technique, can address real intricate questions in a high parallelism and distributed pattern in the manner of biological neural networks. The data mined and analyzing based on ANNs have the ability to replace hundreds of trial and error experiments. ANNs have been used for data analysis by pharmaceutics researchers since the 1990s and it has now become a research method in pharmaceutical science. This review focuses on the latest application progress of ANNs in the prediction, characterization and optimization of pharmaceutical formulation to provide a reference for the further interdisciplinary study of pharmaceutics and ANNs.

Digital light processing (DLP) 3D printing technique applied in the fabrication of two-layered tablets: The concept of a combined polypill

Ever since 3D printing was introduced to the field of pharmacy, it has caused a paradigm shift from the manufacturing of large-scale to small batches of medicines tailored accordingly to the specific needs of patients. This study aimed to formulate and fabricate two-layered 3D tablets using the digital light processing (DLP) technique. Hydrochlorothiazide (HHT,5%,w/w) and warfarin sodium (WS,5%,w/w) were selected as model drugs. The printing process was initiated with 0.1% of photoinitiator, at a constant ratio of poly(ethylene glycol)diacrylate and poly(ethylene glycol) 400, 1:1, with the addition of water (10%,w/w). Single-layered tablets of 8.00 mm diameter and 1.50 mm thickness, containing HHT and WS respectively, were successfully printed, as well as combined two-layered 3D tablets, with each of the active substances in separate layers. Dissolution tests of single-layered tablets showed immediate, but incomplete release of WS (81.47±1.47%, after 45min), and prolonged and complete release of HHT (98.17±3.11%, after 8h), while significantly slower and incomplete release of both drugs from the combined two-layered 3D tablets was observed. The absence of drug-polymer interaction and presence of a layered cross-sectional tablet structure were confirmed. DLP technique enables simple and rapid fabrication of combined two-layered 3D tablets, while further optimization of formulation factors is necessary to achieve complete drug release.

Stereolithography 3D printing technology in pharmaceuticals: a review

Three-dimensional printing (3DP) technology is an innovative tool used in manufacturing medical devices, producing alloys, replacing biological tissues, producing customized dosage forms and so on. Stereolithography (SLA), a 3D printing technique, is very rapid and highly accurate and produces finished products of uniform quality. 3D formulations have been optimized with a perfect tool of artificial intelligence learning techniques. Complex designs/shapes can be fabricated through SLA using the photopolymerization principle. Different 3DP technologies are introduced and the most promising of these, SLA, and its commercial applications, are focused on. The high speed and effectiveness of SLA are highlighted. The working principle of SLA, the materials used and applications of the technique in a wide range of different sectors are highlighted in this review. An innovative idea of 3D printing customized pharmaceutical dosage forms is also presented. SLA compromises several advantages over other methods, such as cost effectiveness, controlled integrity of materials and greater speed. The development of SLA has allowed the development of printed pharmaceutical devices. Considering the present trends, it is expected that SLA will be used along with conventional methods of manufacturing of 3D model. This 3D printing technology may be utilized as a novel tool for delivering drugs on demand. This review will be useful for researchers working on 3D printing technologies.

3D Printing of Thermo-Sensitive Drugs

Three-dimensional (3D) printing is among the rapidly evolving technologies with applications in many sectors. The pharmaceutical industry is no exception, and the approval of the first 3D-printed tablet (Spiratam^®) marked a revolution in the field. Several studies reported the fabrication of different dosage forms using a range of 3D printing techniques. Thermosensitive drugs compose a considerable segment of available medications in the market requiring strict temperature control during processing to ensure their efficacy and safety. Heating involved in some of the 3D printing technologies raises concerns regarding the feasibility of the techniques for printing thermolabile drugs. Studies reported that semi-solid extrusion (SSE) is the commonly used printing technique to fabricate thermosensitive drugs. Digital light processing (DLP), binder jetting (BJ), and stereolithography (SLA) can also be used for the fabrication of thermosensitive drugs as they do not involve heating elements. Nonetheless, degradation of some drugs by light source used in the techniques was reported. Interestingly, fused deposition modelling (FDM) coupled with filling techniques offered protection against thermal degradation. Concepts such as selection of low melting point polymers, adjustment of printing parameters, and coupling of more than one printing technique were exploited in printing thermosensitive drugs. This systematic review presents challenges, 3DP procedures, and future directions of 3D printing of thermo-sensitive formulations.

Harnessing artificial intelligence for the next generation of 3D printed medicines

Artificial intelligence (AI) is redefining how we exist in the world. In almost every sector of society, AI is performing tasks with super-human speed and intellect; from the prediction of stock market trends to driverless vehicles, diagnosis of disease, and robotic surgery. Despite this growing success, the pharmaceutical field is yet to truly harness AI. Development and manufacture of medicines remains largely in a 'one size fits all' paradigm, in which mass-produced, identical formulations are expected to meet individual patient needs. Recently, 3D printing (3DP) has illuminated a path for on-demand production of fully customisable medicines. Due to its flexibility, pharmaceutical 3DP presents innumerable options during formulation development that generally require expert navigation. Leveraging AI within pharmaceutical 3DP removes the need for human expertise, as optimal process parameters can be accurately predicted by machine learning. AI can also be incorporated into a pharmaceutical 3DP 'Internet of Things', moving the personalised production of medicines into an intelligent, streamlined, and autonomous pipeline. Supportive infrastructure, such as The Cloud and blockchain, will also play a vital role. Crucially, these technologies will expedite the use of pharmaceutical 3DP in clinical settings and drive the global movement towards personalised medicine and Industry 4.0.

Stereolithography Apparatus Evolution: Enhancing Throughput and Efficiency of Pharmaceutical Formulation Development

Pharmaceutical applications of 3D printing technologies are growing rapidly. Among these, vat photopolymerisation (VP) techniques, including Stereolithography (SLA) hold much promise for their potential to deliver personalised medicines on-demand. SLA 3D printing offers advantageous features for pharmaceutical production, such as operating at room temperature and offering an unrivaled printing resolution. However, since conventional SLA apparatus are designed to operate with large volumes of a single photopolymer resin, significant throughput limitations remain. This, coupled with the limited choice of biocompatible polymers and photoinitiators available, hold back the pharmaceutical development using such technologies. Hence, the aim of this work was to develop a novel SLA apparatus specifically designed to allow rapid and efficient screening of pharmaceutical photopolymer formulations. A commercially available SLA apparatus was modified by designing and fabricating a novel resin tank and build platform able to 3D print up to 12 different formulations at a single time, reducing the amount of sample resin required by 20-fold. The novel SLA apparatus was subsequently used to conduct a high throughput screening of 156 placebo photopolymer formulations. The efficiency of the equipment and formulation printability outcomes were evaluated. Improved time and cost efficiency by 91.66% and 94.99%, respectively, has been confirmed using the modified SLA apparatus to deliver high quality, highly printable outputs, thus evidencing that such modifications offer a robust and reliable tool to optimize the throughput and efficiency of vat photopolymerisation techniques in formulation development processes, which can, in turn, support future clinical applications.