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Additive manufacturing, sometimes referred to as 3D printing or AM, has numerous applications in industries like manufacturing, aviation, aerospace, vehicles, and education. It has recently made considerable inroads into the healthcare industry, backed by technology breakthroughs such as fused deposition modeling, binder jetting, and inkjet printing. A variety of biomaterials, such as polycaprolactone, polycarbonate, polypropylene, and polylactic acid, have contributed to this increase. This essay delves into the revolutionary possibilities of 3D printing in healthcare, to shed light on the idea of customized medications via the improvement of efficiency and cost. Researchers are using polymers and additive manufacturing to make customized medical devices. However, obstacles including bureaucratic hurdles, technological developments, and the choice of appropriate materials and printers stand in the way of widespread implementation. To fully realize the promise of 3D printing in healthcare, these challenges must be overcome. The article highlights the revolutionary potential of 3D printing in healthcare by following its development from art and construction to customized drugs and patient-specific medical equipment. In addition to addressing issues like quality control and technological limitations, it emphasizes its wide range of applications in surgical planning, dentistry, and anatomical models. The necessity of adapting regulations and instructional programs is highlighted by discussing future trends like bioprinting and FDA-approved innovations. In order to properly utilize 3D printing in healthcare, this adaption is essential. Personalized prescriptions and increased efficacy from the incorporation of 3D printing could revolutionize the healthcare industry. But even with these advances, problems like choosing the right materials and getting over administrative roadblocks prevent widespread implementation. These challenges need to be successfully overcome for 3D printing in healthcare to reach its full potential.

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Vat photopolymerization has garnered interest from pharmaceutical researchers for the fabrication of personalised medicines, especially for drugs that require high precision dosing or are heat labile. However, the 3D printed structures created thus far have been insoluble, limiting printable dosage forms to sustained-release systems or drug-eluting medical devices which do not require dissolution of the printed matrix. Resins that produce water-soluble structures will enable more versatile drug release profiles and expand potential applications. To achieve this, instead of employing cross-linking chemistry to fabricate matrices, supramolecular chemistry may be used to impart dynamic interaction between polymer chains. In this study, water-soluble drug-loaded printlets (3D printed tablets) are fabricated via digital light processing (DLP) 3DP for the first time. Six formulations with varying ratios of an electrolyte acrylate monomer, [2-(acryloyloxy)ethyl]trimethylammonium chloride (TMAEA), and a co-monomer, 1-vinyl-2-pyrrolidone (NVP), were prepared to produce paracetamol-loaded printlets. 1H NMR spectroscopy analysis confirmed the integration of TMAEA and NVP in the polymer, and residual TMAEA monomers were found to be present only in trace amounts (0.71 - 1.37 %w/w). The apparent molecular mass of the photopolymerised polymer was found to exceed 300,000 Da with hydrodynamic radii of 15 - 20 nm, estimated based on 1H DOSY NMR measurements The loaded paracetamol was completely released from the printlets between 45 minutes to 5 hours. In vivo single-dose acute toxicity studies in rats suggest that the printlets did not cause any tissue damage. The findings reported in this study represent a significant step towards the adoption of vat photopolymerization-based 3DP to produce personalised medicines.

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Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex polydrug implants. However, the multi-factorial nature of the inkjet printing process makes formulation (e.g., composition, surface tension, and viscosity) and printing parameter optimization (e.g., nozzle diameter, peak voltage, and drop spacing) an empirical and time-consuming endeavour. Instead, given the wealth of publicly available data on pharmaceutical inkjet printing, there is potential for a predictive model for inkjet printing outcomes to be developed. In this study, machine learning (ML) models (random forest, multilayer perceptron, and support vector machine) to predict printability and drug dose were developed using a dataset of 687 formulations, consolidated from in-house and literature-mined data on inkjet-printed formulations. The optimized ML models predicted the printability of formulations with an accuracy of 97.22%, and predicted the quality of the prints with an accuracy of 97.14%. This study demonstrates that ML models can feasibly provide predictive insights to inkjet printing outcomes prior to formulation preparation, affording resource- and time-savings.

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3D printing is driving a shift in patient care away from a generalised model and towards personalised treatments. To complement fast-paced clinical environments, 3D printing technologies must provide sufficiently high throughputs for them to be feasibly implemented. Volumetric printing is an emerging 3D printing technology that affords such speeds, being capable of producing entire objects within seconds. In this study, for the first time, rotatory volumetric printing was used to simultaneously produce two torus- or cylinder-shaped paracetamol-loaded Printlets (3D printed tablets). Six resin formulations comprising paracetamol as the model drug, poly(ethylene glycol) diacrylate (PEGDA) 575 or 700 as photoreactive monomers, water and PEG 300 as non-reactive diluents, and lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) as the photoinitiator were investigated. Two printlets were successfully printed in 12 to 32 s and exhibited sustained drug release profiles. These results support the use of rotary volumetric printing for efficient and effective manufacturing of various personalised medicines at the same time. With the speed and precision it affords, rotatory volumetric printing has the potential to become one of the most promising alternative manufacturing technologies in the pharmaceutical industry.

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Three-dimensional printing (3DP) has seen growing interest within the healthcare industry for its ability to fabricate personalized medicines and medical devices. However, it may be burdened by the lengthy empirical process of formulation development. Active research in pharmaceutical 3DP has led to a wealth of data that machine learning could utilize to provide predictions of formulation outcomes. A balanced dataset is critical for optimal predictive performance of machine learning (ML) models, but data available from published literature often only include positive results. In this study, in-house and literature-mined data on hot melt extrusion (HME) and fused deposition modeling (FDM) 3DP formulations were combined to give a more balanced dataset of 1594 formulations. The optimized ML models predicted the printability and filament mechanical characteristics with an accuracy of 84%, and predicted HME and FDM processing temperatures with a mean absolute error of 5.5 °C and 8.4 °C, respectively. The performance of these ML models was better than previous iterations with a smaller and a more imbalanced dataset, highlighting the importance of providing a structured and heterogeneous dataset for optimal ML performance. The optimized models were integrated in an updated web-application, M3DISEEN, that provides predictions on filament characteristics, printability, HME and FDM processing temperatures, and drug release profiles (https://m3diseen.com/predictionsFDM/). By simulating the workflow of preparing FDM-printed pharmaceutical products, the web-application expedites the otherwise empirical process of formulation development, facilitating higher pharmaceutical 3DP research throughput.

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Selective laser sintering (SLS) 3D printing is capable of revolutionising pharmaceutical manufacturing, by producing amorphous solid dispersions in a one-step manufacturing process. Here, 3D-printed formulations loaded with a model BCS class II drug (20% w/w itraconazole) and three grades of hydroxypropyl cellulose (HPC) polymer (-SSL, -SL and -L) were produced using SLS 3D printing. Interestingly, the polymers with higher molecular weights (HPC-L and -SL) were found to undergo a uniform sintering process, attributed to the better powder flow characteristics, compared with the lower molecular weight grade (HPC-SSL). XRPD analyses found that the SLS 3D printing process resulted in amorphous conversion of itraconazole for all three polymers, with HPC-SSL retaining a small amount of crystallinity on the drug product surface. The use of process analytical technologies (PAT), including near infrared (NIR) and Raman spectroscopy, was evaluated, to predict the amorphous content, qualitatively and quantitatively, within itraconazole-loaded formulations. Calibration models were developed using partial least squares (PLS) regression, which successfully predicted amorphous content across the range of 0-20% w/w. The models demonstrated excellent linearity (R2 = 0.998 and 0.998) and accuracy (RMSEP = 1.04% and 0.63%) for NIR and Raman spectroscopy models, respectively. Overall, this article demonstrates the feasibility of SLS 3D printing to produce solid dispersions containing a BCS II drug, and the potential for NIR and Raman spectroscopy to quantify amorphous content as a non-destructive quality control measure at the point-of-care.

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For the last 40 years, praziquantel has been the standard treatment for schistosomiasis, a neglected parasitic disease affecting more than 250 million people worldwide. However, there is no suitable paediatric formulation on the market, leading to off-label use and the splitting of commercial tablets for adults. In this study, we use a recently available technology, direct powder extrusion (DPE) three-dimensional printing (3DP), to prepare paediatric Printlets™ (3D printed tablets) of amorphous solid dispersions of praziquantel with Kollidon® VA 64 and surfactants (Span™ 20 or Kolliphor® SLS). Printlets were successfully printed from both pellets and powders obtained from extrudates by hot melt extrusion (HME). In vitro dissolution studies showed a greater than four-fold increase in praziquantel release, due to the formation of amorphous solid dispersions. In vitro palatability data indicated that the printlets were in the range of praziquantel tolerability, highlighting the taste masking capabilities of this technology without the need for additional taste masking excipients. This work has demonstrated the possibility of 3D printing tablets using pellets or powder forms obtained by HME, avoiding the use of filaments in fused deposition modelling 3DP. Moreover, the main formulation hurdles of praziquantel, such as low drug solubility, inadequate taste, and high and variable dose requirements, can be overcome using this technology.

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3D printing (3DP) is a progressive technology capable of transforming pharmaceutical development. However, despite its promising advantages, its transition into clinical settings remains slow. To make the vital leap to mainstream clinical practice and improve patient care, 3DP must harness modern technologies. Machine learning (ML), an influential branch of artificial intelligence, may be a key partner for 3DP. Together, 3DP and ML can utilise intelligence based on human learning to accelerate drug product development, ensure stringent quality control (QC), and inspire innovative dosage-form design. With ML's capabilities, streamlined 3DP drug delivery could mark the next era of personalised medicine. This review details how ML can be applied to elevate the 3DP of pharmaceuticals and importantly, how it can expedite 3DP's integration into mainstream healthcare.

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Powder bed fusion (PBF) is a 3D printing method that selectively consolidates powders into 3D objects using a power source. PBF has various derivatives; selective laser sintering/melting, direct metal laser sintering, electron beam melting and multi-jet fusion. These technologies provide a multitude of benefits that make them well suited for the fabrication of bespoke drug-laden formulations, devices and implants. This includes their superior printing resolution and speed, and ability to produce objects without the need for secondary supports, enabling them to precisely create complex products. Herein, this review article outlines the unique applications of PBF 3D printing, including the main principles underpinning its technologies and highlighting their novel pharmaceutical and biomedical applications. The challenges and shortcomings are also considered, emphasising on their effects on the 3D printed products, whilst providing a forward-thinking view.

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Three-dimensional (3D) printing is an innovative additive manufacturing technology, capable of fabricating unique structures in a layer-by-layer manner. Semi-solid extrusion (SSE) is a subset of material extrusion 3D printing, and through the sequential deposition of layers of gel or paste creates objects of any desired size and shape. In comparison to other extrusion-based technologies, SSE 3D printing employs low printing temperatures which makes it suitable for drug delivery and biomedical applications, and the use of disposable syringes provides benefits in meeting critical quality requirements for pharmaceutical use. Besides pharmaceutical manufacturing, SSE 3D printing has attracted increasing attention in the field of bioelectronics, particularly in the manufacture of biosensors capable of measuring physiological parameters or as a means to trigger drug release from medical devices. This review begins by highlighting the major printing process parameters and material properties that influence the feasibility of transforming a 3D design into a 3D object, and follows with a discussion on the current SSE 3D printing developments and their applications in the fields of pharmaceutics, bioprinting and bioelectronics. Finally, the advantages and limitations of this technology are explored, before focusing on its potential clinical applications and suitability for preparing personalised medicines.

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Ulcerative colitis is a global health problem, affecting millions of individuals worldwide. As an inflammatory condition localised in the large intestine, rectal delivery of immunosuppressive therapies such as tacrolimus is a promising strategy to maximise drug concentration at the site of action whilst minimising systemic side effects. Here, for the first time, self-supporting 3D-printed tacrolimus suppositories were prepared without the aid of moulds using a pharmaceutical semi-solid extrusion (SSE) 3D printer. The suppositories were printed vertically in three different sizes using combinations of two lipid pharmaceutical excipients (Gelucire 44/14 or Gelucire 48/16) and coconut oil. Although both suppository formulations had the appropriate viscosity characteristics for printing, the Gel 44 formulation required less energy and force for extrusion compared to the Gel 48 system. The Gel 44 disintegrated more rapidly but released tacrolimus more slowly than the Gel 48 suppositories. Although the tacrolimus release profiles were significantly different, both suppository systems released more than 80% drug within 120 min. DSC and XRD analysis was inconclusive in determining the solid-state properties of the drug in the suppositories. In summary, this article reports on the fabrication of 3D printed self-supporting suppositories to deliver personalised doses of a narrow therapeutic index drug, with potential benefits for patients with ulcerative colitis.

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Oral films (OFs) continue to attract attention as drug delivery systems, particularly for pedatric and geriatric needs. However, immiscibility between different polymers limits the full potential of OFs from being explored. One example is pullulan (PUL), a novel biopolymer which often has to be blended with other polymers to reduce cost and alter its mechanical properties. In this study, the state-of-the-art in fabrication techniques, three-dimensional (3D) printing was used to produce hybrid film structures of PUL and hydroxypropyl methylcellulose (HPMC), which were loaded with caffeine as a model drug. 3D printing was used to control the spatial deposition of films. HPMC was found to increase the mean mechanical properties of PUL films, where the tensile strength, elastic modulus and elongation break increased from 8.9 to 14.5 MPa, 1.17 to 1.56 GPa and from 1.48% to 1.77%, respectively. In addition, the spatial orientation of the hybrid films was also explored to determine which orientation could maximize the mechanical properties of the hybrid films. The results revealed that 3D printing could modify the mechanical properties of PUL whilst circumventing the issues associated with immiscibility.

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Three-dimensional (3D) printing is transforming manufacturing paradigms within healthcare. Vat photopolymerization 3D printing technology combines the benefits of high resolution and favourable printing speed, offering a sophisticated approach to fabricate bespoke medical devices and drug delivery systems. Herein, an overview of the vat polymerization techniques, their unique applications in the fields of drug delivery and medical device fabrication, material examples and the advantages they provide within healthcare, is provided. The challenges and drawbacks presented by this technology are also discussed. It is forecast that the adoption of 3D printing could pave the way for a personalised health system, advancing from traditional treatments pathways towards digital healthcare.

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The aim of this study was to fabricate novel self-supporting tacrolimus suppositories using semisolid extrusion 3-dimensional printing (3DP) and to investigate their efficacy in an experimental model of inflammatory bowel disease. Blends of Gelucire 44/14 and coconut oil were employed as lipid excipients to obtain suppository formulations with self-emulsifying properties, which were then tested in a TNBS (2,4,6-trinitrobenzenesulfonic acid) induced rat colitis model. Disease activity was monitored using PET/CT medical imaging; maximum standardized uptake values (SUVmax), a measure of tissue radiotracer accumulation rate, together with body weight changes and histological assessments, were used as inflammatory indices to monitor treatment efficacy. Following tacrolimus treatment, a significant reduction in SUVmax was observed on days 7 and 10 in the rat colon sections compared to non-treated animals. Histological analysis using Nancy index confirmed disease remission. Moreover, statistical analysis showed a positive correlation (R2 = 71.48%) between SUVmax values and weight changes over time. Overall, this study demonstrates the effectiveness of 3D printed tacrolimus suppositories to ameliorate colitis and highlights the utility of non-invasive PET/CT imaging to evaluate new therapies in the preclinical area.

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3D printing (3DP) in the pharmaceutical field is a disruptive technology that allows the preparation of personalised medicines at the point of dispensing. The paediatric population presents a variety of pharmaceutical formulation challenges such as dose flexibility, patient compliance, taste masking and the fear or difficulty to swallow tablets, all factors that could be overcome using the adaptable nature of 3DP. User acceptability studies of 3D printed formulations have been previously carried out in adults; however, feedback from children themselves is essential in establishing the quality target product profile towards the development of age-appropriate medicines. The aim of this study was to investigate the preference of children for different 3D printed tablets (Printlets™) as an important precursor to patient acceptability studies. Four different 3DP technologies; digital light processing (DLP), selective laser sintering (SLS), semi-solid extrusion (SSE) and fused deposition modeling (FDM) were used to prepare placebo printlets with similar physical attributes including size and shape. A single-site, two-part survey was completed with participants aged 4-11 years to determine their preference and opinions based on visual inspection of the printlets. A total of 368 participants completed an individual open questionnaire to visually select the best and worst printlet, and 310 participants completed further non-compulsory open questions to elaborate on their choices. Overall, the DLP printlets were the most visually appealing to the children (61.7%) followed by the SLS printlets (21.2%), and with both the FDM (5.4%) and SSE (11.7%) printlets receiving the lowest scores. However, after being informed that the SSE printlets were chewable, the majority of participants changed their selection and favoured this printlet, despite their original choice, in line with children's preference towards chewable dosage forms. Participant age and sex displayed no significant differences in printlet selection. Printlet descriptions were grouped into four distinct categories; appearance, perceived taste, texture and familiarity, and were found to be equally important when creating a quality target product profile for paediatric 3D printed formulations. This study is the first to investigate children's perceptions of printlets, and the findings aim to provide guidance for further development of paediatric-appropriate medicines using different 3DP technologies.

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Rheology is an indispensable tool for formulation development, which when harnessed, can both predict a material's performance and provide valuable insight regarding the material's macrostructure. However, rheological characterizations are under-utilized in 3D printing of drug formulations. In this study, viscosity measurements were used to establish a mathematical model for predicting the printability of fused deposition modelling 3D printed tablets (Printlets). The formulations were composed of polycaprolactone (PCL) with different amounts of ciprofloxacin and polyethylene glycol (PEG), and different molecular weights of PEG. With all printing parameters kept constant, both binary and ternary blends were found to extrude at nozzle temperatures of 130, 150 and 170 °C. In contrast PCL was unextrudable at 130 and 150 °C. Three standard rheological models were applied to the experimental viscosity measurements, which revealed an operating viscosity window of between 100 and 1000 Pa·s at the apparent shear rate of the nozzle. The drug release profiles of the printlets were experimentally measured over seven days. As a proof-of-concept, machine learning models were developed to predict the dissolution behaviour from the viscosity measurements. The machine learning models were discovered to accurately predict the dissolution profile, with the highest f2 similarity score value of 90.9 recorded. Therefore, the study demonstrated that using only the viscosity measurements can be employed for the simultaneous high-throughput screening of formulations that are printable and with the desired release profile.

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Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) three-dimensional printing (3DP) has made significant advancements in the field of oral drug delivery with personalized drug-loaded formulations being designed, developed and dispensed for the needs of the patient. The FDM 3DP process begins with the production of drug-loaded filaments by hot melt extrusion (HME), followed by the printing of a drug product using a FDM 3D printer. However, the optimization of the fabrication parameters is a time-consuming, empirical trial approach, requiring expert knowledge. Here, M3DISEEN, a web-based pharmaceutical software, was developed to accelerate FDM 3D printing using AI machine learning techniques (MLTs). In total, 614 drug-loaded formulations were designed from a comprehensive list of 145 different pharmaceutical excipients, 3D printed and assessed in-house. To build the predictive tool, a dataset was constructed and models were trained and tested at a ratio of 75:25. Significantly, the AI models predicted key fabrication parameters with accuracies of 76% and 67% for the printability and the filament characteristics, respectively. Furthermore, the AI models predicted the HME and FDM processing temperatures with a mean absolute error of 8.9 °C and 8.3 °C, respectively. Strikingly, the AI models achieved high levels of accuracy by solely inputting the pharmaceutical excipient trade names. Therefore, AI provides an effective holistic modeling technology and software to streamline and advance 3DP as a significant technology within drug development. M3DISEEN is available at (http://m3diseen.com/predictions/).

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Zero-order release formulations are designed to release a drug at a constant rate over a prolonged time, thus reducing systemic side effects and improving patience adherence to the therapy. Such formulations are traditionally complex to manufacture, requiring multiple steps. In this work, fused deposition modeling (FDM) 3D printing was explored to prepare on-demand printlets (3D printed tablets). The design includes a prolonged release core surrounded by an insoluble shell able to provide zero-order release profiles. The effect of drug loading (10, 25, and 40% w/w paracetamol) on the mechanical and physical properties of the hot melt extruded filaments and 3D printed formulations was evaluated. Two different shell 3D designs (6 mm and 8 mm diameter apertures) together with three different core infills (100, 50, and 25%) were prepared. The formulations showed a range of zero-order release profiles spanning 16 to 48 h. The work has shown that with simple formulation design modifications, it is possible to print extended release formulations with tunable, zero-order release kinetics. Moreover, by using different infill percentages, the dose contained in the printlet can be infinitely adjusted, providing an additive manufacturing route for personalizing medicines to a patient.

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Pharmaceutical three-dimensional (3D) printing is a modern fabrication process with the potential to create bespoke drug products of virtually any shape and size from a computer-aided design model. Selective laser sintering (SLS) 3D printing combines the benefits of high printing precision and capability, enabling the manufacture of medicines with unique engineering and functional properties. This article reviews the current state-of-the-art in SLS 3D printing, including the main principles underpinning this technology, and highlights the diverse selection of materials and essential parameters that influence printing. The technical challenges and processing conditions are also considered in the context of their effects on the printed product. Finally, the pharmaceutical applications of SLS 3D printing are covered, providing an emphasis on the advantages the technology offers to drug product manufacturing and personalised medicine.

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Visual impairment and blindness affects 285 million people worldwide, resulting in a high public health burden. This study reports, for the first time, the use of three-dimensional (3D) printing to create orally disintegrating printlets (ODPs) suited for patients with visual impairment. Printlets were designed with Braille and Moon patterns on their surface, enabling patients to identify medications when taken out of their original packaging. Printlets with different shapes were fabricated to offer additional information, such as the medication indication or its dosing regimen. Despite the presence of the patterns, the printlets retained their original mechanical properties and dissolution characteristics, wherein all the printlets disintegrated within ~5 s, avoiding the need for water and facilitating self-administration of medications. Moreover, the readability of the printlets was verified by a blind person. Overall, this novel and practical approach should reduce medication errors and improve medication adherence in patients with visual impairment.