Influence of Print Settings on the Critical Quality Attributes of Extrusion-Based 3D-Printed Caplets: A Quality-by-Design Approach

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.

Design of experiment and machine learning inform on the 3D printing of hydrogels for biomedical applications

In the biomedical field, 3D printing has the potential to deliver on some of the promises of personalized therapy, notably by enabling point-of-care fabrication of medical devices, dosage forms and bioimplants. To achieve this full potential, a better understanding of the 3D printing processes is necessary, and non-destructive characterization methods must be developed. This study proposes methodologies to optimize the 3D printing parameters for soft material extrusion. We hypothesize that combining image processing with design of experiment (DoE) analyses and machine learning could help obtaining useful information from a quality-by-design perspective. Herein, we investigated the impact of three critical process parameters (printing speed, printing pressure and infill percentage) on three critical quality attributes (gel weight, total surface area and heterogeneity) monitored with a non-destructive methodology. DoE and machine learning were combined to obtain information on the process. This work paves the way for a rational approach to optimize 3D printing parameters in the biomedical field.

Application of 3D Bioprinting in Liver Diseases

Liver diseases are the primary reason for morbidity and mortality in the world. Owing to a shortage of organ donors and postoperative immune rejection, patients routinely suffer from liver failure. Unlike 2D cell models, animal models, and organoids, 3D bioprinting can be successfully employed to print living tissues and organs that contain blood vessels, bone, and kidney, heart, and liver tissues and so on. 3D bioprinting is mainly classified into four types: inkjet 3D bioprinting, extrusion-based 3D bioprinting, laser-assisted bioprinting (LAB), and vat photopolymerization. Bioinks for 3D bioprinting are composed of hydrogels and cells. For liver 3D bioprinting, hepatic parenchymal cells (hepatocytes) and liver nonparenchymal cells (hepatic stellate cells, hepatic sinusoidal endothelial cells, and Kupffer cells) are commonly used. Compared to conventional scaffold-based approaches, marked by limited functionality and complexity, 3D bioprinting can achieve accurate cell settlement, a high resolution, and more efficient usage of biomaterials, better mimicking the complex microstructures of native tissues. This method will make contributions to disease modeling, drug discovery, and even regenerative medicine. However, the limitations and challenges of this method cannot be ignored. Limitation include the requirement of diverse fabrication technologies, observation of drug dynamic response under perfusion culture, the resolution to reproduce complex hepatic microenvironment, and so on. Despite this, 3D bioprinting is still a promising and innovative biofabrication strategy for the creation of artificial multi-cellular tissues/organs.

Towards the personalization of gelatin-based 3D patches: a tunable porous carrier for topical applications

Cell-free based therapies, for example, the use of the cell secretome, have emerged as a promising alternative to conventional skin therapies using bioactive and, when combined with 3D printing technologies, allow the development of personalized dosage forms. This research work aimed to develop gelatin-based patches with controlled network topology via extrusion 3D printing, loaded with cell culture medium as a model of the secretome, and applicable as vehicles for topical delivery. Inks were optimized through rheological and printing assays, and the incorporation of medium had minor effects in printability. Regarding network topology, grid infills rendered more defined structures than the triangular layout, depicting clearer pores and pore area consistency. Release studies showed that filament spacing and infill pattern influenced the release of rhodamine B (model bioactive) and bovine serum albumin (model protein). Moreover, the grid patches (G-0.7/1/0.7), despite having around a seven-fold higher mean pore area than 0.7-mm triangular ones (T-0.7), showed a similar release profile, which can be linked to the network topology of the printed structures This work provided insight on employing (bio)printing in the production of carriers with reproducible and controlled pore area, able to incorporate cell-derived secretome and to be quickly tailored to the patient's lesions.

Predicting Failure of Additively Manufactured Specimens with Holes

Experimental and computational studies were conducted to predict failure loads of specimens containing different-sized holes made using the additive manufacturing (AM) technique. Two different types of test specimens were prepared. Flat specimens, manufactured from polylactic acid (PLA), were subjected to uniaxial loading. Tubular specimens, made of polycarbonate (PC), were subjected to combined loading that was applied using uniaxial testing equipment. Test specimens were uniquely designed and printed to apply the combined bending and torsional loads to tubular specimens. A newly developed failure theory was applied to predict the loads that would result in the fracture of these test specimens. This theory is composed of two conditions related to stress and the stress gradient to be simultaneously satisfied to predict failure. The failure loads predicted using the new failure criteria were compared closely with the experimental data for all test specimens. In addition, a semi-empirical equation was developed to predict the critical failure surface energy for different printing angles. The critical failure surface energy is a material property and is used for the stress gradient condition. Using the semi-empirically determined values for the failure criterion provided close agreement with experimental results.

3D Printing Technologies in Personalized Medicine, Nanomedicines, and Biopharmaceuticals

3D printing technologies enable medicine customization adapted to patients' needs. There are several 3D printing techniques available, but majority of dosage forms and medical devices are printed using nozzle-based extrusion, laser-writing systems, and powder binder jetting. 3D printing has been demonstrated for a broad range of applications in development and targeting solid, semi-solid, and locally applied or implanted medicines. 3D-printed solid dosage forms allow the combination of one or more drugs within the same solid dosage form to improve patient compliance, facilitate deglutition, tailor the release profile, or fabricate new medicines for which no dosage form is available. Sustained-release 3D-printed implants, stents, and medical devices have been used mainly for joint replacement therapies, medical prostheses, and cardiovascular applications. Locally applied medicines, such as wound dressing, microneedles, and medicated contact lenses, have also been manufactured using 3D printing techniques. The challenge is to select the 3D printing technique most suitable for each application and the type of pharmaceutical ink that should be developed that possesses the required physicochemical and biological performance. The integration of biopharmaceuticals and nanotechnology-based drugs along with 3D printing ("nanoprinting") brings printed personalized nanomedicines within the most innovative perspectives for the coming years. Continuous manufacturing through the use of 3D-printed microfluidic chips facilitates their translation into clinical practice.

Investigation on the use of fused deposition modeling for the production of IR dosage forms containing Timapiprant

The present work focused on evaluating the feasibility of fused deposition modeling (FDM) in the development of a dosage form containing Timapiprant (TMP), also known as CHF6532, which is a novel active molecule indicated in the potential treatment of eosinophilic asthma upon oral administration. The resulting product could be an alternative, with potential towards personalization, of immediate release (IR) tablets used in the clinical studies. Formulations based on different polymeric carriers were screened, leading to the identification of a polyvinyl alcohol-based one, which turned out acceptable for versatility in terms of active ingredient content, printability and dissolution performance (i.e. capability to meet the dissolution specification set, envisaging >80% of the drug dissolved within 30 min). Following an in-depth evaluation on the influence of TMP solid state and of the voids volume resulting from printing on dissolution, few prototypes with shapes especially devised for therapy customization were successfully printed and were compliant with the dissolution specification set.

3D printed, personalized sustained release cortisol for patients with adrenal insufficiency

The standard of care for patients with Adrenal Insufficiency (AI) is suboptimal. Administration of hydrocortisone three times a day produces plasma cortisol fluctuations associated with negative health outcomes. Furthermore, there is a high inter-individual variability in cortisol need, necessitating a personalized approach. It is hypothesized that a personalized, sustained release formulation would enhance the pharmacotherapy by mimicking the physiological cortisol plasma concentration at a higher level. Therefore, a novel 24 h sustained release 3D printed (3DP) hydrocortisone formulation has been developed (M3DICORT) by coupling hot-melt extrusion with fused deposition modeling. A uniform drug distribution in the 3DP tablets is demonstrated by a content of 101.66 ± 1.60 % with an acceptance value of 4.01. Furthermore, tablets had a stable 24 h dissolution profile where the intra-batch standard deviation was ± 2.8 % and the inter-batch standard deviation was ± 6.8 %. Tablet height and hydrocortisone content were correlated (R² = 0.996), providing a tool for easy dose personalization. Tablets maintained critical quality attributes, such as dissolution profile (f2 > 60) and content uniformity after process transfer from a single-screw extruder to a twin-screw extruder. Impurities were observed in the final product which should be mitigated before clinical assessment. To our knowledge, M3DICORT is the first 3DP hydrocortisone formulation specifically developed for AI.

Accelerating 3D printing of pharmaceutical products using machine learning

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.

Extrusion 3D printing of minicaplets for evaluating in vitro & in vivo praziquantel delivery capability

This study aimed to explore extrusion three dimensional (3D) printing technology to develop praziquantel (PZQ)-loaded minicaplets and evaluate their in vitro and in vivo delivery capabilities. PZQ-loaded minicaplets were 3D printed using a fused deposition modelling (FDM) principle-based extrusion 3D printer and were further characterized by different in vitro physicochemical and sophisticated analytical techniques. In addition, the % PZQ entrapment and in vitro PZQ release performance were evaluated using chromatographic techniques. It was in vitro observed that PZQ was fully released in the gastric pH medium within the period of gastric emptying, that is, 120 min, from the PZQ-loaded 3D printed minicaplets. Furthermore, in vivo pharmacokinetic (PK) profiles of PZQ-loaded 3D printed minicaplets were systematically evaluated using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The PK profile of the PZQ-loaded 3D printed minicaplets was established using different parameters such as C_max, T_max, AUC_0-t, AUC_0-∞, and oral relative bioavailability (RBA). The C_max value of pristine PZQ was found at 64.79 ± 13.99 ng/ml, while PZQ-loaded 3D printed minicaplets showed a C_max of 263.16 ± 47.85 ng/ml. Finally, the PZQ-loaded 3D printed minicaplets showed 9.0-fold improved oral RBA compared with that of pristine PZQ (1.0-fold). Together, these observations potentiate the desired in vitro and improved in vivo delivery capabilities of PZQ from the PZQ-loaded 3D printed minicaplets.

Development and evaluation of a 3D printing protocol to produce zolpidem-containing printlets, as compounding preparation, by the pressurized-assisted microsyringes technique

Insomnia is a chronic disorder with a mean prevalence ranged from 6% to 15% worldwide. The usual pharmacologic treatment for insomnia has been benzodiazepines and barbiturates. More recently, z-drugs were introduced in the therapeutic arsenal to maximize benefits and minimize treatment damage. Zolpidem tartrate, whose primary indication is for sleep initiation problems, is conventionally used at a recommended dose of 5 mg for women as well as elderly patients (<65 years-old) and 10 mg for non-elderly men. However, it was demonstrated that the dose of zolpidem should be adjusted according to the gender, age, condition of the patient and the presence of polypharmacy to decrease the occurrence of adverse events. Faced with the therapeutic limitations inherent to marketed products, magistral preparations offer medical and legal alternatives to mass treatment. The use of a semi-automatic technique, with standardized protocol, such as 3D printing should be advantageously implemented as an alternative to standard compounding procedures. In this work, the pressure-assisted microsyringes method was selected as it allows the tridimensional printing, and so the customization of the dose, by easily extruding a viscous semi-liquid material, called "slurry", through a syringe at room temperature. It has been demonstrated that this methodology allows obtaining printlets that responded to the zolpidem-containing tablets monograph of the US pharmacopoeia Edition 42. The compounding preparations proposed in this work therefore have the same criteria of requirements as a commercial form.

Blind-Watermarking—Proof-of-Concept of a Novel Approach to Ensure Batch Traceability for 3D Printed Tablets

Falsified medicines are a major issue and a threat around the world. Various approaches are currently being investigated to mitigate the threat. In this study, a concept is tested that encodes binary digits (bits) on the surface of Fused Deposition Modelling (FDM) 3D printed geometries. All that is needed is a computer, a FDM 3D printer and a paper scanner for detection. For the experiments, eleven different formulations were tested, covering the most used polymers for 3D printing in pharma: Ethylene-vinyl acetate (EVA), polyvinyl alcohol (PVA), polylactic acid (PLA), Hypromellose (HPMC), ethyl cellulose (EC), basic butylated-methacrylate-copolymer (EPO), and ammonio-methacrylate-copolymer type A (ERL). In addition, the scanning process and printing process were evaluated. It was possible to print up to 32 bits per side on oblong shaped tablets corresponding to the dimensions of market preparations of oblong tablets and capsules. Not all polymers or polymer blends were suitable for this method. Only PVA, PLA, EC, EC+HPMC, and EPO allowed the detection of bits with the scanner. EVA and ERL had too much surface roughness, too low viscosity, and cooled down too slowly preventing the detection of bits. It was observed that the addition of a colorant or active pharmaceutical ingredient (API) could facilitate the detection process. Thus, the process could be transferred for 3D printed pharmaceuticals, but further improvement is necessary to increase robustness and allow use for more materials.