Simulation and evaluation of rupturable coated capsules by finite element method

Application and evaluation of fused deposition modeling technique in customized medical products

The fused deposition modeling (FDM) technique has enormous potential for developing customized medical products with complicated structures. In this study, the application of the FDM technique to three medical products was investigated, and the risk factors affecting product quality were evaluated. For FDM-printed matrix and reservoir preparations, special attention should be paid to spacing width reduction and layered coating thickness. Therefore, spacing printing fidelity and interlayer bonding strength was established as unique indexes to characterize the effectiveness and safety of FDM-printed medicine. For FDM-printed orthopedic implants, layer height affected the dimensional deviation of surface morphology, which could be digitally evaluated. Moreover, internal structure affected the biomechanical behavior, which could be investigated using in silico simulation. The results reveal the broad application of FDM technology in customized medical products and might help to establish scientific and reasonable evaluation systems for them.

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.

Printability of External and Internal Structures Based on Digital Light Processing 3D Printing Technique

The high printing efficiency and easy availability of desktop digital light processing (DLP) printers have made DLP 3D printing a promising technique with increasingly broad application prospects, particularly in personalized medicine. The objective of this study was to fabricate and evaluate medical samples with external and internal structures using the DLP technique. The influence of different additives and printing parameters on the printability and functionality of this technique was thoroughly evaluated. It was observed that the printability and mechanical properties of external structures were affected by the poly(ethylene glycol) diacrylate (PEGDA) concentration, plasticizers, layer height, and exposure time. The optimal printing solutions for 3D external and internal structures were 100% PEGDA and 75% PEGDA with 0.25 mg/mL tartrazine, respectively. And the optimal layer height for 3D external and internal structures were 0.02 mm and 0.05 mm, respectively. The optimal sample with external structures had an adequate drug-loading ability, acceptable sustained-release characteristics, and satisfactory biomechanical properties. In contrast, the printability of internal structures was affected by the photoabsorber, PEGDA concentration, layer height, and exposure time. The optimal samples with internal structures had good morphology, integrity and perfusion behavior. The present study showed that the DLP printing technique was capable of fabricating implants for drug delivery and physiological channels for in vivo evaluation.

Fabrication and evaluation of dental fillers using customized molds via 3D printing technology

In view of the high incidence and long-term treatment of dental caries, personalized dental fillers with long therapeutic action have broad application prospects in the dental clinic. The objective of this study was to fabricate and evaluate novel dental fillers using state-of-the-art 3D printing technology. Tinidazole (TNZ), a commonly used antibacterial drug in the dental clinic, was chosen as the model compound. Models of molars with carious cavities were obtained via 3D scanning. TNZ dental fillers were indirectly produced by thermal pressing using customized 3D printed molds. In addition, bio-relevant in vitro dissolution and mechanical testing methods were developed using customized 3D printed release and compression molds, respectively. It was observed that the formability, mechanical properties, and release behavior of the TNZ dental fillers were affected by mold materials, plasticizers, and release modifiers. The developed dental fillers were capable of sustained releasing TNZ over one week. The TNZ release characteristics can be tailored based on clinical requirements by varying hydroxypropyl methylcellulose E5 (HPMC-E5) concentrations and filler dimensions. Moreover, computational simulation based on the finite element method showed that the biomechanical behavior of the TNZ dental fillers met the daily use requirement. The present study demonstrated that the state-of-the-art 3D printing technology can be used to design and fabricate personalized dental fillers with high mechanical strength and "on-demand" drug release characteristics.