The aim of this review is to present the factors influencing the mechanical properties of 3D-printed oral dosage forms. It also explores how it is possible to use specific excipients and printing parameters to maintain the structural integrity of printed drug products while meeting the needs of patients. Three-dimensional (3D) printing is an emerging manufacturing technology that is gaining acceptance in the pharmaceutical industry to overcome traditional mass production and move toward personalized pharmacotherapy. After continuous research over the last thirty years, 3D printing now offers numerous opportunities to personalize oral dosage forms in terms of size, shape, release profile, or dose modification. However, there is still a long way to go before 3D printing is integrated into clinical practice. 3D printing techniques follow a different process than traditional oral dosage from manufacturing methods. Currently, there are no specific guidelines for the hardness and friability of 3D printed solid oral dosage forms. Therefore, new regulatory frameworks for 3D-printed oral dosage forms should be established to ensure that they meet all appropriate quality standards. The evaluation of mechanical properties of solid dosage forms is an integral part of quality control, as tablets must withstand mechanical stresses during manufacturing processes, transportation, and drug distribution as well as rough handling by the end user. Until now, this has been achieved through extensive pre- and post-processing testing, which is often time-consuming. However, computational methods combined with 3D printing technology can open up a new avenue for the design and construction of 3D tablets, enabling the fabrication of structures with complex microstructures and desired mechanical properties. In this context, the emerging role of computational methods and artificial intelligence techniques is highlighted.

Skin care formulations have evolved as the interaction of health and beauty products for the skin. Their benefits are based on the combination of cosmetic active ingredients and targeted application. Cosmetic actives have been used in novel formulations for decades (sunscreens, anti-aging treatments, etc.), but the problems with their low solubility, low penetration, and physicochemical instability when applied to the skin have yet to be solved. One way to circumvent these shortcomings is to use lipid carriers, which are known to play an important role in the solubility of poorly soluble compounds by facilitating skin permeation and improving stability. This review addresses recent advances in skin care products that use novel nanotechnology-based lipid systems (liposomes, solid lipid nanoparticles, etc.) to deliver moisturizing cosmetic actives and improve product efficacy.

Furosemide, a chloride channel blocker ordinarily used as a high-ceiling or loop diuretic, is practically insoluble in water and dilute acids. Due to its acidic nature, furosemide is mostly absorbed in the stomach and in the upper small intestine. Efforts have focused on the development of sustained release systems of furosemide in order to improve the effectiveness of the drug, which exhibits poor aqueous solubility and poor permeability. Recently, electrospun nanofibrous drug delivery systems have emerged as promising alternative solid-dosage forms due to their advantages of high porosity, high surface to volume ratio, and high drug-loading efficacy. Herein, a number of nanofibrous mats composed of different types of Eudragit^® polymers in various concentrations and combinations loaded with furosemide were designed, successfully electrospun, and characterized using SEM, FTIR, DSC, and TGA analyses. The nanofibrous nonwovens were formulated in nanofiber tablets and the release profile of furosemide from them was evaluated at pH 1.2 and 6.8 and compared to that of physical mixture matrix tablets of analogous composition as well as to that of a commercial formulation. It was found that the release of furosemide was compatible with the gastroretentive and slower intestinal release requirements with a well-defined absorption window, while some nanofiber formulations could act as furosemide carriers in emergency situations where a relatively fast onset of its action is required, as in the case of critically ill post-traumatic patients.

Direct compression (DC) remains a popular manufacturing technology for producing solid dosage forms. However, the formulation optimisation is a laborious process, costly and time-consuming. The aim of this study was to determine whether machine learning (ML) can be used to accelerate developments by predicting the drug release profiles under dynamic conditions given the composition of formulations. A total of 377 formulations were produced in-house and their release profile under dynamic dissolution conditions was measured from 0 to 480 min across 11 time points. A subsequent ML analysis involved predicting the entire release profile. Six different ML techniques were explored, where random forest (RF) and extreme gradient boosting (XGB) were found to achieve a fivefold cross-validation R² of 0.635 ± 0.047 and 0.601 ± 0.091, respectively. A second ML strategy was developed, where the ML techniques predict the kinetic parameters of the Weibull and a modified first-order kinetic release model and subsequently use the predicted parameters to fit the release profiles. The R² results using RF were comparable to the first strategy. These findings demonstrate that ML can be used to predict entire drug release profiles during dynamic dissolution studies, whilst simultaneously providing insight into kinetic parameters, thus making the modelling process more informative for pharmaceutical researchers. Future work will seek to investigate more ‘kinetic-informed’ ML models. Graphical Abstract