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Oral Disintegrating Tablets (ODTs) is a novel dosage form that can be dissolved on the tongue within 3min or less especially for geriatric and pediatric patients. Current ODT formulation studies usually rely on the personal experience of pharmaceutical experts and trial-and-error in the laboratory, which is inefficient and time-consuming. The aim of current research was to establish the prediction model of ODT formulations with direct compression process by Artificial Neural Network (ANN) and Deep Neural Network (DNN) techniques. 145 formulation data were extracted from Web of Science. All data sets were divided into three parts: training set (105 data), validation set (20) and testing set (20). ANN and DNN were compared for the prediction of the disintegrating time. The accuracy of the ANN model has reached 85.60%, 80.00% and 75.00% on the training set, validation set and testing set respectively, whereas that of the DNN model was 85.60%, 85.00% and 80.00%, respectively. Compared with the ANN, DNN showed the better prediction for ODT formulations. It is the first time that deep neural network with the improved dataset selection algorithm is applied to formulation prediction on small data. The proposed predictive approach could evaluate the critical parameters about quality control of formulation, and guide research and process development. The implementation of this prediction model could effectively reduce drug product development timeline and material usage, and proactively facilitate the development of a robust drug product.

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Background: Solid dispersions are an effective formulation technique to improve the solubility, dissolution rate, and bioavailability of water-insoluble drugs for oral delivery. In the last 15 years, increased attention was focused on this technology. There were 23 marketed drugs prepared by solid dispersion techniques. Objective: This study aimed to report the big picture of solid dispersion research from 1980 to 2015. Method: Scientific knowledge mapping tools were used for the qualitative and the quantitative analysis of patents and literature from the time and space dimensions. Results: Western Europe and North America were the major research areas in this field with frequent international cooperation. Moreover, there was a close collaboration between universities and industries, while research collaboration in Asia mainly existed between universities. The model drugs, main excipients, preparation technologies, characterization approaches and the mechanism involved in the formulation of solid dispersions were analyzed via the keyword burst and co-citation cluster techniques. Integrated experimental, theoretical and computational tools were useful techniques for in silico formulation design of the solid dispersions. Conclusions: Our research provided the qualitative and the quantitative analysis of patents and literature of solid dispersions in the last three decades.

Nowadays, destruction of redox homeostasis to induce cancer cell death is an emerging anti‐cancer strategy. Here, the authors utilized pH‐sensitive acetalated β‐cyclodextrin (Ac‐β‐CD) to efficiently deliver dihydroartemisinin (DHA) for tumor ferroptosis therapy and chemodynamic therapy in a synergistic manner. The Ac‐β‐CD‐DHA based nanoparticles are coated by an iron‐containing polyphenol network. In response to the tumor microenvironment, Fe2+/Fe3+ can consume glutathione (GSH) and trigger the Fenton reaction in the presence of hydrogen peroxide (H2O2), leading to the generation of lethal reactive oxygen species (ROS). Meanwhile, the OO bridge bonds of DHA are also disintegrated to enable ferroptosis of cancer cells. Their results demonstrate that these nanoparticles acted as a ROS generator to break the redox balance of cancer cells, showing an effective anticancer efficacy, which is different from traditional approaches.

With the increase concern of solubilization for insoluble drug, ternary solid dispersion (SD) formulations developed more rapidly than binary systems. However, rational formulation design of ternary systems and their dissolution molecular mechanism were still under development. Current research aimed to develop the effective ternary formulations and investigate their molecular mechanism by integrated experimental and modeling techniques. Glipizide (GLI) was selected as the model drug and PEG was used as the solubilizing polymer, while surfactants (e.g., SDS or Tween80) were the third components. SD samples were prepared at different weight ratio by melting method. In the dissolution tests, the solubilization effect of ternary system with very small amount of surfactant (drug/PEG/surfactant 1/1/0.02) was similar with that of binary systems with high polymer ratios (drug/PEG 1/3 and 1/9). The molecular structure of ternary systems was characterized by differential scanning calorimetry (DSC), infrared absorption spectroscopy (IR), X-ray diffraction (XRD), and scanning electron microscope (SEM). Moreover, molecular dynamic (MD) simulations mimicked the preparation process of SDs, and molecular motion in solvent revealed the dissolution mechanism of SD. As the Gordon-Taylor equation described, the experimental and calculated values of Tg were compared for ternary and binary systems, which confirmed good miscibility of GLI with other components. In summary, ternary SD systems could significantly decrease the usage of polymers than binary system. Molecular mechanism of dissolution for both binary and ternary solid dispersions was revealed by combined experiments and molecular modeling techniques. Our research provides a novel pathway for the further research of ternary solid dispersion formulations.

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Mesoporous silica nanoparticles (MSNs) are widely used in the biomedical field because of their unique and excellent properties. However, the potential toxicity of different shaped MSNs via injection has not been fully studied. This study aims to systematically explore the impact of shape and shear stress on the toxicity of MSNs after injection. An in vitro blood flow model was developed to investigate the cytotoxicity and the underlying mechanisms of spherical MSNs (S-MSN) and rodlike MSNs (R-MSN) in human umbilical vein endothelial cells (HUVECs). The results suggested that the interactions between MSNs and HUVECs under the physiological flow conditions were significantly different from that under static conditions. Whether under static or flow conditions, R-MSN showed better cellular uptake and less oxidative damage than S-MSN. The main mechanism of cytotoxicity induced by R-MSN was due to shear stress-dependent mechanical damage of the cell membrane, while the toxicity of S-MSN was attributed to mechanical damage and oxidative damage. The addition of fetal bovine serum (FBS) alleviated the toxicity of S-MSN by reducing cellular uptake and oxidative stress under static and flow conditions. Moreover, the in vivo results showed that both S-MSN and R-MSN caused cardiovascular toxicity in zebrafish and mouse models due to the high shear stress, especially in the heart. S-MSN led to severe oxidative damage at the accumulation site, such as liver, spleen, and lung in mice, while R-MSN did not cause significant oxidative stress. The results of in vitro blood flow and in vivo models indicated that particle shape and shear stress are crucial to the biosafety of MSNs, providing new evidence for the toxicity mechanisms of the injected MSNs.