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Medical devices are a key element of patient diagnosis and treatment. They could be basic diagnostic tools like tongue depressors and thermometers or complicated, curative implantation like heart valves and coronary stents. Rigorous regulatory requirements are necessary to guarantee that medical devices are well-studied, safe, and well-tolerated in light of their growing use. Many medical devices are in use today, and their marketing is subject to various laws and regulations across different countries. A medical device must have its marketing authorization approved by the relevant regulatory body in order to be sold on the market. The ASEAN (Association of Southeast Asian Nations) Medical Device Directive (AMDD) is an agreement designed for the convergence of medical device laws among ASEAN nations. The current study aims to better understand the medical device registration procedure, fees, and timelines in Singapore and Thailand. This review explains the appropriate local legislation for creating, importing, or selling a medical device in Singapore and Thailand.

Plant pathologists desire an accurate and reliable soybean plant disease diagnosis system. In this study, we propose an efficient soybean diseases identification method based on a transfer learning approach by using pretrained AlexNet and GoogleNet convolutional neural networks (CNNs). The proposed AlexNet and GoogleNet CNNs were trained using 649 and 550 image samples of diseased and healthy soybean leaves, respectively, to identify three soybean diseases. We used the five-fold cross-validation strategy. The proposed AlexNet and GoogleNet CNN-based models achieved an accuracy of 98.75% and 96.25%, respectively. This accuracy was considerably higher than that for conventional pattern recognition techniques. The experimental results for the identification of soybean diseases indicated that the proposed model achieved highest efficiency.

A 23Factorial design of cissus-gelatin B polymer blends was developed to formulate amodiaquine HCl-artesunate (AQ-AS) microparticles by varying the polymer blend concentration (2 %w/v, 5 %w/v), crosslinking time (0.5 h, 1 h) and glutaraldehye volume (0.5 ml, 1 ml). The formulations were evaluated using drug entrapment efficiency (EE), particle size, polydispersity index, thermal behavior with differential scanning calorimetry, crystallinity with powder X-ray diffraction, morphology with scanning electron microscope and in vitrorelease using combination of simulated gastric fluid (SGF, pH = 7.4, 95%) and methanol (5%). The expected responses, EE and in vitrorelease were fitted into Design Expert®.

Mucoadhesive polymers have recently gained interest among pharmaceutical scientists as a means of improving drug delivery by promoting the residence time and contact time of the dosage form with the mucous membranes. Mucoadhesion is the process whereby synthetic and natural polymers adhere to mucosal surfaces in the body. If these materials are then incorporated into pharmaceutical formulations, drug absorption by mucosal cells may be enhanced or the drug will be released at the site for an extended period of time. Microspheres, in general, have the potential to be used for targeted and controlled release drug delivery; however, coupling of mucoadhesive properties to microspheres has additional advantages like, a much more intimate contact with the mucus layer, efficient absorption and enhanced bioavailability of the drugs due to a high surface to volume ratio. The present review describes the potential applications of mucoadhesive microspheres as a novel carrier system to improve drug delivery by various routes of administration like buccal, oral, nasal, ocular, vaginal and rectal, either for systemic or for local effects. The mucoadhesive polymers, methods of preparation of microspheres and their in vitro and in vivo evaluation are also described.