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Objective: To present an overview of import need for wound care and burn dressings in India. This article provides a complete analysis of the import-export value of wound care and burn dressings in India. It helps in preparing growth strategies, knowledge about leading players, recent developments, business strategies, and manufacturing status of the wound care and burn dressings in India. Methodology: A trend analysis of import-export was carried out for wound and burn dressings in India. Raw data of the years (2008-2017) were collected from various market research analysis sites and import need was identified. Results and Discussion: The detailed analysis reveals that India is a growing market for wound and burn dressings and spends a lot of the exchequer on importing the subject commodity. Wound dressing export is averaged to the same from 2013 to 2017. India saw a rise in wound dressing export after 2012. India saw a rise of wound dressing import over the past 10 years. It averaged 502.6 million from 2008 to 2017 and it reached its all-time high of 765 million in 2016. The import value was found quite high as compared to export. Conclusion: The report of import and export analysis very clearly highlights that there is a strong demand for dressings in the country and due to lack of own manufacturers of such dressing in India, these are imported. Since these products are expensive, there is a large outflow of Indian currency due to imports. It is imperative that such products get government attention and should be manufactured within the country.

We present DeepMVI, a deep learning method for missing value imputation in multidimensional time-series datasets. Missing values are commonplace in decision support platforms that aggregate data over long time stretches from disparate sources, and reliable data analytics calls for careful handling of missing data. One strategy is imputing the missing values, and a wide variety of algorithms exist spanning simple interpolation, matrix factorization methods like SVD, statistical models like Kalman filters, and recent deep learning methods. We show that often these provide worse results on aggregate analytics compared to just excluding the missing data. DeepMVI uses a neural network to combine fine-grained and coarse-grained patterns along a time series, and trends from related series across categorical dimensions. After failing with off-the-shelf neural architectures, we design our own network that includes a temporal transformer with a novel convolutional window feature, and kernel regression with learned embeddings. The parameters and their training are designed carefully to generalize across different placements of missing blocks and data characteristics. Experiments across nine real datasets, four different missing scenarios, comparing seven existing methods show that DeepMVI is significantly more accurate, reducing error by more than 50% in more than half the cases, compared to the best existing method. Although slower than simpler matrix factorization methods, we justify the increased time overheads by showing that DeepMVI is the only option that provided overall more accurate analytics than dropping missing values., Comment: Accepted to VLDB 2021

Objectives: The present study describes a disposable static diffusion cell for in vitro diffusion studies to achieve better results as compared to well existing Franz diffusion cell (FDC) in terms of the absence of bubbles, variable receptor compartment, ease of handling, and faster results.Materials and Methods: The cell consists of a cup-shaped donor compartment made of semi permeable that could be either cellophane membrane or, animal skin fitted to a rigid frame, which is supported on a plastic plate that contains a hole for the sample withdrawal. The receptor compartment is a separate unit, and it could be any container up to 500ml volume capacity. The most preferred receptor compartment is glass beaker. In the present study, goatskin was used as semi-permeable membrane and verification of its performance was carried out through diffusion studies using gel formulations of one each of the four-selected biopharmaceutical classification system (BCS) class drugs. Metronidazole, diclofenac sodium, fluconazole, and sulfadiazine were used as model drugs for BCS Class I, II, III, and IV, respectively.Results: The newly developed diffusion cell (NDDC) was found to provide faster and more reproducible results as compared to FDC. At the time interval of 24 h, the cell was found to exhibit a higher diffusion of metronidazole, diclofenac sodium, fluconazole, and sulfadiazine by 0.65, 0.65, 0.32, and 0.81 folds, respectively. The faster release obtained with NDDC was attributed to a larger surface area of skin as compared to that in FDC.Conclusion: It was concluded that better reproducibility of results could be achieved with NDDC.

Objective: The objective of the study was to present an overview of regulatory requirements for wound and burn care dressings.Methods: A total of 80 research and review articles including regulatory guidelines to control the marketing of wound and burn care dressings recommended by international regulatory agencies were reviewed.Results: A wide range of dressings, as a new target of the healing process, have been developed due to continued growth and innovations in the field. Ideal dressings should be safe and achieve healing at a reasonable cost with minimum inconvenience to patients. It is mandatory that manufacture and sale of such dressings are approved by the relevant health authority of each country. This article provides manufacturers with an overview regarding regulatory approval procedures for marketing such dressings in different countries and addresses the gaps and challenges in the existing guidelines aimed at maintaining product quality. It provides a comparative analysis of the differences in regulatory requirements and highlights that ongoing discussions and appropriate actions are required to support the continuous development of these dressings. Most countries have their own regulatory guidelines, and the approval processes differ according to the country. Quality parameters concerning the type of material, pore size, sterilization methods, shape and size, and labeling are not discussed in guidelines; therefore, innovators and manufacturers are facing tough challenges to showcase their products in the market, and this further leads to either lack of market availability or high cost of such dressings.Conclusion: Development of common quality guidelines is essential for market availability of low-cost, high-quality dressings.