A systematic review on Drug Re-profiling/Re-Purposing

Hardcore capability of drug repurposing has allowed rising population of diversified diseased patients to approach various medications with known safety profiles. In an ongoing scenario considering current pharmaceutical market, we have numerous drugs that are approved and repurposed by the U.S. Food and Drug Administration. Developing and bringing a novel drug molecule from the laboratory to a market requires a lot of investment in terms of money, efforts, and time. On the other hand, repurposing a drug holds the capability of bringing out best cures with harmless, ease availability and inexpensive quality. Sildenafil, Chloroquine, Metformin are some examples of repurposed drug used in multiple disease models. Despite numerous challenges, drug repurposing stood to be a core component to any comprehensive drug re-discovering strategies which has been planned to bring benefit to the patients suffering from a wide variety of dreadful ailments. In this review, we have discussed the various repurposed drugs in numerous types of cancer, deadly novel coronavirus (SARS-CoV-2) and some orphan diseases. This paper holds various examples of drugs which are still under clinical trial and have high chances of being approved as repurposed drugs benefitting humankind

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Proceedings of APP 11th ANNUAL CONVENTION AND 5th INDO SWISS CONFERENCE 16 – 17, DEC-2022 &nbsp

A Brief Description of Different Types of Cancers and Role of Some Herbs & Bioactive Compounds in Lung Cancer Management

Cancer immunotherapy has considerably raised patient survival rates and significantly improved patients\u27 quality of life in comparison to the gold standard of care, which includes chemotherapy, radiation therapy, and surgery. Immunotherapy has firmly established itself as a novel pillar of cancer care across the board, from the metastatic stage all the way through adjuvant and neoadjuvant treatment in a wide variety of cancer types. In this overview, the primary emphasis will be placed on the seminal moments in the history of cancer immunotherapy that prepared the way for the cutting-edge treatments that are available today. Cancer treatment that makes use of medicinal herbs and the phytocompounds that can be obtained from those herbs is becoming an increasingly attractive option. It has been demonstrated in a number of clinical studies that the use of herbal medicines in conjunction with conventional therapy can increase survival rates, immunological modulation, and quality of life (QOL) in patients who have cancer. In addition to this, we highlight the challenges and restrictions currently faced by cancer checkpoint immunotherapy as well as the cutting-edge research being conducted in the fields of individualized cancer vaccines, autoimmunity, the microbiome, the microenvironment of tumors, and metabolomics to find solutions to these problems. For hundreds of years, practitioners of traditional medicine have depended on treatments derived from plants. Many studies on their use have been carried out all over the world, and some of the findings have led to the development of medicines that are derived from plants. The global market for medicinal plant products is estimated to be worth more than one hundred billion dollars each year. This research investigates the role, contributions, and utility of medicinal plants in the context of the current strategic methods to disease prevention, notably lung cancer, which is a public health concern. The focus of this research is on the current strategic approaches to disease prevention

Mechanisms of Laser-Tissue Interaction: II. Tissue Thermal Properties

Laser-tissue interaction is of great interest due to its significant application in biomedical optics in both diagnostic and treatment purposes. Major aspects of the laser-tissue interaction which has to be considered in biomedical studies are the thermal properties of the tissue and the thermal changes caused by the interaction of light and tissue. In this review paper the effects of light on the tissue at different temperatures are discussed. Then, due to the noticeable importance of studying the heat transfer quantitatively, the equations governing this phenomenon are presented. Finally a method of medical diagnosis called thermography and some of its applications are explained

In Silico Drug Repurposing: An Effective Tool to Accelerate the Drug Discovery Process

Repurposing “old” drugs to treat both common and rare diseases is increasingly emerging as an attractive proposition due to the use of de-risked compounds, with potential for lower overall development costs and shorter development timelines. This is due to the high attrition rates, significant costs, and slow pace of new drug discovery and development. Drug repurposing is the process of finding new, more efficient uses for already-available medications. Numerous computational drug repurposing techniques exist, there are three main types of computational drug-repositioning methods used on COVID-19 are network-based models, structure-based methods and artificial intelligence (AI) methods used to discover novel drug–target relationships useful for new therapies. In order to assess how a chemical molecule can interact with its biological counterpart and try to find new uses for medicines already on the market, structure-based techniques made it possible to identify small chemical compounds capable of binding macromolecular targets. In this chapter, we explain strategies for drug repurposing, discuss about difficulties encountered by the repurposing community, and suggest reported drugs through the drug repurposing. Moreover, metabolic and drug discovery network resources, tools for network construction, analysis and protein–protein interaction analysis to enable drug repurposing to reach its full potential

Advanced Computational Methods for Oncological Image Analysis

[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians’ unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations—such as segmentation, co-registration, classification, and dimensionality reduction—and multi-omics data integration.

RECENT ADVANCES IN MOLECULAR MEDICINE AND TRANSLATIONAL RESEARCH

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