RESUMO
Background: COVID-19, a Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2), was first diagnosed in the patients from Wuhan, China, in December 2019. Within a cou-ple of months of infection, it was declared as pandemic by the World health organization. COVID-19 has become the most contagious infection with a serious threat to global health. In this review, we aimed to discuss the pathogenesis, diagnostics, current treatments and potential vaccines for COVID-19. Method(s): An extensive literature search was conducted using keywords "COVID-19";"Coron-avirus";"SARS-Cov-2";"SARS" in public domains of Google, Google scholar, PubMed, and Sci-enceDirect. Selected articles were used to construct this review. Result(s): SARS-Cov-2 uses the Spike (S) protein on its surface to recognize the receptor on an-giotensin-converting enzyme 2 (ACE2) and bind with 10-folds greater affinity than SARS-Cov-1. Molecular assays and immunoassays are the most frequently used tests, whereas computed tomog-raphy (CT) scans and artificial intelligence enabled diagnostic tools were also used in patients. In therapeutic treatment, few drugs were repurposed and about 23 therapeutic molecules, including the repurposed drugs are at different stages of the clinical trial. Similarly, the development of vaccines is also in the pipeline. Few countries have managed well to contain the spread by rapid testing and identifying the clusters. Conclusion(s): Till now, the acute complications and mortality of COVID-19 have been linked to pre-existing comorbid conditions or age. Besides the development of therapeutic strategies that include drugs and vaccine, the long term implication of COVID-19 infection in terms of the disor-der/disability in the cured/discharged patients is a new area to investigate.Copyright © 2021 Bentham Science Publishers.
RESUMO
Artificial intelligence (AI) is a branch of computer science that allows machines to work efficiently, can analyze complex data. The research focused on AI has increased tremendously, and its role in healthcare service and research is emerging at a greater pace. This review elaborates on the opportunities and challenges of AI in healthcare and pharmaceutical research. The literature was collected from domains such as PubMed, Science Direct and Google scholar using specific keywords and phrases such as ‘Artificial intelligence', ‘Pharmaceutical research', ‘drug discovery', ‘clinical trial', ‘disease diagnosis', etc. to select the research and review articles published within the last five years. The application of AI in disease diagnosis, digital therapy, personalized treatment, drug discovery and forecasting epidemics or pandemics was extensively reviewed in this article. Deep learning and neural networks are the most used AI technologies;Bayesian nonparametric models are the potential technologies for clinical trial design;natural language processing and wearable devices are used in patient identification and clinical trial monitoring. Deep learning and neural networks were applied in predicting the outbreak of seasonal influenza, Zika, Ebola, Tuberculosis and COVID-19. With the advancement of AI technologies, the scientific community may witness rapid and cost-effective healthcare and pharmaceutical research as well as provide improved service to the general public. © 2023 by the authors.