COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long /Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Artificial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications.

On February 19, 2020, the first case of a patient infected with Coronavirus Disease-2019 (COVID-19) was announced in Iran. The number of infected patients increased rapidly, and all health care centers faced an extremely challenging situation in Iran. The centers had to adopt new regulations and approaches to keep their patients and staff safe while providing service to society. Patients diagnosed with a malignancy are at a higher risk for infection with COVID-19 with a poorer prognosis. The Pardis Noor Radiology-Oncology center is a private center in Tehran composed of different departments, including radiation therapy and chemotherapy. Soon after the outbreak, we changed our rules and regulations for patients and staff. This is a report from a private radiology-oncology center in Tehran during the COVID-19 outbreak.

Highlight The emergence of CAR-T cell therapy with its exciting results attained in patients with relapsed and refractory hematological malignancies is considered as the biggest advance in cellular cancer immunotherapy. However, severe side effects and toxicity stir concerns regarding the safety of CAR-T cell treatments.Most of CAR-T cell therapies are currently autologous small-scale treatments for patients suffering from B cell malignancies due to the safety concerns about the potential development of a GVHD in allogeneic therapies. So, allogeneic therapies have been less effective than autologous ones. High cost and highly variable manufacturing processes are other limitations on the way of CAR-T cell therapy. In contrast to the unprecedented responses achieved through using CD19-CAR-T cells in the treatment of ALL, this type of treatment has not shown the same results in the battle against solid tumors that is partly related to different characteristics and microenvironment of solid tumors that limit the success of CAR-T cell therapies in patients with solid tumors. Immune checkpoint therapies with previously reported reproducible beneficial effects in 20–30% of patients with different incurable cancers have serious side effects and considerable cost of repeated administration. Also, recently most patients have not responded effectively to these therapies. In contrast, CAR-T cell therapy has two characteristics that may compensate for the limitations of immune checkpoint therapies. Firstly, only one administration of the engineered T cells is needed for long lasting effectiveness of the therapy. Secondly, more than 90% of patients suffering from ALL respond to CAR-T cell therapy, a result which is not obtained through administration of the immune checkpoints. Future development of CAR-T cell technology should address concerns related to the safety of the treatment and improve toxicity management. Also, it should extend the application of technology in diseases where its effectiveness has been demonstrated and opt for more targets and cancers.

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